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    <title>The NeuralPod</title>
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    <description>Welcome to The NeuralPod.

The 0-1 machine learning podcast.

Chatting with ML Leaders, Researchers and Engineers who've built models, systems and products 0-1.</description>
    <copyright>NeuralRec Limited - The NeuralPod</copyright>
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    <language>en</language>
    <pubDate>Thu, 07 May 2026 13:51:04 -0700</pubDate>
    <lastBuildDate>Thu, 07 May 2026 13:51:16 -0700</lastBuildDate>
    <link>https://neuralrec.ai</link>
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      <title>The NeuralPod</title>
      <link>https://neuralrec.ai</link>
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    <itunes:category text="Technology"/>
    <itunes:category text="Business"/>
    <itunes:type>serial</itunes:type>
    <itunes:author>Chris Coyne</itunes:author>
    <itunes:image href="https://img.transistorcdn.com/xk_Egv444iLmadR03PHuPb-etSjDEl5dJRJmQXUE6uw/rs:fill:0:0:1/w:1400/h:1400/q:60/mb:500000/aHR0cHM6Ly9pbWct/dXBsb2FkLXByb2R1/Y3Rpb24udHJhbnNp/c3Rvci5mbS82MDNj/NTUyN2ZkNGU1OTZj/MDlhMTZiYTE5ZDUx/ZTJlYS5qcGc.jpg"/>
    <itunes:summary>Welcome to The NeuralPod.

The 0-1 machine learning podcast.

Chatting with ML Leaders, Researchers and Engineers who've built models, systems and products 0-1.</itunes:summary>
    <itunes:subtitle>Welcome to The NeuralPod.</itunes:subtitle>
    <itunes:keywords>Machine Learning, AI, Deep Learning, Recommender Systems, Reinforcement Learning</itunes:keywords>
    <itunes:owner>
      <itunes:name>Chris Coyne</itunes:name>
      <itunes:email>Chris@neuralrec.ai</itunes:email>
    </itunes:owner>
    <itunes:complete>No</itunes:complete>
    <itunes:explicit>No</itunes:explicit>
    <item>
      <title>Vidhi Chugh - Governance, Ethics and The Chief AI Officer.</title>
      <itunes:episode>5</itunes:episode>
      <podcast:episode>5</podcast:episode>
      <itunes:title>Vidhi Chugh - Governance, Ethics and The Chief AI Officer.</itunes:title>
      <itunes:episodeType>full</itunes:episodeType>
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      <link>https://share.transistor.fm/s/280aed82</link>
      <description>
        <![CDATA[<p>We had an insightful chat about the role of the Chief AI Officer in light of the recent White House announcements. </p><p>Vidhi shared her experience developing AI strategies in various organisations and the importance of starting with business objectives in mind. </p><p>Some topics we discussed: <br> <br>✅ Vidhi's career and lessons learnt<br>✅ Examing business goals and using AI to achieve them<br>✅ The EU AI Act and its example of categorising AI risks and building governance frameworks<br>✅ Explainable AI is essential for users to understand how AI systems arrive at decisions<br>✅ Accountability is shared. From developers to CEOs, everyone has a role to play in ensuring AI is used ethically </p><p>Tune in for this insightful episode</p><p><br></p>]]>
      </description>
      <content:encoded>
        <![CDATA[<p>We had an insightful chat about the role of the Chief AI Officer in light of the recent White House announcements. </p><p>Vidhi shared her experience developing AI strategies in various organisations and the importance of starting with business objectives in mind. </p><p>Some topics we discussed: <br> <br>✅ Vidhi's career and lessons learnt<br>✅ Examing business goals and using AI to achieve them<br>✅ The EU AI Act and its example of categorising AI risks and building governance frameworks<br>✅ Explainable AI is essential for users to understand how AI systems arrive at decisions<br>✅ Accountability is shared. From developers to CEOs, everyone has a role to play in ensuring AI is used ethically </p><p>Tune in for this insightful episode</p><p><br></p>]]>
      </content:encoded>
      <pubDate>Mon, 29 Jul 2024 14:53:09 -0700</pubDate>
      <author>Chris Coyne</author>
      <enclosure url="https://prfx.byspotify.com/e/media.transistor.fm/280aed82/6b173e7b.mp3" length="26376922" type="audio/mpeg"/>
      <itunes:author>Chris Coyne</itunes:author>
      <itunes:duration>1648</itunes:duration>
      <itunes:summary>
        <![CDATA[<p>We had an insightful chat about the role of the Chief AI Officer in light of the recent White House announcements. </p><p>Vidhi shared her experience developing AI strategies in various organisations and the importance of starting with business objectives in mind. </p><p>Some topics we discussed: <br> <br>✅ Vidhi's career and lessons learnt<br>✅ Examing business goals and using AI to achieve them<br>✅ The EU AI Act and its example of categorising AI risks and building governance frameworks<br>✅ Explainable AI is essential for users to understand how AI systems arrive at decisions<br>✅ Accountability is shared. From developers to CEOs, everyone has a role to play in ensuring AI is used ethically </p><p>Tune in for this insightful episode</p><p><br></p>]]>
      </itunes:summary>
      <itunes:keywords>Machine Learning, AI, Deep Learning, Recommender Systems, Reinforcement Learning</itunes:keywords>
      <itunes:explicit>No</itunes:explicit>
    </item>
    <item>
      <title>Alexey Strygin - AI and Aging </title>
      <itunes:episode>1</itunes:episode>
      <podcast:episode>1</podcast:episode>
      <itunes:title>Alexey Strygin - AI and Aging </itunes:title>
      <itunes:episodeType>full</itunes:episodeType>
      <guid isPermaLink="false">37c98ad6-aa1e-43f2-90e9-253630e7047c</guid>
      <link>https://share.transistor.fm/s/6ae04570</link>
      <description>
        <![CDATA[<p>We discuss all things Longevity AI with Alexey Strying, subject matter expert. </p><p>We also discuss how to transition your career to longevity where Alexey draws on his own experience to help others.</p><p>Speaking about Gero, Gerosense, the biotech industry and the importance of data. </p><p>At the end, Alexey also shares some 80/20 longevity tips that he applies today that can increase healthy life expectancy by 5-10 years.</p>]]>
      </description>
      <content:encoded>
        <![CDATA[<p>We discuss all things Longevity AI with Alexey Strying, subject matter expert. </p><p>We also discuss how to transition your career to longevity where Alexey draws on his own experience to help others.</p><p>Speaking about Gero, Gerosense, the biotech industry and the importance of data. </p><p>At the end, Alexey also shares some 80/20 longevity tips that he applies today that can increase healthy life expectancy by 5-10 years.</p>]]>
      </content:encoded>
      <pubDate>Wed, 31 Jul 2024 06:01:53 -0700</pubDate>
      <author>Chris Coyne</author>
      <enclosure url="https://prfx.byspotify.com/e/media.transistor.fm/6ae04570/4b10e3ec.mp3" length="70458631" type="audio/mpeg"/>
      <itunes:author>Chris Coyne</itunes:author>
      <itunes:duration>4403</itunes:duration>
      <itunes:summary>
        <![CDATA[<p>We discuss all things Longevity AI with Alexey Strying, subject matter expert. </p><p>We also discuss how to transition your career to longevity where Alexey draws on his own experience to help others.</p><p>Speaking about Gero, Gerosense, the biotech industry and the importance of data. </p><p>At the end, Alexey also shares some 80/20 longevity tips that he applies today that can increase healthy life expectancy by 5-10 years.</p>]]>
      </itunes:summary>
      <itunes:keywords>Longevity, AI, Deep Learning, Machine Learning</itunes:keywords>
      <itunes:explicit>No</itunes:explicit>
    </item>
    <item>
      <title>Gilbert Cassar - AI and Energy</title>
      <itunes:episode>2</itunes:episode>
      <podcast:episode>2</podcast:episode>
      <itunes:title>Gilbert Cassar - AI and Energy</itunes:title>
      <itunes:episodeType>full</itunes:episodeType>
      <guid isPermaLink="false">32b5f426-be89-4cb7-a526-5be8d2605dc2</guid>
      <link>https://share.transistor.fm/s/b0f05978</link>
      <description>
        <![CDATA[<p>Curious about how Generative AI can transform the UK energy sector as we move towards net zero?</p><p>It was great to chat with Gilbert Cassar, Chief AI Scientist for Energy at Accenture, who discusses how Generative AI is bringing value and solving longstanding problems in the industry. </p><p>It's clear to see Gilbert's passion for the energy industry where AI is solving real-world problems and making a difference. </p><p>In this episode, you will discover:</p><p>✅How to scale AI beyond proof of concept and deliver value at scale <br>✅How AI can enable new low-carbon infrastructure and help consumers save energy<br>✅Why ethical considerations are essential when deploying AI<br>✅How to educate and engage stakeholders on the benefits of AI<br>✅What use cases of Generative AI are already making an impact in the energy sector<br>✅How to build teams with the right skills and future trends in AI<br>✅And more ...</p>]]>
      </description>
      <content:encoded>
        <![CDATA[<p>Curious about how Generative AI can transform the UK energy sector as we move towards net zero?</p><p>It was great to chat with Gilbert Cassar, Chief AI Scientist for Energy at Accenture, who discusses how Generative AI is bringing value and solving longstanding problems in the industry. </p><p>It's clear to see Gilbert's passion for the energy industry where AI is solving real-world problems and making a difference. </p><p>In this episode, you will discover:</p><p>✅How to scale AI beyond proof of concept and deliver value at scale <br>✅How AI can enable new low-carbon infrastructure and help consumers save energy<br>✅Why ethical considerations are essential when deploying AI<br>✅How to educate and engage stakeholders on the benefits of AI<br>✅What use cases of Generative AI are already making an impact in the energy sector<br>✅How to build teams with the right skills and future trends in AI<br>✅And more ...</p>]]>
      </content:encoded>
      <pubDate>Wed, 31 Jul 2024 06:06:50 -0700</pubDate>
      <author>Chris Coyne</author>
      <enclosure url="https://prfx.byspotify.com/e/media.transistor.fm/b0f05978/6ece6316.mp3" length="34454544" type="audio/mpeg"/>
      <itunes:author>Chris Coyne</itunes:author>
      <itunes:duration>2153</itunes:duration>
      <itunes:summary>
        <![CDATA[<p>Curious about how Generative AI can transform the UK energy sector as we move towards net zero?</p><p>It was great to chat with Gilbert Cassar, Chief AI Scientist for Energy at Accenture, who discusses how Generative AI is bringing value and solving longstanding problems in the industry. </p><p>It's clear to see Gilbert's passion for the energy industry where AI is solving real-world problems and making a difference. </p><p>In this episode, you will discover:</p><p>✅How to scale AI beyond proof of concept and deliver value at scale <br>✅How AI can enable new low-carbon infrastructure and help consumers save energy<br>✅Why ethical considerations are essential when deploying AI<br>✅How to educate and engage stakeholders on the benefits of AI<br>✅What use cases of Generative AI are already making an impact in the energy sector<br>✅How to build teams with the right skills and future trends in AI<br>✅And more ...</p>]]>
      </itunes:summary>
      <itunes:keywords>Machine Learning, Generative AI, Deep Learning, LLM</itunes:keywords>
      <itunes:explicit>No</itunes:explicit>
    </item>
    <item>
      <title>Rishabh Mehrotra - Exploring RecSys and Gen AI</title>
      <itunes:episode>3</itunes:episode>
      <podcast:episode>3</podcast:episode>
      <itunes:title>Rishabh Mehrotra - Exploring RecSys and Gen AI</itunes:title>
      <itunes:episodeType>full</itunes:episodeType>
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      <link>https://share.transistor.fm/s/37132887</link>
      <description>
        <![CDATA[<p>We enjoyed sitting down with Rishabh Mehrotra recently, discussing RecSys and LLM problems, specifically how they intersect. </p><p>Rishabh is an all-around great person, he is committed to driving forward the RecSys/Gen AI community with open-source knowledge.</p><p>Some of the topics we covered:</p><p>✅How RecSys and LLMs overlap, and why it’s important <br>✅Managing multistakeholder recommender systems <br>✅RecSys cold start problems <br>✅Building teams to win in RecSys and Gen AI <br>✅Ethical accountability</p><p>Stay tuned as we continue to connect with more thought leaders over the coming months!</p>]]>
      </description>
      <content:encoded>
        <![CDATA[<p>We enjoyed sitting down with Rishabh Mehrotra recently, discussing RecSys and LLM problems, specifically how they intersect. </p><p>Rishabh is an all-around great person, he is committed to driving forward the RecSys/Gen AI community with open-source knowledge.</p><p>Some of the topics we covered:</p><p>✅How RecSys and LLMs overlap, and why it’s important <br>✅Managing multistakeholder recommender systems <br>✅RecSys cold start problems <br>✅Building teams to win in RecSys and Gen AI <br>✅Ethical accountability</p><p>Stay tuned as we continue to connect with more thought leaders over the coming months!</p>]]>
      </content:encoded>
      <pubDate>Wed, 31 Jul 2024 06:18:03 -0700</pubDate>
      <author>Chris Coyne</author>
      <enclosure url="https://prfx.byspotify.com/e/media.transistor.fm/37132887/f1e05e23.mp3" length="79723208" type="audio/mpeg"/>
      <itunes:author>Chris Coyne</itunes:author>
      <itunes:duration>4982</itunes:duration>
      <itunes:summary>
        <![CDATA[<p>We enjoyed sitting down with Rishabh Mehrotra recently, discussing RecSys and LLM problems, specifically how they intersect. </p><p>Rishabh is an all-around great person, he is committed to driving forward the RecSys/Gen AI community with open-source knowledge.</p><p>Some of the topics we covered:</p><p>✅How RecSys and LLMs overlap, and why it’s important <br>✅Managing multistakeholder recommender systems <br>✅RecSys cold start problems <br>✅Building teams to win in RecSys and Gen AI <br>✅Ethical accountability</p><p>Stay tuned as we continue to connect with more thought leaders over the coming months!</p>]]>
      </itunes:summary>
      <itunes:keywords>Machine Learning</itunes:keywords>
      <itunes:explicit>No</itunes:explicit>
    </item>
    <item>
      <title>Sumit Singh - Digital Twins, Simulation and AI</title>
      <itunes:episode>4</itunes:episode>
      <podcast:episode>4</podcast:episode>
      <itunes:title>Sumit Singh - Digital Twins, Simulation and AI</itunes:title>
      <itunes:episodeType>full</itunes:episodeType>
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      <link>https://share.transistor.fm/s/ccf09cf1</link>
      <description>
        <![CDATA[<p>It was great to be joined by Sumit Singh, a Digital Twin expert and champion of the field. </p><p>Sumit dives into the fascinating world of digital twins and their potential to transform industries and society.</p><p>In this episode, we explore:</p><p>✅What are digital twins? Learn about these virtual replicas and their data magic<br>✅Benefits for businesses and people. <br>✅How digital twins optimise systems and improve our world.<br>✅Challenges and steps organisations can take to harness the power<br>✅The future with digital twins. <br>✅Their role in simulation, the metaverse<br>✅The Digital Twin skills gap and how to address it</p><p>Intrigued? Tune in to the full episode and explore the cutting-edge of digital twin technology!</p>]]>
      </description>
      <content:encoded>
        <![CDATA[<p>It was great to be joined by Sumit Singh, a Digital Twin expert and champion of the field. </p><p>Sumit dives into the fascinating world of digital twins and their potential to transform industries and society.</p><p>In this episode, we explore:</p><p>✅What are digital twins? Learn about these virtual replicas and their data magic<br>✅Benefits for businesses and people. <br>✅How digital twins optimise systems and improve our world.<br>✅Challenges and steps organisations can take to harness the power<br>✅The future with digital twins. <br>✅Their role in simulation, the metaverse<br>✅The Digital Twin skills gap and how to address it</p><p>Intrigued? Tune in to the full episode and explore the cutting-edge of digital twin technology!</p>]]>
      </content:encoded>
      <pubDate>Wed, 31 Jul 2024 06:19:00 -0700</pubDate>
      <author>Chris Coyne</author>
      <enclosure url="https://prfx.byspotify.com/e/media.transistor.fm/ccf09cf1/fe88bf4c.mp3" length="47650368" type="audio/mpeg"/>
      <itunes:author>Chris Coyne</itunes:author>
      <itunes:duration>2978</itunes:duration>
      <itunes:summary>
        <![CDATA[<p>It was great to be joined by Sumit Singh, a Digital Twin expert and champion of the field. </p><p>Sumit dives into the fascinating world of digital twins and their potential to transform industries and society.</p><p>In this episode, we explore:</p><p>✅What are digital twins? Learn about these virtual replicas and their data magic<br>✅Benefits for businesses and people. <br>✅How digital twins optimise systems and improve our world.<br>✅Challenges and steps organisations can take to harness the power<br>✅The future with digital twins. <br>✅Their role in simulation, the metaverse<br>✅The Digital Twin skills gap and how to address it</p><p>Intrigued? Tune in to the full episode and explore the cutting-edge of digital twin technology!</p>]]>
      </itunes:summary>
      <itunes:keywords>Digital Twin, AI, VR, Virtual Reality.</itunes:keywords>
      <itunes:explicit>No</itunes:explicit>
    </item>
    <item>
      <title>Jan Krasnodebski - Recommender Systems, Pricing and Travel</title>
      <itunes:episode>6</itunes:episode>
      <podcast:episode>6</podcast:episode>
      <itunes:title>Jan Krasnodebski - Recommender Systems, Pricing and Travel</itunes:title>
      <itunes:episodeType>full</itunes:episodeType>
      <guid isPermaLink="false">1e56af5c-7b6c-467c-8c03-342aac848f29</guid>
      <link>https://share.transistor.fm/s/b1c0f045</link>
      <description>
        <![CDATA[<p>Have you ever wondered why and how certain holidays and flights are priced then recommended?</p><p>In this episode of What AI Means for Us by NeuralRec. Chris is joined by Jan Krasnodebski, recommender systems and pricing subject matter expert. With more than 13 years of experience at Expedia and a strong background in pricing and recommendations, Jan shares his expertise on several key topics:</p><p>✅The crucial role of pricing in business strategy and its impact on profitability.<br>✅Unique challenges are faced in pricing for various industries, including med tech and travel.<br>✅How generative AI is transforming pricing and recommendations, and its current limitations.<br>✅Multi-stakerholder recommendations, managing them effectively.<br>✅The integration of AI in booking platforms, enhancing personalization and user experience.<br>✅Handling ethical implications and ensuring fairness in AI models.<br>✅Skills and leadership qualities required for success in AI-focused roles.</p><p>Join us for a deep dive into the dynamic world of pricing and AI, and how these elements shape the modern travel industry.</p>]]>
      </description>
      <content:encoded>
        <![CDATA[<p>Have you ever wondered why and how certain holidays and flights are priced then recommended?</p><p>In this episode of What AI Means for Us by NeuralRec. Chris is joined by Jan Krasnodebski, recommender systems and pricing subject matter expert. With more than 13 years of experience at Expedia and a strong background in pricing and recommendations, Jan shares his expertise on several key topics:</p><p>✅The crucial role of pricing in business strategy and its impact on profitability.<br>✅Unique challenges are faced in pricing for various industries, including med tech and travel.<br>✅How generative AI is transforming pricing and recommendations, and its current limitations.<br>✅Multi-stakerholder recommendations, managing them effectively.<br>✅The integration of AI in booking platforms, enhancing personalization and user experience.<br>✅Handling ethical implications and ensuring fairness in AI models.<br>✅Skills and leadership qualities required for success in AI-focused roles.</p><p>Join us for a deep dive into the dynamic world of pricing and AI, and how these elements shape the modern travel industry.</p>]]>
      </content:encoded>
      <pubDate>Tue, 06 Aug 2024 06:40:31 -0700</pubDate>
      <author>Chris Coyne</author>
      <enclosure url="https://prfx.byspotify.com/e/media.transistor.fm/b1c0f045/b5c36578.mp3" length="64261252" type="audio/mpeg"/>
      <itunes:author>Chris Coyne</itunes:author>
      <itunes:duration>4016</itunes:duration>
      <itunes:summary>
        <![CDATA[<p>Have you ever wondered why and how certain holidays and flights are priced then recommended?</p><p>In this episode of What AI Means for Us by NeuralRec. Chris is joined by Jan Krasnodebski, recommender systems and pricing subject matter expert. With more than 13 years of experience at Expedia and a strong background in pricing and recommendations, Jan shares his expertise on several key topics:</p><p>✅The crucial role of pricing in business strategy and its impact on profitability.<br>✅Unique challenges are faced in pricing for various industries, including med tech and travel.<br>✅How generative AI is transforming pricing and recommendations, and its current limitations.<br>✅Multi-stakerholder recommendations, managing them effectively.<br>✅The integration of AI in booking platforms, enhancing personalization and user experience.<br>✅Handling ethical implications and ensuring fairness in AI models.<br>✅Skills and leadership qualities required for success in AI-focused roles.</p><p>Join us for a deep dive into the dynamic world of pricing and AI, and how these elements shape the modern travel industry.</p>]]>
      </itunes:summary>
      <itunes:keywords>Machine Learning, AI, Deep Learning, Recommender Systems, Reinforcement Learning</itunes:keywords>
      <itunes:explicit>No</itunes:explicit>
    </item>
    <item>
      <title>Tetiana Torovets - Property, Personalisation and Search Systems</title>
      <itunes:episode>7</itunes:episode>
      <podcast:episode>7</podcast:episode>
      <itunes:title>Tetiana Torovets - Property, Personalisation and Search Systems</itunes:title>
      <itunes:episodeType>full</itunes:episodeType>
      <guid isPermaLink="false">385f271c-c75d-4029-98e3-6362d008e89c</guid>
      <link>https://share.transistor.fm/s/c6798200</link>
      <description>
        <![CDATA[<p>In this episode, we sit down with Tetiana Torovets, Head of Data Science at QuintoAndar. Tetiana shares her journey from banking and consulting in FinTech to leading a team at ThredUP and now at QuintoAndar. </p><p>We explore the intricate challenges of creating recommender systems for marketplaces, the balance between classical machine learning and the latest neural networks, and the application of AI-driven search assistants. </p><p>Tune in for insights on metrics, experimentation, and the future of AI in property tech.</p><p>✅ Tetiana's Career Journey in Data Science<br>✅ Differences in Machine Learning Across Industries<br>✅ Challenges in Marketplace Recommendations<br>✅ Technical Insights and Multi-Objective Models<br>✅ Search Assistants and Future of Property Tech<br>✅ Leadership and Hiring in Machine Learning</p>]]>
      </description>
      <content:encoded>
        <![CDATA[<p>In this episode, we sit down with Tetiana Torovets, Head of Data Science at QuintoAndar. Tetiana shares her journey from banking and consulting in FinTech to leading a team at ThredUP and now at QuintoAndar. </p><p>We explore the intricate challenges of creating recommender systems for marketplaces, the balance between classical machine learning and the latest neural networks, and the application of AI-driven search assistants. </p><p>Tune in for insights on metrics, experimentation, and the future of AI in property tech.</p><p>✅ Tetiana's Career Journey in Data Science<br>✅ Differences in Machine Learning Across Industries<br>✅ Challenges in Marketplace Recommendations<br>✅ Technical Insights and Multi-Objective Models<br>✅ Search Assistants and Future of Property Tech<br>✅ Leadership and Hiring in Machine Learning</p>]]>
      </content:encoded>
      <pubDate>Fri, 08 Nov 2024 01:00:00 -0800</pubDate>
      <author>Chris Coyne</author>
      <enclosure url="https://prfx.byspotify.com/e/media.transistor.fm/c6798200/5289a7b8.mp3" length="56212281" type="audio/mpeg"/>
      <itunes:author>Chris Coyne</itunes:author>
      <itunes:duration>3513</itunes:duration>
      <itunes:summary>
        <![CDATA[<p>In this episode, we sit down with Tetiana Torovets, Head of Data Science at QuintoAndar. Tetiana shares her journey from banking and consulting in FinTech to leading a team at ThredUP and now at QuintoAndar. </p><p>We explore the intricate challenges of creating recommender systems for marketplaces, the balance between classical machine learning and the latest neural networks, and the application of AI-driven search assistants. </p><p>Tune in for insights on metrics, experimentation, and the future of AI in property tech.</p><p>✅ Tetiana's Career Journey in Data Science<br>✅ Differences in Machine Learning Across Industries<br>✅ Challenges in Marketplace Recommendations<br>✅ Technical Insights and Multi-Objective Models<br>✅ Search Assistants and Future of Property Tech<br>✅ Leadership and Hiring in Machine Learning</p>]]>
      </itunes:summary>
      <itunes:keywords>Machine Learning, AI, Deep Learning, Recommender Systems, Reinforcement Learning</itunes:keywords>
      <itunes:explicit>No</itunes:explicit>
    </item>
    <item>
      <title>Marco Del Tredici - Agentic AI, LLM Evals and Research</title>
      <itunes:episode>8</itunes:episode>
      <podcast:episode>8</podcast:episode>
      <itunes:title>Marco Del Tredici - Agentic AI, LLM Evals and Research</itunes:title>
      <itunes:episodeType>full</itunes:episodeType>
      <guid isPermaLink="false">a3103610-166f-4d69-89d3-8d5d380f9381</guid>
      <link>https://share.transistor.fm/s/c9de0e0e</link>
      <description>
        <![CDATA[<p>In this episode, we chat with Marco, who is extremely passionate and accomplished in NLP research; with a diverse background from the University of Amsterdam to industry giants like Amazon and Cohere. Marco shares his unique transition from academia to industry, his work on fake news detection, and his contributions to advancements in Amazon Alexa's conversational abilities. </p><p>We dig into the future of Large Language Models (LLMs), the challenges with LLM evals, and the promise of AI agents in simplifying daily tasks. Marco also discusses the emerging research directions and the potential of AI agents becoming integral to our daily lives.</p><p><a href="https://www.youtube.com/watch?v=hDsbAxAA2Co&amp;t=0s">00:00</a> Introduction and Guest Welcome<br><a href="https://www.youtube.com/watch?v=hDsbAxAA2Co&amp;t=61s">01:01</a>  Background and Research Journey<br><a href="https://www.youtube.com/watch?v=hDsbAxAA2Co&amp;t=388s">06:28</a> Transition from Academia to Industry<br><a href="https://www.youtube.com/watch?v=hDsbAxAA2Co&amp;t=613s">10:13</a> LLMs and Their Future<br><a href="https://www.youtube.com/watch?v=hDsbAxAA2Co&amp;t=910s">15:10</a> Evaluating LLMs<br><a href="https://www.youtube.com/watch?v=hDsbAxAA2Co&amp;t=1423s">23:43</a> Interpretability and Explainability<br><a href="https://www.youtube.com/watch?v=hDsbAxAA2Co&amp;t=1730s">28:50</a> Understanding AI Agents<br><a href="https://www.youtube.com/watch?v=hDsbAxAA2Co&amp;t=2246s">37:26</a> Research and Future of AI Agents<br><a href="https://www.youtube.com/watch?v=hDsbAxAA2Co&amp;t=3134s">52:14</a> Predictions and Closing Remarks</p><p><br>Connect with Marco: https://www.linkedin.com/in/marco-del-tredici-316a2984/</p>]]>
      </description>
      <content:encoded>
        <![CDATA[<p>In this episode, we chat with Marco, who is extremely passionate and accomplished in NLP research; with a diverse background from the University of Amsterdam to industry giants like Amazon and Cohere. Marco shares his unique transition from academia to industry, his work on fake news detection, and his contributions to advancements in Amazon Alexa's conversational abilities. </p><p>We dig into the future of Large Language Models (LLMs), the challenges with LLM evals, and the promise of AI agents in simplifying daily tasks. Marco also discusses the emerging research directions and the potential of AI agents becoming integral to our daily lives.</p><p><a href="https://www.youtube.com/watch?v=hDsbAxAA2Co&amp;t=0s">00:00</a> Introduction and Guest Welcome<br><a href="https://www.youtube.com/watch?v=hDsbAxAA2Co&amp;t=61s">01:01</a>  Background and Research Journey<br><a href="https://www.youtube.com/watch?v=hDsbAxAA2Co&amp;t=388s">06:28</a> Transition from Academia to Industry<br><a href="https://www.youtube.com/watch?v=hDsbAxAA2Co&amp;t=613s">10:13</a> LLMs and Their Future<br><a href="https://www.youtube.com/watch?v=hDsbAxAA2Co&amp;t=910s">15:10</a> Evaluating LLMs<br><a href="https://www.youtube.com/watch?v=hDsbAxAA2Co&amp;t=1423s">23:43</a> Interpretability and Explainability<br><a href="https://www.youtube.com/watch?v=hDsbAxAA2Co&amp;t=1730s">28:50</a> Understanding AI Agents<br><a href="https://www.youtube.com/watch?v=hDsbAxAA2Co&amp;t=2246s">37:26</a> Research and Future of AI Agents<br><a href="https://www.youtube.com/watch?v=hDsbAxAA2Co&amp;t=3134s">52:14</a> Predictions and Closing Remarks</p><p><br>Connect with Marco: https://www.linkedin.com/in/marco-del-tredici-316a2984/</p>]]>
      </content:encoded>
      <pubDate>Mon, 27 Jan 2025 10:12:41 -0800</pubDate>
      <author>Chris Coyne</author>
      <enclosure url="https://prfx.byspotify.com/e/media.transistor.fm/c9de0e0e/cb94f75a.mp3" length="53049578" type="audio/mpeg"/>
      <itunes:author>Chris Coyne</itunes:author>
      <itunes:duration>3315</itunes:duration>
      <itunes:summary>
        <![CDATA[<p>In this episode, we chat with Marco, who is extremely passionate and accomplished in NLP research; with a diverse background from the University of Amsterdam to industry giants like Amazon and Cohere. Marco shares his unique transition from academia to industry, his work on fake news detection, and his contributions to advancements in Amazon Alexa's conversational abilities. </p><p>We dig into the future of Large Language Models (LLMs), the challenges with LLM evals, and the promise of AI agents in simplifying daily tasks. Marco also discusses the emerging research directions and the potential of AI agents becoming integral to our daily lives.</p><p><a href="https://www.youtube.com/watch?v=hDsbAxAA2Co&amp;t=0s">00:00</a> Introduction and Guest Welcome<br><a href="https://www.youtube.com/watch?v=hDsbAxAA2Co&amp;t=61s">01:01</a>  Background and Research Journey<br><a href="https://www.youtube.com/watch?v=hDsbAxAA2Co&amp;t=388s">06:28</a> Transition from Academia to Industry<br><a href="https://www.youtube.com/watch?v=hDsbAxAA2Co&amp;t=613s">10:13</a> LLMs and Their Future<br><a href="https://www.youtube.com/watch?v=hDsbAxAA2Co&amp;t=910s">15:10</a> Evaluating LLMs<br><a href="https://www.youtube.com/watch?v=hDsbAxAA2Co&amp;t=1423s">23:43</a> Interpretability and Explainability<br><a href="https://www.youtube.com/watch?v=hDsbAxAA2Co&amp;t=1730s">28:50</a> Understanding AI Agents<br><a href="https://www.youtube.com/watch?v=hDsbAxAA2Co&amp;t=2246s">37:26</a> Research and Future of AI Agents<br><a href="https://www.youtube.com/watch?v=hDsbAxAA2Co&amp;t=3134s">52:14</a> Predictions and Closing Remarks</p><p><br>Connect with Marco: https://www.linkedin.com/in/marco-del-tredici-316a2984/</p>]]>
      </itunes:summary>
      <itunes:keywords>llm, ai agent, agentic ai, reinforcement learning, deep learning, machine learning, </itunes:keywords>
      <itunes:explicit>No</itunes:explicit>
    </item>
    <item>
      <title>Mwenya Kawesha - AI Fundraising, Responsible AI Development and The Impact of a Chief of Staff</title>
      <itunes:episode>9</itunes:episode>
      <podcast:episode>9</podcast:episode>
      <itunes:title>Mwenya Kawesha - AI Fundraising, Responsible AI Development and The Impact of a Chief of Staff</itunes:title>
      <itunes:episodeType>full</itunes:episodeType>
      <guid isPermaLink="false">af561346-37fb-47bf-b781-c0daf5f6a108</guid>
      <link>https://share.transistor.fm/s/1fc45e1d</link>
      <description>
        <![CDATA[<p>Exploring the Role and Impact of a Chief of Staff in AI Startups and fundraising with Mwenya. </p><p><br></p><p>In this episode, we join Chris as he chats with Mwenya, an accomplished Chief of Staff with a rich background in operations and strategy within UK startups.</p><p>Together, they delve into Mwenya's career journey, transitioning from liberal arts to consultancy and AI. Mwenya is a true champion for responsible AI development and its intersection with industries like social media. Discover insights on what has made her successful as Chief of Staff and when the right time to hire one is. </p><p>We also cover the intricacies of AI strategy, the challenges of responsible AI development and why it's vital to any start-up trying to succeed. Mwenya also shares valuable fundraising tips, specifically focused on supporting founders, emphasizing the importance of having a clear vision and understanding the market dynamics.</p><p>00:00 Introduction and Guest Welcome</p><p>00:45 Career Journey and Background</p><p>06:02 Role and Responsibilities of a Chief of Staff</p><p>14:00 AI Strategy and Responsible Development</p><p>35:42 Fundraising Insights and Challenges</p><p>49:51 Conclusion and Final Thoughts</p><p>Connect with Mwenya here: https://www.linkedin.com/in/mwenyakawesha/</p>]]>
      </description>
      <content:encoded>
        <![CDATA[<p>Exploring the Role and Impact of a Chief of Staff in AI Startups and fundraising with Mwenya. </p><p><br></p><p>In this episode, we join Chris as he chats with Mwenya, an accomplished Chief of Staff with a rich background in operations and strategy within UK startups.</p><p>Together, they delve into Mwenya's career journey, transitioning from liberal arts to consultancy and AI. Mwenya is a true champion for responsible AI development and its intersection with industries like social media. Discover insights on what has made her successful as Chief of Staff and when the right time to hire one is. </p><p>We also cover the intricacies of AI strategy, the challenges of responsible AI development and why it's vital to any start-up trying to succeed. Mwenya also shares valuable fundraising tips, specifically focused on supporting founders, emphasizing the importance of having a clear vision and understanding the market dynamics.</p><p>00:00 Introduction and Guest Welcome</p><p>00:45 Career Journey and Background</p><p>06:02 Role and Responsibilities of a Chief of Staff</p><p>14:00 AI Strategy and Responsible Development</p><p>35:42 Fundraising Insights and Challenges</p><p>49:51 Conclusion and Final Thoughts</p><p>Connect with Mwenya here: https://www.linkedin.com/in/mwenyakawesha/</p>]]>
      </content:encoded>
      <pubDate>Mon, 03 Feb 2025 08:04:34 -0800</pubDate>
      <author>Chris Coyne</author>
      <enclosure url="https://prfx.byspotify.com/e/media.transistor.fm/1fc45e1d/274bf99d.mp3" length="48135220" type="audio/mpeg"/>
      <itunes:author>Chris Coyne</itunes:author>
      <itunes:duration>3008</itunes:duration>
      <itunes:summary>
        <![CDATA[<p>Exploring the Role and Impact of a Chief of Staff in AI Startups and fundraising with Mwenya. </p><p><br></p><p>In this episode, we join Chris as he chats with Mwenya, an accomplished Chief of Staff with a rich background in operations and strategy within UK startups.</p><p>Together, they delve into Mwenya's career journey, transitioning from liberal arts to consultancy and AI. Mwenya is a true champion for responsible AI development and its intersection with industries like social media. Discover insights on what has made her successful as Chief of Staff and when the right time to hire one is. </p><p>We also cover the intricacies of AI strategy, the challenges of responsible AI development and why it's vital to any start-up trying to succeed. Mwenya also shares valuable fundraising tips, specifically focused on supporting founders, emphasizing the importance of having a clear vision and understanding the market dynamics.</p><p>00:00 Introduction and Guest Welcome</p><p>00:45 Career Journey and Background</p><p>06:02 Role and Responsibilities of a Chief of Staff</p><p>14:00 AI Strategy and Responsible Development</p><p>35:42 Fundraising Insights and Challenges</p><p>49:51 Conclusion and Final Thoughts</p><p>Connect with Mwenya here: https://www.linkedin.com/in/mwenyakawesha/</p>]]>
      </itunes:summary>
      <itunes:keywords>Agentic AI, LLM, Deepseek, Machine Learning, Chief of Staff, Fundraising, Debt, Ethical AI, Responsible AI</itunes:keywords>
      <itunes:explicit>No</itunes:explicit>
      <podcast:transcript url="https://share.transistor.fm/s/1fc45e1d/transcript.vtt" type="text/vtt" rel="captions"/>
      <podcast:transcript url="https://share.transistor.fm/s/1fc45e1d/transcript.json" type="application/json"/>
    </item>
    <item>
      <title>Erik Schwartz - Aligning AI to Business Strategy, DeepSeek and AI Agents</title>
      <itunes:episode>10</itunes:episode>
      <podcast:episode>10</podcast:episode>
      <itunes:title>Erik Schwartz - Aligning AI to Business Strategy, DeepSeek and AI Agents</itunes:title>
      <itunes:episodeType>full</itunes:episodeType>
      <guid isPermaLink="false">736b52ba-241e-4b43-ab3e-13d61959662e</guid>
      <link>https://share.transistor.fm/s/6f92cc85</link>
      <description>
        <![CDATA[<p>Join Chris as he welcomes Erik Schwartz in an in-depth conversation covering the fast-paced world of AI. </p><p>Eric shares his extensive career journey, providing insights from his early days in information retrieval to his current role as Chief AI Officer. </p><p>The discussion spans various topics, including the challenges of keeping up with rapid technological changes, the impact of AI on business operations, DeekSeek, the Paris AI Summit, the emergence of agentic AI, and the future of AI in personal and enterprise applications. Erik also delves into the similarities between the current AI boom and the dotcom era, and offers valuable advice for companies looking to align AI to business strategy. </p><p>00:00 Introduction and Welcoming Eric Schwartz<br>00:27 The Rapid Pace of AI Development<br>02:28 Eric's Career Journey and Early Tech Experiences<br>05:20 Building Digital Libraries and Information Retrieval<br>06:33 The Evolution of AI and Large Language Models<br>08:40 The Role of AI in Business and Market Trends<br>14:13 Defining AI Agents and Their Capabilities<br>18:06 Adoption of AI in Businesses and Strategic Planning<br>26:04 The Role of a Chief AI Officer<br>36:12 Automating Content Review<br>36:57 Measuring ROI and Success<br>38:15 Improving Operational Efficiency<br>40:18 Product Market Fit for Startups<br>43:26 Impact of AI on SEO and Search<br>46:17 Enterprise Search Solutions<br>48:57 Future of AI and Distributed Technologies<br>55:32 Exciting Developments in AI<br>01:05:34 Closing Thoughts and Community Engagement</p><p>Don't miss this thought-provoking episode as they explore the intricacies of AI adoption, ethics, and the future landscape of search and recommender systems.</p>]]>
      </description>
      <content:encoded>
        <![CDATA[<p>Join Chris as he welcomes Erik Schwartz in an in-depth conversation covering the fast-paced world of AI. </p><p>Eric shares his extensive career journey, providing insights from his early days in information retrieval to his current role as Chief AI Officer. </p><p>The discussion spans various topics, including the challenges of keeping up with rapid technological changes, the impact of AI on business operations, DeekSeek, the Paris AI Summit, the emergence of agentic AI, and the future of AI in personal and enterprise applications. Erik also delves into the similarities between the current AI boom and the dotcom era, and offers valuable advice for companies looking to align AI to business strategy. </p><p>00:00 Introduction and Welcoming Eric Schwartz<br>00:27 The Rapid Pace of AI Development<br>02:28 Eric's Career Journey and Early Tech Experiences<br>05:20 Building Digital Libraries and Information Retrieval<br>06:33 The Evolution of AI and Large Language Models<br>08:40 The Role of AI in Business and Market Trends<br>14:13 Defining AI Agents and Their Capabilities<br>18:06 Adoption of AI in Businesses and Strategic Planning<br>26:04 The Role of a Chief AI Officer<br>36:12 Automating Content Review<br>36:57 Measuring ROI and Success<br>38:15 Improving Operational Efficiency<br>40:18 Product Market Fit for Startups<br>43:26 Impact of AI on SEO and Search<br>46:17 Enterprise Search Solutions<br>48:57 Future of AI and Distributed Technologies<br>55:32 Exciting Developments in AI<br>01:05:34 Closing Thoughts and Community Engagement</p><p>Don't miss this thought-provoking episode as they explore the intricacies of AI adoption, ethics, and the future landscape of search and recommender systems.</p>]]>
      </content:encoded>
      <pubDate>Sun, 09 Mar 2025 10:31:52 -0700</pubDate>
      <author>Chris Coyne</author>
      <enclosure url="https://prfx.byspotify.com/e/media.transistor.fm/6f92cc85/9288cc07.mp3" length="64435634" type="audio/mpeg"/>
      <itunes:author>Chris Coyne</itunes:author>
      <itunes:duration>4027</itunes:duration>
      <itunes:summary>
        <![CDATA[<p>Join Chris as he welcomes Erik Schwartz in an in-depth conversation covering the fast-paced world of AI. </p><p>Eric shares his extensive career journey, providing insights from his early days in information retrieval to his current role as Chief AI Officer. </p><p>The discussion spans various topics, including the challenges of keeping up with rapid technological changes, the impact of AI on business operations, DeekSeek, the Paris AI Summit, the emergence of agentic AI, and the future of AI in personal and enterprise applications. Erik also delves into the similarities between the current AI boom and the dotcom era, and offers valuable advice for companies looking to align AI to business strategy. </p><p>00:00 Introduction and Welcoming Eric Schwartz<br>00:27 The Rapid Pace of AI Development<br>02:28 Eric's Career Journey and Early Tech Experiences<br>05:20 Building Digital Libraries and Information Retrieval<br>06:33 The Evolution of AI and Large Language Models<br>08:40 The Role of AI in Business and Market Trends<br>14:13 Defining AI Agents and Their Capabilities<br>18:06 Adoption of AI in Businesses and Strategic Planning<br>26:04 The Role of a Chief AI Officer<br>36:12 Automating Content Review<br>36:57 Measuring ROI and Success<br>38:15 Improving Operational Efficiency<br>40:18 Product Market Fit for Startups<br>43:26 Impact of AI on SEO and Search<br>46:17 Enterprise Search Solutions<br>48:57 Future of AI and Distributed Technologies<br>55:32 Exciting Developments in AI<br>01:05:34 Closing Thoughts and Community Engagement</p><p>Don't miss this thought-provoking episode as they explore the intricacies of AI adoption, ethics, and the future landscape of search and recommender systems.</p>]]>
      </itunes:summary>
      <itunes:keywords>Agentic AI, AI Agents, DeepSeek, Recommender System, RecSys, Enterprise AI, Adoption</itunes:keywords>
      <itunes:explicit>No</itunes:explicit>
      <podcast:transcript url="https://share.transistor.fm/s/6f92cc85/transcript.vtt" type="text/vtt" rel="captions"/>
      <podcast:transcript url="https://share.transistor.fm/s/6f92cc85/transcript.json" type="application/json"/>
    </item>
    <item>
      <title>Shreesha Jagadeesh - RecSys at Scale, Leadership and Retail Personalisation</title>
      <itunes:episode>11</itunes:episode>
      <podcast:episode>11</podcast:episode>
      <itunes:title>Shreesha Jagadeesh - RecSys at Scale, Leadership and Retail Personalisation</itunes:title>
      <itunes:episodeType>full</itunes:episodeType>
      <guid isPermaLink="false">58aac301-1900-4f4d-b29e-e4321e362e27</guid>
      <link>https://share.transistor.fm/s/175ee446</link>
      <description>
        <![CDATA[<p>The NeuralPod welcomes Shreesha Jagadeesh, Associate Director of Applied Machine Learning at Best Buy, for an insightful conversation. </p><p>Shreesha shares her extensive career journey, from his early days in biomedical diagnostics to her current role at Best Buy. The discussion delves into machine learning techniques in retail, the evolution of recommendation systems, and the technical challenges of personalisation at scale. They also explore his contributions to HR tech at Amazon and his innovative paper on homepage personalisation using XGBoost, soon to be published at RecSys.</p><p>Additionally, Shreesha offers valuable advice on leadership, career growth, and navigating the competitive field of machine learning. Get ready for an episode packed with expert insights and practical tips for aspiring AI professionals.</p><p>00:00 Introduction and Guest Background<br>01:48 Career Journey: From Academia to Industry<br>03:34 Transition to Software and Data Science<br>04:19 Consulting and Managerial Roles<br>07:09 Joining Amazon and HR Tech<br>09:35 Advising a Startup in India<br>11:19 Joining Best Buy and Recommender Systems<br>12:46 Challenges in Retail Personalisation<br>28:28 Implementing XGBoost for Homepage Personalisation<br>40:01 Top-Down and Bottom-Up Approaches in AI<br>40:57 Challenges in Implementing Recommender Systems<br>42:20 Understanding Business Objectives in AB Testing<br>44:36 Experimentation and Value Demonstration<br>46:20 Representation Learning in Machine Learning<br>51:03 Leadership Principles in AI<br>58:08 Hiring and Team Building in AI<br>01:02:43 Future of Recommender Systems and Generative AI<br>01:03:00 Upcoming Book on Recommender Systems<br>01:10:21 AI Tools for Productivity<br>01:16:20 Conclusion and Final Thoughts</p><p>References: </p><p>Multi stage recommender systems blog <br>https://eugeneyan.com/writing/system-design-for-discovery/</p><p>Hidden technical debt in machine learning <br>https://papers.nips.cc/paper_files/paper/2015/hash/86df7dcfd896fcaf2674f757a2463eba-Abstract.html</p><p>HSTU paper<br>https://github.com/meta-recsys/generative-recommenders/blob/main/README.md</p>]]>
      </description>
      <content:encoded>
        <![CDATA[<p>The NeuralPod welcomes Shreesha Jagadeesh, Associate Director of Applied Machine Learning at Best Buy, for an insightful conversation. </p><p>Shreesha shares her extensive career journey, from his early days in biomedical diagnostics to her current role at Best Buy. The discussion delves into machine learning techniques in retail, the evolution of recommendation systems, and the technical challenges of personalisation at scale. They also explore his contributions to HR tech at Amazon and his innovative paper on homepage personalisation using XGBoost, soon to be published at RecSys.</p><p>Additionally, Shreesha offers valuable advice on leadership, career growth, and navigating the competitive field of machine learning. Get ready for an episode packed with expert insights and practical tips for aspiring AI professionals.</p><p>00:00 Introduction and Guest Background<br>01:48 Career Journey: From Academia to Industry<br>03:34 Transition to Software and Data Science<br>04:19 Consulting and Managerial Roles<br>07:09 Joining Amazon and HR Tech<br>09:35 Advising a Startup in India<br>11:19 Joining Best Buy and Recommender Systems<br>12:46 Challenges in Retail Personalisation<br>28:28 Implementing XGBoost for Homepage Personalisation<br>40:01 Top-Down and Bottom-Up Approaches in AI<br>40:57 Challenges in Implementing Recommender Systems<br>42:20 Understanding Business Objectives in AB Testing<br>44:36 Experimentation and Value Demonstration<br>46:20 Representation Learning in Machine Learning<br>51:03 Leadership Principles in AI<br>58:08 Hiring and Team Building in AI<br>01:02:43 Future of Recommender Systems and Generative AI<br>01:03:00 Upcoming Book on Recommender Systems<br>01:10:21 AI Tools for Productivity<br>01:16:20 Conclusion and Final Thoughts</p><p>References: </p><p>Multi stage recommender systems blog <br>https://eugeneyan.com/writing/system-design-for-discovery/</p><p>Hidden technical debt in machine learning <br>https://papers.nips.cc/paper_files/paper/2015/hash/86df7dcfd896fcaf2674f757a2463eba-Abstract.html</p><p>HSTU paper<br>https://github.com/meta-recsys/generative-recommenders/blob/main/README.md</p>]]>
      </content:encoded>
      <pubDate>Wed, 11 Jun 2025 10:02:06 -0700</pubDate>
      <author>Chris Coyne</author>
      <enclosure url="https://prfx.byspotify.com/e/media.transistor.fm/175ee446/45eb0995.mp3" length="74003614" type="audio/mpeg"/>
      <itunes:author>Chris Coyne</itunes:author>
      <itunes:duration>4625</itunes:duration>
      <itunes:summary>
        <![CDATA[<p>The NeuralPod welcomes Shreesha Jagadeesh, Associate Director of Applied Machine Learning at Best Buy, for an insightful conversation. </p><p>Shreesha shares her extensive career journey, from his early days in biomedical diagnostics to her current role at Best Buy. The discussion delves into machine learning techniques in retail, the evolution of recommendation systems, and the technical challenges of personalisation at scale. They also explore his contributions to HR tech at Amazon and his innovative paper on homepage personalisation using XGBoost, soon to be published at RecSys.</p><p>Additionally, Shreesha offers valuable advice on leadership, career growth, and navigating the competitive field of machine learning. Get ready for an episode packed with expert insights and practical tips for aspiring AI professionals.</p><p>00:00 Introduction and Guest Background<br>01:48 Career Journey: From Academia to Industry<br>03:34 Transition to Software and Data Science<br>04:19 Consulting and Managerial Roles<br>07:09 Joining Amazon and HR Tech<br>09:35 Advising a Startup in India<br>11:19 Joining Best Buy and Recommender Systems<br>12:46 Challenges in Retail Personalisation<br>28:28 Implementing XGBoost for Homepage Personalisation<br>40:01 Top-Down and Bottom-Up Approaches in AI<br>40:57 Challenges in Implementing Recommender Systems<br>42:20 Understanding Business Objectives in AB Testing<br>44:36 Experimentation and Value Demonstration<br>46:20 Representation Learning in Machine Learning<br>51:03 Leadership Principles in AI<br>58:08 Hiring and Team Building in AI<br>01:02:43 Future of Recommender Systems and Generative AI<br>01:03:00 Upcoming Book on Recommender Systems<br>01:10:21 AI Tools for Productivity<br>01:16:20 Conclusion and Final Thoughts</p><p>References: </p><p>Multi stage recommender systems blog <br>https://eugeneyan.com/writing/system-design-for-discovery/</p><p>Hidden technical debt in machine learning <br>https://papers.nips.cc/paper_files/paper/2015/hash/86df7dcfd896fcaf2674f757a2463eba-Abstract.html</p><p>HSTU paper<br>https://github.com/meta-recsys/generative-recommenders/blob/main/README.md</p>]]>
      </itunes:summary>
      <itunes:keywords>Machine Learning, AI, Deep Learning, Recommender Systems, Reinforcement Learning</itunes:keywords>
      <itunes:explicit>No</itunes:explicit>
      <podcast:transcript url="https://share.transistor.fm/s/175ee446/transcript.vtt" type="text/vtt" rel="captions"/>
      <podcast:transcript url="https://share.transistor.fm/s/175ee446/transcript.json" type="application/json"/>
    </item>
    <item>
      <title>Schaun Wheeler - Agentic Personalization, Building Aampe and Crafting User Experience</title>
      <itunes:episode>12</itunes:episode>
      <podcast:episode>12</podcast:episode>
      <itunes:title>Schaun Wheeler - Agentic Personalization, Building Aampe and Crafting User Experience</itunes:title>
      <itunes:episodeType>full</itunes:episodeType>
      <guid isPermaLink="false">01eee553-5903-446c-a836-1c87257a7e52</guid>
      <link>https://share.transistor.fm/s/10a1ce5e</link>
      <description>
        <![CDATA[<p>Exploring Agentic Systems and Infrastructure with Schaun Wheeler, Chief Scientist at Aampe. </p><p>In this in-depth discussion with Schaun, we discuss his unique career path, from cognitive anthropology to leading roles in civil service and ad tech. Sean offers insights into the development of agentic systems for optimizing user experience and the challenges within. Here's what we covered 👇</p><p>✓ Schaun's career journey: From cognitive anthropology to data science<br>✓ The role of anthropology in data science and decision-making<br>✓ Common themes and challenges in machine learning projects<br>✓ Developing agentic infrastructure for consumer apps<br>✓ Key technical challenges in startup environments<br>✓ Building agentic systems at Aampe<br>✓ Aampe's Unique Approach to User Engagement<br>✓ The Role of LLMs in Engineering<br>✓ Agent Decision-Making Processes<br>✓ Navigating a fully remote global team culture<br>✓ Future advancements in agentic systems and AI<br>✓ The importance of understanding evidence and decision-making processes in AI<br>✓ Future of AI and Agents</p><p>Tune in for real-world AI insights and cutting-edge developments in agentic systems. </p><p>Thanks, Schaun for sharing!</p>]]>
      </description>
      <content:encoded>
        <![CDATA[<p>Exploring Agentic Systems and Infrastructure with Schaun Wheeler, Chief Scientist at Aampe. </p><p>In this in-depth discussion with Schaun, we discuss his unique career path, from cognitive anthropology to leading roles in civil service and ad tech. Sean offers insights into the development of agentic systems for optimizing user experience and the challenges within. Here's what we covered 👇</p><p>✓ Schaun's career journey: From cognitive anthropology to data science<br>✓ The role of anthropology in data science and decision-making<br>✓ Common themes and challenges in machine learning projects<br>✓ Developing agentic infrastructure for consumer apps<br>✓ Key technical challenges in startup environments<br>✓ Building agentic systems at Aampe<br>✓ Aampe's Unique Approach to User Engagement<br>✓ The Role of LLMs in Engineering<br>✓ Agent Decision-Making Processes<br>✓ Navigating a fully remote global team culture<br>✓ Future advancements in agentic systems and AI<br>✓ The importance of understanding evidence and decision-making processes in AI<br>✓ Future of AI and Agents</p><p>Tune in for real-world AI insights and cutting-edge developments in agentic systems. </p><p>Thanks, Schaun for sharing!</p>]]>
      </content:encoded>
      <pubDate>Wed, 16 Jul 2025 10:59:50 -0700</pubDate>
      <author>Chris Coyne</author>
      <enclosure url="https://prfx.byspotify.com/e/media.transistor.fm/10a1ce5e/5453cebd.mp3" length="56510862" type="audio/mpeg"/>
      <itunes:author>Chris Coyne</itunes:author>
      <itunes:duration>3531</itunes:duration>
      <itunes:summary>
        <![CDATA[<p>Exploring Agentic Systems and Infrastructure with Schaun Wheeler, Chief Scientist at Aampe. </p><p>In this in-depth discussion with Schaun, we discuss his unique career path, from cognitive anthropology to leading roles in civil service and ad tech. Sean offers insights into the development of agentic systems for optimizing user experience and the challenges within. Here's what we covered 👇</p><p>✓ Schaun's career journey: From cognitive anthropology to data science<br>✓ The role of anthropology in data science and decision-making<br>✓ Common themes and challenges in machine learning projects<br>✓ Developing agentic infrastructure for consumer apps<br>✓ Key technical challenges in startup environments<br>✓ Building agentic systems at Aampe<br>✓ Aampe's Unique Approach to User Engagement<br>✓ The Role of LLMs in Engineering<br>✓ Agent Decision-Making Processes<br>✓ Navigating a fully remote global team culture<br>✓ Future advancements in agentic systems and AI<br>✓ The importance of understanding evidence and decision-making processes in AI<br>✓ Future of AI and Agents</p><p>Tune in for real-world AI insights and cutting-edge developments in agentic systems. </p><p>Thanks, Schaun for sharing!</p>]]>
      </itunes:summary>
      <itunes:keywords>Machine Learning, AI, Deep Learning, Recommender Systems, Reinforcement Learning</itunes:keywords>
      <itunes:explicit>No</itunes:explicit>
      <podcast:transcript url="https://share.transistor.fm/s/10a1ce5e/transcript.vtt" type="text/vtt" rel="captions"/>
      <podcast:transcript url="https://share.transistor.fm/s/10a1ce5e/transcript.json" type="application/json"/>
    </item>
    <item>
      <title>Pavan Vemuri - Transforming Automotive with Gen AI and Leadership</title>
      <itunes:episode>13</itunes:episode>
      <podcast:episode>13</podcast:episode>
      <itunes:title>Pavan Vemuri - Transforming Automotive with Gen AI and Leadership</itunes:title>
      <itunes:episodeType>full</itunes:episodeType>
      <guid isPermaLink="false">8049a19d-a7f7-4467-bff3-b600a627e2a4</guid>
      <link>https://youtu.be/VmDHCt2F-94</link>
      <description>
        <![CDATA[<p>Join us, as Chris interviews Pavan Vemuri, the Director of Product Engineering at SDVerse. Pavan shares his remarkable journey from working with Cognizant in India to leading AI and ML operations at major automotive companies like Ford and Stellantis. </p><p>They discuss a range of topics, including the application of generative AI in the automotive sector, overcoming technical and organizational challenges, and building efficient ML infrastructure. Pavan also delves into his effective strategies for onboarding teams and scaling AI use across large organizations. They conclude with thoughts on future trends in AI and the rise of AI agents. </p><p>Here's what we covered 👇</p><p>00:00 Introduction and Career Background<br>05:36 Move to Advanced Engineering at Ford<br>10:22 Implementing Data Quality Inference Engine<br>15:45 Role in Advanced Product Group<br>19:56 Centralized vs. Decentralized ML Platform<br>23:36 Entry into Generative AI<br>27:12 Overcoming Technical Hurdles<br>32:44 Improving Onboarding Process<br>38:59 Collaboration and Adoption<br>46:23 GenAI in Automotive<br>52:14 AI Productivity Tools and Techniques<br>56:21 Future AI Trends and Predictions<br>59:42 Building Trusted Teams and Culture</p><p>Thanks, Pavan, for sharing!</p>]]>
      </description>
      <content:encoded>
        <![CDATA[<p>Join us, as Chris interviews Pavan Vemuri, the Director of Product Engineering at SDVerse. Pavan shares his remarkable journey from working with Cognizant in India to leading AI and ML operations at major automotive companies like Ford and Stellantis. </p><p>They discuss a range of topics, including the application of generative AI in the automotive sector, overcoming technical and organizational challenges, and building efficient ML infrastructure. Pavan also delves into his effective strategies for onboarding teams and scaling AI use across large organizations. They conclude with thoughts on future trends in AI and the rise of AI agents. </p><p>Here's what we covered 👇</p><p>00:00 Introduction and Career Background<br>05:36 Move to Advanced Engineering at Ford<br>10:22 Implementing Data Quality Inference Engine<br>15:45 Role in Advanced Product Group<br>19:56 Centralized vs. Decentralized ML Platform<br>23:36 Entry into Generative AI<br>27:12 Overcoming Technical Hurdles<br>32:44 Improving Onboarding Process<br>38:59 Collaboration and Adoption<br>46:23 GenAI in Automotive<br>52:14 AI Productivity Tools and Techniques<br>56:21 Future AI Trends and Predictions<br>59:42 Building Trusted Teams and Culture</p><p>Thanks, Pavan, for sharing!</p>]]>
      </content:encoded>
      <pubDate>Fri, 29 Aug 2025 04:00:00 -0700</pubDate>
      <author>Chris Coyne</author>
      <enclosure url="https://prfx.byspotify.com/e/media.transistor.fm/485333e9/79e0ba50.mp3" length="80924500" type="audio/mpeg"/>
      <itunes:author>Chris Coyne</itunes:author>
      <itunes:duration>5055</itunes:duration>
      <itunes:summary>
        <![CDATA[<p>Join us, as Chris interviews Pavan Vemuri, the Director of Product Engineering at SDVerse. Pavan shares his remarkable journey from working with Cognizant in India to leading AI and ML operations at major automotive companies like Ford and Stellantis. </p><p>They discuss a range of topics, including the application of generative AI in the automotive sector, overcoming technical and organizational challenges, and building efficient ML infrastructure. Pavan also delves into his effective strategies for onboarding teams and scaling AI use across large organizations. They conclude with thoughts on future trends in AI and the rise of AI agents. </p><p>Here's what we covered 👇</p><p>00:00 Introduction and Career Background<br>05:36 Move to Advanced Engineering at Ford<br>10:22 Implementing Data Quality Inference Engine<br>15:45 Role in Advanced Product Group<br>19:56 Centralized vs. Decentralized ML Platform<br>23:36 Entry into Generative AI<br>27:12 Overcoming Technical Hurdles<br>32:44 Improving Onboarding Process<br>38:59 Collaboration and Adoption<br>46:23 GenAI in Automotive<br>52:14 AI Productivity Tools and Techniques<br>56:21 Future AI Trends and Predictions<br>59:42 Building Trusted Teams and Culture</p><p>Thanks, Pavan, for sharing!</p>]]>
      </itunes:summary>
      <itunes:keywords>Machine Learning, AI, Deep Learning, Recommender Systems, Reinforcement Learning</itunes:keywords>
      <itunes:explicit>No</itunes:explicit>
      <podcast:transcript url="https://share.transistor.fm/s/485333e9/transcript.vtt" type="text/vtt" rel="captions"/>
      <podcast:transcript url="https://share.transistor.fm/s/485333e9/transcript.json" type="application/json"/>
    </item>
    <item>
      <title>Danijela Horak - AI Innovation, Deepfakes, and Responsible AI</title>
      <itunes:episode>14</itunes:episode>
      <podcast:episode>14</podcast:episode>
      <itunes:title>Danijela Horak - AI Innovation, Deepfakes, and Responsible AI</itunes:title>
      <itunes:episodeType>full</itunes:episodeType>
      <guid isPermaLink="false">a265f5d2-6eb5-4f6b-81b6-139cb4788fe1</guid>
      <link>https://share.transistor.fm/s/a135318d</link>
      <description>
        <![CDATA[<p>Join Chris as he sits down with Danijela Horak, former Head of AI of the BBC. Danijela holds a mathematics PhD and she is a machine learning expert. </p><p>We explore her unconventional career path leading to the BBC. Danijela discusses common themes in machine learning, the importance of scientific thinking, and the role of AI in media and journalism.</p><p>Their conversation covers the increasing relevance of LLMs, deepfake detection, and initiatives for responsible AI. Learn about cutting-edge projects at the BBC, the challenges of balancing innovation with trust, and Danijela's leadership philosophy in a highly complex, interdisciplinary environment.</p><p>00:00 Introduction and Welcome<br>00:50 Danijela's Career Journey<br>03:36 Common Themes in Machine Learning<br>04:08 The Importance of Fundamentals in AI<br>08:20 Challenges in Programming and Engineering<br>16:35 AI Innovation at BBC<br>21:26 DeepFakes and Detection<br>30:42 Governance and Responsible AI<br>36:32 Leadership and Culture<br>44:44 Future Trends and Personal Use of AI<br>51:13 Conclusion and Farewell</p><p>Thanks for sharing your insights, Danijela!</p>]]>
      </description>
      <content:encoded>
        <![CDATA[<p>Join Chris as he sits down with Danijela Horak, former Head of AI of the BBC. Danijela holds a mathematics PhD and she is a machine learning expert. </p><p>We explore her unconventional career path leading to the BBC. Danijela discusses common themes in machine learning, the importance of scientific thinking, and the role of AI in media and journalism.</p><p>Their conversation covers the increasing relevance of LLMs, deepfake detection, and initiatives for responsible AI. Learn about cutting-edge projects at the BBC, the challenges of balancing innovation with trust, and Danijela's leadership philosophy in a highly complex, interdisciplinary environment.</p><p>00:00 Introduction and Welcome<br>00:50 Danijela's Career Journey<br>03:36 Common Themes in Machine Learning<br>04:08 The Importance of Fundamentals in AI<br>08:20 Challenges in Programming and Engineering<br>16:35 AI Innovation at BBC<br>21:26 DeepFakes and Detection<br>30:42 Governance and Responsible AI<br>36:32 Leadership and Culture<br>44:44 Future Trends and Personal Use of AI<br>51:13 Conclusion and Farewell</p><p>Thanks for sharing your insights, Danijela!</p>]]>
      </content:encoded>
      <pubDate>Sun, 21 Sep 2025 18:00:00 -0700</pubDate>
      <author>Chris Coyne</author>
      <enclosure url="https://prfx.byspotify.com/e/media.transistor.fm/a135318d/209cbeb0.mp3" length="49476344" type="audio/mpeg"/>
      <itunes:author>Chris Coyne</itunes:author>
      <itunes:duration>3090</itunes:duration>
      <itunes:summary>
        <![CDATA[<p>Join Chris as he sits down with Danijela Horak, former Head of AI of the BBC. Danijela holds a mathematics PhD and she is a machine learning expert. </p><p>We explore her unconventional career path leading to the BBC. Danijela discusses common themes in machine learning, the importance of scientific thinking, and the role of AI in media and journalism.</p><p>Their conversation covers the increasing relevance of LLMs, deepfake detection, and initiatives for responsible AI. Learn about cutting-edge projects at the BBC, the challenges of balancing innovation with trust, and Danijela's leadership philosophy in a highly complex, interdisciplinary environment.</p><p>00:00 Introduction and Welcome<br>00:50 Danijela's Career Journey<br>03:36 Common Themes in Machine Learning<br>04:08 The Importance of Fundamentals in AI<br>08:20 Challenges in Programming and Engineering<br>16:35 AI Innovation at BBC<br>21:26 DeepFakes and Detection<br>30:42 Governance and Responsible AI<br>36:32 Leadership and Culture<br>44:44 Future Trends and Personal Use of AI<br>51:13 Conclusion and Farewell</p><p>Thanks for sharing your insights, Danijela!</p>]]>
      </itunes:summary>
      <itunes:keywords>Machine Learning, AI, Deep Learning, Recommender Systems, Reinforcement Learning</itunes:keywords>
      <itunes:explicit>No</itunes:explicit>
      <podcast:transcript url="https://share.transistor.fm/s/a135318d/transcript.vtt" type="text/vtt" rel="captions"/>
      <podcast:transcript url="https://share.transistor.fm/s/a135318d/transcript.json" type="application/json"/>
    </item>
    <item>
      <title>Alexey Strygin - Live Longer &amp; Aging, Pt.2 </title>
      <itunes:episode>15</itunes:episode>
      <podcast:episode>15</podcast:episode>
      <itunes:title>Alexey Strygin - Live Longer &amp; Aging, Pt.2 </itunes:title>
      <itunes:episodeType>full</itunes:episodeType>
      <guid isPermaLink="false">eb4206d8-94f6-4770-842e-66d4bde40b2e</guid>
      <link>https://share.transistor.fm/s/561ddaa9</link>
      <description>
        <![CDATA[<p>Exploring the Future of Longevity: Breakthroughs, Ethical Dilemmas, and Viva City</p><p>In this episode of the NeuralPod, Chris and Alexey discuss recent developments in the field of longevity, with an emphasis on breakneck innovations and ethical concerns. Our guest, Alexey, shares insights on his co-founded project, Viva City—a new initiative aiming to accelerate progress in longevity through special economic zones. They discuss the concept of 'sack of organs', the potential and controversy around gene-edited and animal-grown organs, and recent advances in longevity research. The podcast also sheds light on the importance of mega-projects for longevity, akin to the International Space Station or Apollo programs, and the need for substantial investments to make significant breakthroughs. Learn about the AI agents vs. aging hackathon aimed at attracting more talent to the longevity space and explore future possibilities of significantly extending human lifespan through technology.</p><p>00:00 Welcome Back to the Neural Pod<br>00:28 Longevity in the Mainstream<br>01:14 Recent Breakthroughs in Longevity<br>03:14 The Concept of 'Sack of Organs'<br>07:04 Ethical Dilemmas in Organ Replacement<br>09:50 AI and Organ Transplantation<br>14:31 Introducing Viva City: The Longevity City<br>16:16 The Vision Behind Viva City<br>24:59 Challenges and Negotiations for Viva City<br>29:56 Building Viva City: The Role of Universities and Smart People<br>30:23 Governance and Initial Experiments in Viva City<br>32:06 Challenges and Legal Considerations for Longevity Therapies<br>38:47 Global Perspectives on Longevity Research<br>47:27 AI and Longevity: The Hackathon Initiative<br>54:40 The Future of Longevity and AI<br>58:11 Conclusion and Final Thoughts</p>]]>
      </description>
      <content:encoded>
        <![CDATA[<p>Exploring the Future of Longevity: Breakthroughs, Ethical Dilemmas, and Viva City</p><p>In this episode of the NeuralPod, Chris and Alexey discuss recent developments in the field of longevity, with an emphasis on breakneck innovations and ethical concerns. Our guest, Alexey, shares insights on his co-founded project, Viva City—a new initiative aiming to accelerate progress in longevity through special economic zones. They discuss the concept of 'sack of organs', the potential and controversy around gene-edited and animal-grown organs, and recent advances in longevity research. The podcast also sheds light on the importance of mega-projects for longevity, akin to the International Space Station or Apollo programs, and the need for substantial investments to make significant breakthroughs. Learn about the AI agents vs. aging hackathon aimed at attracting more talent to the longevity space and explore future possibilities of significantly extending human lifespan through technology.</p><p>00:00 Welcome Back to the Neural Pod<br>00:28 Longevity in the Mainstream<br>01:14 Recent Breakthroughs in Longevity<br>03:14 The Concept of 'Sack of Organs'<br>07:04 Ethical Dilemmas in Organ Replacement<br>09:50 AI and Organ Transplantation<br>14:31 Introducing Viva City: The Longevity City<br>16:16 The Vision Behind Viva City<br>24:59 Challenges and Negotiations for Viva City<br>29:56 Building Viva City: The Role of Universities and Smart People<br>30:23 Governance and Initial Experiments in Viva City<br>32:06 Challenges and Legal Considerations for Longevity Therapies<br>38:47 Global Perspectives on Longevity Research<br>47:27 AI and Longevity: The Hackathon Initiative<br>54:40 The Future of Longevity and AI<br>58:11 Conclusion and Final Thoughts</p>]]>
      </content:encoded>
      <pubDate>Fri, 26 Sep 2025 01:14:10 -0700</pubDate>
      <author>Chris Coyne</author>
      <enclosure url="https://prfx.byspotify.com/e/media.transistor.fm/561ddaa9/357667bf.mp3" length="56631370" type="audio/mpeg"/>
      <itunes:author>Chris Coyne</itunes:author>
      <itunes:duration>3537</itunes:duration>
      <itunes:summary>
        <![CDATA[<p>Exploring the Future of Longevity: Breakthroughs, Ethical Dilemmas, and Viva City</p><p>In this episode of the NeuralPod, Chris and Alexey discuss recent developments in the field of longevity, with an emphasis on breakneck innovations and ethical concerns. Our guest, Alexey, shares insights on his co-founded project, Viva City—a new initiative aiming to accelerate progress in longevity through special economic zones. They discuss the concept of 'sack of organs', the potential and controversy around gene-edited and animal-grown organs, and recent advances in longevity research. The podcast also sheds light on the importance of mega-projects for longevity, akin to the International Space Station or Apollo programs, and the need for substantial investments to make significant breakthroughs. Learn about the AI agents vs. aging hackathon aimed at attracting more talent to the longevity space and explore future possibilities of significantly extending human lifespan through technology.</p><p>00:00 Welcome Back to the Neural Pod<br>00:28 Longevity in the Mainstream<br>01:14 Recent Breakthroughs in Longevity<br>03:14 The Concept of 'Sack of Organs'<br>07:04 Ethical Dilemmas in Organ Replacement<br>09:50 AI and Organ Transplantation<br>14:31 Introducing Viva City: The Longevity City<br>16:16 The Vision Behind Viva City<br>24:59 Challenges and Negotiations for Viva City<br>29:56 Building Viva City: The Role of Universities and Smart People<br>30:23 Governance and Initial Experiments in Viva City<br>32:06 Challenges and Legal Considerations for Longevity Therapies<br>38:47 Global Perspectives on Longevity Research<br>47:27 AI and Longevity: The Hackathon Initiative<br>54:40 The Future of Longevity and AI<br>58:11 Conclusion and Final Thoughts</p>]]>
      </itunes:summary>
      <itunes:keywords>Machine Learning, AI, Deep Learning, Recommender Systems, Reinforcement Learning</itunes:keywords>
      <itunes:explicit>No</itunes:explicit>
      <podcast:transcript url="https://share.transistor.fm/s/561ddaa9/transcript.vtt" type="text/vtt" rel="captions"/>
      <podcast:transcript url="https://share.transistor.fm/s/561ddaa9/transcript.json" type="application/json"/>
    </item>
    <item>
      <title>Michal Klos - Transforming Legal Monitoring with AI</title>
      <itunes:episode>16</itunes:episode>
      <podcast:episode>16</podcast:episode>
      <itunes:title>Michal Klos - Transforming Legal Monitoring with AI</itunes:title>
      <itunes:episodeType>full</itunes:episodeType>
      <guid isPermaLink="false">1d90699d-7a72-417d-afd3-60eea7e5edd2</guid>
      <link>https://share.transistor.fm/s/83cb3855</link>
      <description>
        <![CDATA[<p>We welcome Michal Klos, former Tech Lead from ByteDance and ShareChat focusing on machine learning and recommendations. Michal recently joined Lex AI as Co-Founder, a tech start-up in Germany solving challenges in Legal Monitoring with AI, recently partnering with Deloitte.</p><p> The conversation delves into the architecture and innovative solutions offered by Lex AI. Mical shares his views on integrating AI to streamline workflows while maintaining accuracy and efficiency. </p><p>The episode also explores the importance of feedback in finding product-market fit, building 0-1 and navigates through the challenges and future trends in the legal tech space.</p><p>00:43 Michal's Career Journey<br>03:49 Working at ByteDance<br>06:48 Challenges at ShareChat<br>09:46 Founding Lex AI<br>10:20 Machine Learning Fundamentals<br>15:39 The Value of an MBA<br>20:01 Transitioning to Startups<br>24:01 Building Lex AI<br>32:19 Technical Insights of Lex AI<br>42:24 Overview of Legal Problems<br>43:30 Product Market Fit Challenges<br>45:53 Feedback and Adaptation<br>52:03 AI in Legal Tech<br>55:00 Startup Culture and Engineering<br>01:00:44 Future of AI in Legal Tech<br>01:04:45 Productivity Tools for Founders<br>01:15:37 AI Trends and Predictions<br>01:22:50 Conclusion and Final Thoughts</p><p>Learn more about Lex AI's partnership with Deloitte and how they are creating positive change here: https://www.lexai.co/post/deloitte-partnership-with-ai-startup-lex-ai-underscores-role-of-ai-in-legal-and-compliance</p>]]>
      </description>
      <content:encoded>
        <![CDATA[<p>We welcome Michal Klos, former Tech Lead from ByteDance and ShareChat focusing on machine learning and recommendations. Michal recently joined Lex AI as Co-Founder, a tech start-up in Germany solving challenges in Legal Monitoring with AI, recently partnering with Deloitte.</p><p> The conversation delves into the architecture and innovative solutions offered by Lex AI. Mical shares his views on integrating AI to streamline workflows while maintaining accuracy and efficiency. </p><p>The episode also explores the importance of feedback in finding product-market fit, building 0-1 and navigates through the challenges and future trends in the legal tech space.</p><p>00:43 Michal's Career Journey<br>03:49 Working at ByteDance<br>06:48 Challenges at ShareChat<br>09:46 Founding Lex AI<br>10:20 Machine Learning Fundamentals<br>15:39 The Value of an MBA<br>20:01 Transitioning to Startups<br>24:01 Building Lex AI<br>32:19 Technical Insights of Lex AI<br>42:24 Overview of Legal Problems<br>43:30 Product Market Fit Challenges<br>45:53 Feedback and Adaptation<br>52:03 AI in Legal Tech<br>55:00 Startup Culture and Engineering<br>01:00:44 Future of AI in Legal Tech<br>01:04:45 Productivity Tools for Founders<br>01:15:37 AI Trends and Predictions<br>01:22:50 Conclusion and Final Thoughts</p><p>Learn more about Lex AI's partnership with Deloitte and how they are creating positive change here: https://www.lexai.co/post/deloitte-partnership-with-ai-startup-lex-ai-underscores-role-of-ai-in-legal-and-compliance</p>]]>
      </content:encoded>
      <pubDate>Mon, 20 Oct 2025 13:32:22 -0700</pubDate>
      <author>Chris Coyne</author>
      <enclosure url="https://prfx.byspotify.com/e/media.transistor.fm/83cb3855/51b0d9a1.mp3" length="80080569" type="audio/mpeg"/>
      <itunes:author>Chris Coyne</itunes:author>
      <itunes:duration>5003</itunes:duration>
      <itunes:summary>
        <![CDATA[<p>We welcome Michal Klos, former Tech Lead from ByteDance and ShareChat focusing on machine learning and recommendations. Michal recently joined Lex AI as Co-Founder, a tech start-up in Germany solving challenges in Legal Monitoring with AI, recently partnering with Deloitte.</p><p> The conversation delves into the architecture and innovative solutions offered by Lex AI. Mical shares his views on integrating AI to streamline workflows while maintaining accuracy and efficiency. </p><p>The episode also explores the importance of feedback in finding product-market fit, building 0-1 and navigates through the challenges and future trends in the legal tech space.</p><p>00:43 Michal's Career Journey<br>03:49 Working at ByteDance<br>06:48 Challenges at ShareChat<br>09:46 Founding Lex AI<br>10:20 Machine Learning Fundamentals<br>15:39 The Value of an MBA<br>20:01 Transitioning to Startups<br>24:01 Building Lex AI<br>32:19 Technical Insights of Lex AI<br>42:24 Overview of Legal Problems<br>43:30 Product Market Fit Challenges<br>45:53 Feedback and Adaptation<br>52:03 AI in Legal Tech<br>55:00 Startup Culture and Engineering<br>01:00:44 Future of AI in Legal Tech<br>01:04:45 Productivity Tools for Founders<br>01:15:37 AI Trends and Predictions<br>01:22:50 Conclusion and Final Thoughts</p><p>Learn more about Lex AI's partnership with Deloitte and how they are creating positive change here: https://www.lexai.co/post/deloitte-partnership-with-ai-startup-lex-ai-underscores-role-of-ai-in-legal-and-compliance</p>]]>
      </itunes:summary>
      <itunes:keywords>Machine Learning, AI, Deep Learning, Recommender Systems, Reinforcement Learning</itunes:keywords>
      <itunes:explicit>No</itunes:explicit>
      <podcast:transcript url="https://share.transistor.fm/s/83cb3855/transcript.vtt" type="text/vtt" rel="captions"/>
      <podcast:transcript url="https://share.transistor.fm/s/83cb3855/transcript.json" type="application/json"/>
    </item>
    <item>
      <title>Alberto Lumbreras - Defining the future of e-commerce with Agentic AI</title>
      <itunes:episode>17</itunes:episode>
      <podcast:episode>17</podcast:episode>
      <itunes:title>Alberto Lumbreras - Defining the future of e-commerce with Agentic AI</itunes:title>
      <itunes:episodeType>full</itunes:episodeType>
      <guid isPermaLink="false">fb7dbab2-6726-4916-b317-7ac181efd78f</guid>
      <link>https://share.transistor.fm/s/2e1c557a</link>
      <description>
        <![CDATA[<p>Future of AI in E-commerce and Ad Tech </p><p>Join us for a discussion with Staff AI Researcher and Project Leader from Criteo, Alberto Lumbreras. We chatted about how Agentic AI will transform the AdTech and e-commerce experience. </p><p>Alberto shares his unique career journey from telecommunications engineering to AI and machine learning, exploring his involvement in social network analysis and PhD studies. The conversation goes into the evolving landscape of AI in e-commerce, with a specific focus on shopping assistants and agent interfaces. Alberto also discusses the challenges in developing AI systems for commerce, the impact on the ad tech industry, and future predictions. Learn about his views on the importance of unique data, the advent of smaller, more efficient AI models, and how AI will become more autonomous and integrated into daily life.</p><p>00:00 Introduction and Welcome<br>01:02 Alberto's Career Journey<br>03:06 AI and Social Movements<br>03:53 Joining Criteo and Current Work<br>04:52 The Future of Shopping with AI Agents<br>08:25 Impact on Ad Tech Industry<br>10:48 Challenges and Opportunities in E-commerce<br>21:06 Data as a Competitive Moat<br>26:21 Challenges in Retail Catalogs for AI<br>27:15 Dynamic Data in Travel Industry<br>28:19 Importance of Comprehensive Data for AI<br>28:41 User Willingness to Share Data<br>29:07 Research, Engineering, and Talent Crossover<br>30:00 Essential Skills for ML Researchers<br>31:45 Impact of AI Tools on Engineering<br>32:46 Advice for Working with AI<br>38:19 Future Trends in AI Development<br>44:49 Research Directions and Influential Papers<br>48:18 Books That Shape AI Thinking<br>51:41 Conclusion and Farewell</p><p>Link to the first solo publication mentioned in the podcast: https://arxiv.org/pdf/2510.04871</p>]]>
      </description>
      <content:encoded>
        <![CDATA[<p>Future of AI in E-commerce and Ad Tech </p><p>Join us for a discussion with Staff AI Researcher and Project Leader from Criteo, Alberto Lumbreras. We chatted about how Agentic AI will transform the AdTech and e-commerce experience. </p><p>Alberto shares his unique career journey from telecommunications engineering to AI and machine learning, exploring his involvement in social network analysis and PhD studies. The conversation goes into the evolving landscape of AI in e-commerce, with a specific focus on shopping assistants and agent interfaces. Alberto also discusses the challenges in developing AI systems for commerce, the impact on the ad tech industry, and future predictions. Learn about his views on the importance of unique data, the advent of smaller, more efficient AI models, and how AI will become more autonomous and integrated into daily life.</p><p>00:00 Introduction and Welcome<br>01:02 Alberto's Career Journey<br>03:06 AI and Social Movements<br>03:53 Joining Criteo and Current Work<br>04:52 The Future of Shopping with AI Agents<br>08:25 Impact on Ad Tech Industry<br>10:48 Challenges and Opportunities in E-commerce<br>21:06 Data as a Competitive Moat<br>26:21 Challenges in Retail Catalogs for AI<br>27:15 Dynamic Data in Travel Industry<br>28:19 Importance of Comprehensive Data for AI<br>28:41 User Willingness to Share Data<br>29:07 Research, Engineering, and Talent Crossover<br>30:00 Essential Skills for ML Researchers<br>31:45 Impact of AI Tools on Engineering<br>32:46 Advice for Working with AI<br>38:19 Future Trends in AI Development<br>44:49 Research Directions and Influential Papers<br>48:18 Books That Shape AI Thinking<br>51:41 Conclusion and Farewell</p><p>Link to the first solo publication mentioned in the podcast: https://arxiv.org/pdf/2510.04871</p>]]>
      </content:encoded>
      <pubDate>Mon, 03 Nov 2025 19:00:00 -0800</pubDate>
      <author>Chris Coyne</author>
      <enclosure url="https://prfx.byspotify.com/e/media.transistor.fm/2e1c557a/217dd715.mp3" length="49323726" type="audio/mpeg"/>
      <itunes:author>Chris Coyne</itunes:author>
      <itunes:duration>3080</itunes:duration>
      <itunes:summary>
        <![CDATA[<p>Future of AI in E-commerce and Ad Tech </p><p>Join us for a discussion with Staff AI Researcher and Project Leader from Criteo, Alberto Lumbreras. We chatted about how Agentic AI will transform the AdTech and e-commerce experience. </p><p>Alberto shares his unique career journey from telecommunications engineering to AI and machine learning, exploring his involvement in social network analysis and PhD studies. The conversation goes into the evolving landscape of AI in e-commerce, with a specific focus on shopping assistants and agent interfaces. Alberto also discusses the challenges in developing AI systems for commerce, the impact on the ad tech industry, and future predictions. Learn about his views on the importance of unique data, the advent of smaller, more efficient AI models, and how AI will become more autonomous and integrated into daily life.</p><p>00:00 Introduction and Welcome<br>01:02 Alberto's Career Journey<br>03:06 AI and Social Movements<br>03:53 Joining Criteo and Current Work<br>04:52 The Future of Shopping with AI Agents<br>08:25 Impact on Ad Tech Industry<br>10:48 Challenges and Opportunities in E-commerce<br>21:06 Data as a Competitive Moat<br>26:21 Challenges in Retail Catalogs for AI<br>27:15 Dynamic Data in Travel Industry<br>28:19 Importance of Comprehensive Data for AI<br>28:41 User Willingness to Share Data<br>29:07 Research, Engineering, and Talent Crossover<br>30:00 Essential Skills for ML Researchers<br>31:45 Impact of AI Tools on Engineering<br>32:46 Advice for Working with AI<br>38:19 Future Trends in AI Development<br>44:49 Research Directions and Influential Papers<br>48:18 Books That Shape AI Thinking<br>51:41 Conclusion and Farewell</p><p>Link to the first solo publication mentioned in the podcast: https://arxiv.org/pdf/2510.04871</p>]]>
      </itunes:summary>
      <itunes:keywords>Machine Learning, AI, Deep Learning, Recommender Systems, Reinforcement Learning</itunes:keywords>
      <itunes:explicit>No</itunes:explicit>
      <podcast:transcript url="https://share.transistor.fm/s/2e1c557a/transcript.vtt" type="text/vtt" rel="captions"/>
      <podcast:transcript url="https://share.transistor.fm/s/2e1c557a/transcript.json" type="application/json"/>
    </item>
    <item>
      <title>Keith Dear - Everything Is Prediction, AGI &amp; Cassi AI</title>
      <itunes:episode>18</itunes:episode>
      <podcast:episode>18</podcast:episode>
      <itunes:title>Keith Dear - Everything Is Prediction, AGI &amp; Cassi AI</itunes:title>
      <itunes:episodeType>full</itunes:episodeType>
      <guid isPermaLink="false">22c807d3-f6c5-465f-892f-6c7d51d58396</guid>
      <link>https://share.transistor.fm/s/d25a4c1c</link>
      <description>
        <![CDATA[<p>We're joined by Keith Dear, CEO and co-founder of Cassi, an AI super strategy engine. Keith is a former intelligence officer, an advisor at Number 10 and a former leader at Fujitsu Research. </p><p>We discussed his vision for Cassie, the concept of 'everything is prediction,' and how AI will shape organisational strategies and decision-making processes. We also explore the potential impact of AGI on job markets, the national economy, and global politics, touching on Keith's recent visit to China and his work with the UN on AI security and ethics. </p><p>00:00 Introduction and Initial Thoughts<br>00:22 Welcome to the Neuro Pod<br>00:41 Keith's Career Journey<br>01:16 Cassie: The Super Strategy Engine<br>02:17 The Importance of Clear Objectives<br>03:26 AI and Crowdsourcing in Decision Making<br>04:58 Keith's Background and Education<br>06:57 The Genesis of Cassie<br>10:42 Concerns About AI and the Future<br>14:29 Visiting China: Insights and Observations<br>18:39 Leadership Principles and Military Experience<br>24:36 Transitioning from Corporate to Startup<br>26:44 Predictions on AGI and Superintelligence<br>34:17 Choosing AI Over Human Advice<br>34:45 AI's Limitations and Human Judgment<br>35:23 Trusting AI vs. Human Judgment<br>36:33 Self-Driving Cars and Ethical Dilemmas<br>37:57 AI's Impact on Jobs and Economy<br>40:34 International Security and AI<br>48:03 Cassie: Everything is Prediction<br>50:50 Cassie in Action: Real-World Applications<br>56:46 The Future of AI and Organizational Design<br>01:03:00 Closing Thoughts and Future Aspirations</p><p>Keith's blog on why everything is prediction: https://cassiai.substack.com/p/everything-is-prediction<br>Website: https://cassi-ai.com/</p>]]>
      </description>
      <content:encoded>
        <![CDATA[<p>We're joined by Keith Dear, CEO and co-founder of Cassi, an AI super strategy engine. Keith is a former intelligence officer, an advisor at Number 10 and a former leader at Fujitsu Research. </p><p>We discussed his vision for Cassie, the concept of 'everything is prediction,' and how AI will shape organisational strategies and decision-making processes. We also explore the potential impact of AGI on job markets, the national economy, and global politics, touching on Keith's recent visit to China and his work with the UN on AI security and ethics. </p><p>00:00 Introduction and Initial Thoughts<br>00:22 Welcome to the Neuro Pod<br>00:41 Keith's Career Journey<br>01:16 Cassie: The Super Strategy Engine<br>02:17 The Importance of Clear Objectives<br>03:26 AI and Crowdsourcing in Decision Making<br>04:58 Keith's Background and Education<br>06:57 The Genesis of Cassie<br>10:42 Concerns About AI and the Future<br>14:29 Visiting China: Insights and Observations<br>18:39 Leadership Principles and Military Experience<br>24:36 Transitioning from Corporate to Startup<br>26:44 Predictions on AGI and Superintelligence<br>34:17 Choosing AI Over Human Advice<br>34:45 AI's Limitations and Human Judgment<br>35:23 Trusting AI vs. Human Judgment<br>36:33 Self-Driving Cars and Ethical Dilemmas<br>37:57 AI's Impact on Jobs and Economy<br>40:34 International Security and AI<br>48:03 Cassie: Everything is Prediction<br>50:50 Cassie in Action: Real-World Applications<br>56:46 The Future of AI and Organizational Design<br>01:03:00 Closing Thoughts and Future Aspirations</p><p>Keith's blog on why everything is prediction: https://cassiai.substack.com/p/everything-is-prediction<br>Website: https://cassi-ai.com/</p>]]>
      </content:encoded>
      <pubDate>Sun, 16 Nov 2025 13:47:33 -0800</pubDate>
      <author>Chris Coyne</author>
      <enclosure url="https://prfx.byspotify.com/e/media.transistor.fm/d25a4c1c/a8af7b6d.mp3" length="64501188" type="audio/mpeg"/>
      <itunes:author>Chris Coyne</itunes:author>
      <itunes:duration>4029</itunes:duration>
      <itunes:summary>
        <![CDATA[<p>We're joined by Keith Dear, CEO and co-founder of Cassi, an AI super strategy engine. Keith is a former intelligence officer, an advisor at Number 10 and a former leader at Fujitsu Research. </p><p>We discussed his vision for Cassie, the concept of 'everything is prediction,' and how AI will shape organisational strategies and decision-making processes. We also explore the potential impact of AGI on job markets, the national economy, and global politics, touching on Keith's recent visit to China and his work with the UN on AI security and ethics. </p><p>00:00 Introduction and Initial Thoughts<br>00:22 Welcome to the Neuro Pod<br>00:41 Keith's Career Journey<br>01:16 Cassie: The Super Strategy Engine<br>02:17 The Importance of Clear Objectives<br>03:26 AI and Crowdsourcing in Decision Making<br>04:58 Keith's Background and Education<br>06:57 The Genesis of Cassie<br>10:42 Concerns About AI and the Future<br>14:29 Visiting China: Insights and Observations<br>18:39 Leadership Principles and Military Experience<br>24:36 Transitioning from Corporate to Startup<br>26:44 Predictions on AGI and Superintelligence<br>34:17 Choosing AI Over Human Advice<br>34:45 AI's Limitations and Human Judgment<br>35:23 Trusting AI vs. Human Judgment<br>36:33 Self-Driving Cars and Ethical Dilemmas<br>37:57 AI's Impact on Jobs and Economy<br>40:34 International Security and AI<br>48:03 Cassie: Everything is Prediction<br>50:50 Cassie in Action: Real-World Applications<br>56:46 The Future of AI and Organizational Design<br>01:03:00 Closing Thoughts and Future Aspirations</p><p>Keith's blog on why everything is prediction: https://cassiai.substack.com/p/everything-is-prediction<br>Website: https://cassi-ai.com/</p>]]>
      </itunes:summary>
      <itunes:keywords>Machine Learning, AI, Deep Learning, Recommender Systems, Reinforcement Learning</itunes:keywords>
      <itunes:explicit>No</itunes:explicit>
      <podcast:transcript url="https://share.transistor.fm/s/d25a4c1c/transcript.vtt" type="text/vtt" rel="captions"/>
      <podcast:transcript url="https://share.transistor.fm/s/d25a4c1c/transcript.json" type="application/json"/>
    </item>
    <item>
      <title>Artem Elmuratov - How AI Is Shaping Genetics</title>
      <itunes:episode>19</itunes:episode>
      <podcast:episode>19</podcast:episode>
      <itunes:title>Artem Elmuratov - How AI Is Shaping Genetics</itunes:title>
      <itunes:episodeType>full</itunes:episodeType>
      <guid isPermaLink="false">4bbbdfca-c61c-4602-932f-854ee34e4ccb</guid>
      <link>https://share.transistor.fm/s/ea41bc3d</link>
      <description>
        <![CDATA[<p>We're joined by Artem Elmuratov, Head of Life Sciences at Nebius and former Founder. </p><p>In this episode, we discuss with Artem genetics and its future with AI. Specifically discussing the impact of CRISPR-GPT on biotechnology. We explore its potential applications in genetic engineering, disease prevention, and personalised medicine. The discussion highlights the scientific breakthroughs enabling precise genetic modifications and considers the societal implications of such advancements.</p><p>Join us as we explore: </p><p>00:00 Introduction: AI and Scientists<br>00:20 Welcome to Rhe NeuralPod<br>00:37 Artem's Unique Journey in Biotech<br>01:04 The Intersection of Genetics and AI<br>03:55 Career Overview and Early Ventures<br>04:54 Confidential Computing and Current Role<br>05:40 Lessons Learned and Advice for Researchers<br>08:16 Current State of Genetics and AI<br>10:05 Challenges in the Industry<br>12:03 AI's Role in Drug Discovery<br>18:02 CRISPR and Gene Editing<br>27:24 Future of Gene Editing and Ethics<br>31:56 Fun Predictions and Sci-Fi Inspirations<br>41:05 Closing Thoughts and Contact Information</p><p>CRISPR GPT: https://nebius.com/customer-stories/crispr-gpt-stanford</p>]]>
      </description>
      <content:encoded>
        <![CDATA[<p>We're joined by Artem Elmuratov, Head of Life Sciences at Nebius and former Founder. </p><p>In this episode, we discuss with Artem genetics and its future with AI. Specifically discussing the impact of CRISPR-GPT on biotechnology. We explore its potential applications in genetic engineering, disease prevention, and personalised medicine. The discussion highlights the scientific breakthroughs enabling precise genetic modifications and considers the societal implications of such advancements.</p><p>Join us as we explore: </p><p>00:00 Introduction: AI and Scientists<br>00:20 Welcome to Rhe NeuralPod<br>00:37 Artem's Unique Journey in Biotech<br>01:04 The Intersection of Genetics and AI<br>03:55 Career Overview and Early Ventures<br>04:54 Confidential Computing and Current Role<br>05:40 Lessons Learned and Advice for Researchers<br>08:16 Current State of Genetics and AI<br>10:05 Challenges in the Industry<br>12:03 AI's Role in Drug Discovery<br>18:02 CRISPR and Gene Editing<br>27:24 Future of Gene Editing and Ethics<br>31:56 Fun Predictions and Sci-Fi Inspirations<br>41:05 Closing Thoughts and Contact Information</p><p>CRISPR GPT: https://nebius.com/customer-stories/crispr-gpt-stanford</p>]]>
      </content:encoded>
      <pubDate>Tue, 25 Nov 2025 04:18:31 -0800</pubDate>
      <author>Chris Coyne</author>
      <enclosure url="https://prfx.byspotify.com/e/media.transistor.fm/ea41bc3d/01051f3b.mp3" length="40861430" type="audio/mpeg"/>
      <itunes:author>Chris Coyne</itunes:author>
      <itunes:duration>2551</itunes:duration>
      <itunes:summary>
        <![CDATA[<p>We're joined by Artem Elmuratov, Head of Life Sciences at Nebius and former Founder. </p><p>In this episode, we discuss with Artem genetics and its future with AI. Specifically discussing the impact of CRISPR-GPT on biotechnology. We explore its potential applications in genetic engineering, disease prevention, and personalised medicine. The discussion highlights the scientific breakthroughs enabling precise genetic modifications and considers the societal implications of such advancements.</p><p>Join us as we explore: </p><p>00:00 Introduction: AI and Scientists<br>00:20 Welcome to Rhe NeuralPod<br>00:37 Artem's Unique Journey in Biotech<br>01:04 The Intersection of Genetics and AI<br>03:55 Career Overview and Early Ventures<br>04:54 Confidential Computing and Current Role<br>05:40 Lessons Learned and Advice for Researchers<br>08:16 Current State of Genetics and AI<br>10:05 Challenges in the Industry<br>12:03 AI's Role in Drug Discovery<br>18:02 CRISPR and Gene Editing<br>27:24 Future of Gene Editing and Ethics<br>31:56 Fun Predictions and Sci-Fi Inspirations<br>41:05 Closing Thoughts and Contact Information</p><p>CRISPR GPT: https://nebius.com/customer-stories/crispr-gpt-stanford</p>]]>
      </itunes:summary>
      <itunes:keywords>Machine Learning, AI, Deep Learning, Recommender Systems, Reinforcement Learning</itunes:keywords>
      <itunes:explicit>No</itunes:explicit>
      <podcast:transcript url="https://share.transistor.fm/s/ea41bc3d/transcript.vtt" type="text/vtt" rel="captions"/>
      <podcast:transcript url="https://share.transistor.fm/s/ea41bc3d/transcript.json" type="application/json"/>
    </item>
    <item>
      <title>Kate Ivanova - AI Cloning Your Personality with Pantio</title>
      <itunes:episode>20</itunes:episode>
      <podcast:episode>20</podcast:episode>
      <itunes:title>Kate Ivanova - AI Cloning Your Personality with Pantio</itunes:title>
      <itunes:episodeType>full</itunes:episodeType>
      <guid isPermaLink="false">811d1fed-be83-4405-9907-650181eb21ec</guid>
      <link>https://share.transistor.fm/s/221490da</link>
      <description>
        <![CDATA[<p>Would you clone your likeness and personality with AI?</p><p>Chris is joined by Katherine Ivanova, co-founder of Pantio, a company dedicated to creating digital personalities, a product that has the potential to change how humanity communicates. </p><p>They discuss the product, which involves deep voice cloning to capture and preserve a person's unique personality and voice. They discuss the ethical and security considerations of this technology, its applications in preserving legacies, and potential use cases for individuals with terminal illnesses. </p><p>Tune in as they delve into the philosophical aspects and future visions of immortalising human experiences through digital avatars.</p><p>00:00 Introduction To The Podcast<br>00:42 Meet Kate: Co-Founder of Panio<br>02:16 Understanding Digital Twins and Deep Voice Cloning<br>04:11 The Vision Behind Panio<br>05:33 Addressing Ethical and Security Concerns<br>06:48 Personal Stories and Use Cases<br>10:57 Future Plans and Technological Advancements<br>16:06 Customer Engagement and Feedback<br>33:20 Final Thoughts and Closing Remarks</p><p>https://pantio.io/</p>]]>
      </description>
      <content:encoded>
        <![CDATA[<p>Would you clone your likeness and personality with AI?</p><p>Chris is joined by Katherine Ivanova, co-founder of Pantio, a company dedicated to creating digital personalities, a product that has the potential to change how humanity communicates. </p><p>They discuss the product, which involves deep voice cloning to capture and preserve a person's unique personality and voice. They discuss the ethical and security considerations of this technology, its applications in preserving legacies, and potential use cases for individuals with terminal illnesses. </p><p>Tune in as they delve into the philosophical aspects and future visions of immortalising human experiences through digital avatars.</p><p>00:00 Introduction To The Podcast<br>00:42 Meet Kate: Co-Founder of Panio<br>02:16 Understanding Digital Twins and Deep Voice Cloning<br>04:11 The Vision Behind Panio<br>05:33 Addressing Ethical and Security Concerns<br>06:48 Personal Stories and Use Cases<br>10:57 Future Plans and Technological Advancements<br>16:06 Customer Engagement and Feedback<br>33:20 Final Thoughts and Closing Remarks</p><p>https://pantio.io/</p>]]>
      </content:encoded>
      <pubDate>Sun, 14 Dec 2025 18:00:00 -0800</pubDate>
      <author>Chris Coyne</author>
      <enclosure url="https://prfx.byspotify.com/e/media.transistor.fm/221490da/0b3e4f9f.mp3" length="34166459" type="audio/mpeg"/>
      <itunes:author>Chris Coyne</itunes:author>
      <itunes:duration>2133</itunes:duration>
      <itunes:summary>
        <![CDATA[<p>Would you clone your likeness and personality with AI?</p><p>Chris is joined by Katherine Ivanova, co-founder of Pantio, a company dedicated to creating digital personalities, a product that has the potential to change how humanity communicates. </p><p>They discuss the product, which involves deep voice cloning to capture and preserve a person's unique personality and voice. They discuss the ethical and security considerations of this technology, its applications in preserving legacies, and potential use cases for individuals with terminal illnesses. </p><p>Tune in as they delve into the philosophical aspects and future visions of immortalising human experiences through digital avatars.</p><p>00:00 Introduction To The Podcast<br>00:42 Meet Kate: Co-Founder of Panio<br>02:16 Understanding Digital Twins and Deep Voice Cloning<br>04:11 The Vision Behind Panio<br>05:33 Addressing Ethical and Security Concerns<br>06:48 Personal Stories and Use Cases<br>10:57 Future Plans and Technological Advancements<br>16:06 Customer Engagement and Feedback<br>33:20 Final Thoughts and Closing Remarks</p><p>https://pantio.io/</p>]]>
      </itunes:summary>
      <itunes:keywords>Machine Learning, AI, Deep Learning, Recommender Systems, Reinforcement Learning</itunes:keywords>
      <itunes:explicit>No</itunes:explicit>
      <podcast:transcript url="https://share.transistor.fm/s/221490da/transcript.vtt" type="text/vtt" rel="captions"/>
      <podcast:transcript url="https://share.transistor.fm/s/221490da/transcript.json" type="application/json"/>
    </item>
    <item>
      <title>Vivek Chand - OpenClaw, Agents and Observability</title>
      <itunes:episode>21</itunes:episode>
      <podcast:episode>21</podcast:episode>
      <itunes:title>Vivek Chand - OpenClaw, Agents and Observability</itunes:title>
      <itunes:episodeType>full</itunes:episodeType>
      <guid isPermaLink="false">3c17182c-1d06-455d-8e19-280a5f30646c</guid>
      <link>https://share.transistor.fm/s/0b6385db</link>
      <description>
        <![CDATA[<p>AI Agent Observability: OpenClaw, ClawMetry and Observability | Vivek Chand (Booking.com)</p><p>How do you monitor AI agents in production? </p><p>In this episode, Vivek Chand, tech leader at Booking.com and founder of ClawMetry breaks down AI agent observability, evaluation loops, and his open-source tool ClawMetry tracking agent behaviour in real time. Clawmetry is an open-source tool with already 30,000 plus downloads after just a week. </p><p>Vivek shares his engineering journey from startups to leading customer support AI at Booking.com, what it actually takes to ship AI systems that deliver ROI, and why observability is the missing layer for agentic AI workflows.</p><p>We cover OpenClaw for coding agents, how ClawMetry visualizes agent actions, subagent spawning, file access, and token usage, plus the roadmap for remote monitoring, mobile apps, and security alerts.</p><p>🔑 Topics covered:<br>AI agent observability explained<br>Building production AI systems at Booking.com<br>Evaluation loops for prediction quality<br>OpenClaw use cases for coding agents<br>Clawmetry Telemetry: open-source agent monitoring<br>Advice for junior AI engineers in 2026</p><p>00:00 Welcome and Guest Intro<br>00:59 Vivek Career Journey<br>03:03 Building AI at Booking<br>04:26 Scaling Systems and Eval Loops<br>06:19 Advice for Junior Engineers<br>07:48 Why Agent Observability Matters<br>11:30 OpenClaw Use Cases for Coding<br>13:21 Productivity Gains with Agents<br>14:43 What Telemetry Does<br>18:03 How Telemetry Was Built<br>19:53 Roadmap Managed and Security<br>22:24 Future of Agents and Monitoring</p><p>To download and try Clawmetry, you can use the following link: https://clawmetry.com/</p><p>There is also a cloud version available with a 7-day free trial here: https://clawmetry.com/cloud</p><p>Clawmetry Mac app:  https://clawmetry.com/mac</p>]]>
      </description>
      <content:encoded>
        <![CDATA[<p>AI Agent Observability: OpenClaw, ClawMetry and Observability | Vivek Chand (Booking.com)</p><p>How do you monitor AI agents in production? </p><p>In this episode, Vivek Chand, tech leader at Booking.com and founder of ClawMetry breaks down AI agent observability, evaluation loops, and his open-source tool ClawMetry tracking agent behaviour in real time. Clawmetry is an open-source tool with already 30,000 plus downloads after just a week. </p><p>Vivek shares his engineering journey from startups to leading customer support AI at Booking.com, what it actually takes to ship AI systems that deliver ROI, and why observability is the missing layer for agentic AI workflows.</p><p>We cover OpenClaw for coding agents, how ClawMetry visualizes agent actions, subagent spawning, file access, and token usage, plus the roadmap for remote monitoring, mobile apps, and security alerts.</p><p>🔑 Topics covered:<br>AI agent observability explained<br>Building production AI systems at Booking.com<br>Evaluation loops for prediction quality<br>OpenClaw use cases for coding agents<br>Clawmetry Telemetry: open-source agent monitoring<br>Advice for junior AI engineers in 2026</p><p>00:00 Welcome and Guest Intro<br>00:59 Vivek Career Journey<br>03:03 Building AI at Booking<br>04:26 Scaling Systems and Eval Loops<br>06:19 Advice for Junior Engineers<br>07:48 Why Agent Observability Matters<br>11:30 OpenClaw Use Cases for Coding<br>13:21 Productivity Gains with Agents<br>14:43 What Telemetry Does<br>18:03 How Telemetry Was Built<br>19:53 Roadmap Managed and Security<br>22:24 Future of Agents and Monitoring</p><p>To download and try Clawmetry, you can use the following link: https://clawmetry.com/</p><p>There is also a cloud version available with a 7-day free trial here: https://clawmetry.com/cloud</p><p>Clawmetry Mac app:  https://clawmetry.com/mac</p>]]>
      </content:encoded>
      <pubDate>Wed, 11 Mar 2026 04:10:59 -0700</pubDate>
      <author>Chris Coyne</author>
      <enclosure url="https://prfx.byspotify.com/e/media.transistor.fm/0b6385db/899ae85d.mp3" length="22980215" type="audio/mpeg"/>
      <itunes:author>Chris Coyne</itunes:author>
      <itunes:duration>1434</itunes:duration>
      <itunes:summary>
        <![CDATA[<p>AI Agent Observability: OpenClaw, ClawMetry and Observability | Vivek Chand (Booking.com)</p><p>How do you monitor AI agents in production? </p><p>In this episode, Vivek Chand, tech leader at Booking.com and founder of ClawMetry breaks down AI agent observability, evaluation loops, and his open-source tool ClawMetry tracking agent behaviour in real time. Clawmetry is an open-source tool with already 30,000 plus downloads after just a week. </p><p>Vivek shares his engineering journey from startups to leading customer support AI at Booking.com, what it actually takes to ship AI systems that deliver ROI, and why observability is the missing layer for agentic AI workflows.</p><p>We cover OpenClaw for coding agents, how ClawMetry visualizes agent actions, subagent spawning, file access, and token usage, plus the roadmap for remote monitoring, mobile apps, and security alerts.</p><p>🔑 Topics covered:<br>AI agent observability explained<br>Building production AI systems at Booking.com<br>Evaluation loops for prediction quality<br>OpenClaw use cases for coding agents<br>Clawmetry Telemetry: open-source agent monitoring<br>Advice for junior AI engineers in 2026</p><p>00:00 Welcome and Guest Intro<br>00:59 Vivek Career Journey<br>03:03 Building AI at Booking<br>04:26 Scaling Systems and Eval Loops<br>06:19 Advice for Junior Engineers<br>07:48 Why Agent Observability Matters<br>11:30 OpenClaw Use Cases for Coding<br>13:21 Productivity Gains with Agents<br>14:43 What Telemetry Does<br>18:03 How Telemetry Was Built<br>19:53 Roadmap Managed and Security<br>22:24 Future of Agents and Monitoring</p><p>To download and try Clawmetry, you can use the following link: https://clawmetry.com/</p><p>There is also a cloud version available with a 7-day free trial here: https://clawmetry.com/cloud</p><p>Clawmetry Mac app:  https://clawmetry.com/mac</p>]]>
      </itunes:summary>
      <itunes:keywords>Machine Learning, AI, Deep Learning, Recommender Systems, Reinforcement Learning</itunes:keywords>
      <itunes:explicit>No</itunes:explicit>
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      <title>Darminder Singh - Scaling Agents and AI from Pilot to Production</title>
      <itunes:episode>22</itunes:episode>
      <podcast:episode>22</podcast:episode>
      <itunes:title>Darminder Singh - Scaling Agents and AI from Pilot to Production</itunes:title>
      <itunes:episodeType>full</itunes:episodeType>
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      <link>https://share.transistor.fm/s/ca47fb74</link>
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        <![CDATA[<p>How do you actually move enterprise AI from pilot to production — and measure real ROI?</p><p>In this episode of The NeuralPod, Chris Coyne sits down with Darminder Singh, AI leader at HCLTech AI Labs, to unpack what separates AI initiatives that deliver measurable business value from those that stall. </p><p>With a career spanning engineering, data science at KPMG and Fujitsu, and deep work in defence and critical national infrastructure, Darminder offers a rare cross-sector view on what genuinely works.</p><p>The conversation covers:</p><p>00:00 Why Leverage AI<br>00:23 Meet Amin Inda<br>00:54 Engineering to Data Value<br>02:55 Business Skills for AI Leaders<br>04:31 Consulting Lessons and Teams<br>05:36 Hiring for Growth Mindset<br>08:03 AI in Defense Edge vs Office<br>10:34 Data Culture and Tool Ecosystems<br>15:11 HCL Labs and Scaling GenAI<br>17:45 Agent ROI and Orchestration<br>23:31 Data Mesh and Common Pitfalls<br>26:24 Guardrails Red Teaming Regulation<br>28:19 Future Trends Personal Agents<br>31:38 Autonomous Employees and Trust<br>32:47 Reading List and Wrap Up</p>]]>
      </description>
      <content:encoded>
        <![CDATA[<p>How do you actually move enterprise AI from pilot to production — and measure real ROI?</p><p>In this episode of The NeuralPod, Chris Coyne sits down with Darminder Singh, AI leader at HCLTech AI Labs, to unpack what separates AI initiatives that deliver measurable business value from those that stall. </p><p>With a career spanning engineering, data science at KPMG and Fujitsu, and deep work in defence and critical national infrastructure, Darminder offers a rare cross-sector view on what genuinely works.</p><p>The conversation covers:</p><p>00:00 Why Leverage AI<br>00:23 Meet Amin Inda<br>00:54 Engineering to Data Value<br>02:55 Business Skills for AI Leaders<br>04:31 Consulting Lessons and Teams<br>05:36 Hiring for Growth Mindset<br>08:03 AI in Defense Edge vs Office<br>10:34 Data Culture and Tool Ecosystems<br>15:11 HCL Labs and Scaling GenAI<br>17:45 Agent ROI and Orchestration<br>23:31 Data Mesh and Common Pitfalls<br>26:24 Guardrails Red Teaming Regulation<br>28:19 Future Trends Personal Agents<br>31:38 Autonomous Employees and Trust<br>32:47 Reading List and Wrap Up</p>]]>
      </content:encoded>
      <pubDate>Thu, 07 May 2026 13:51:04 -0700</pubDate>
      <author>Chris Coyne</author>
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      <itunes:author>Chris Coyne</itunes:author>
      <itunes:duration>2095</itunes:duration>
      <itunes:summary>
        <![CDATA[<p>How do you actually move enterprise AI from pilot to production — and measure real ROI?</p><p>In this episode of The NeuralPod, Chris Coyne sits down with Darminder Singh, AI leader at HCLTech AI Labs, to unpack what separates AI initiatives that deliver measurable business value from those that stall. </p><p>With a career spanning engineering, data science at KPMG and Fujitsu, and deep work in defence and critical national infrastructure, Darminder offers a rare cross-sector view on what genuinely works.</p><p>The conversation covers:</p><p>00:00 Why Leverage AI<br>00:23 Meet Amin Inda<br>00:54 Engineering to Data Value<br>02:55 Business Skills for AI Leaders<br>04:31 Consulting Lessons and Teams<br>05:36 Hiring for Growth Mindset<br>08:03 AI in Defense Edge vs Office<br>10:34 Data Culture and Tool Ecosystems<br>15:11 HCL Labs and Scaling GenAI<br>17:45 Agent ROI and Orchestration<br>23:31 Data Mesh and Common Pitfalls<br>26:24 Guardrails Red Teaming Regulation<br>28:19 Future Trends Personal Agents<br>31:38 Autonomous Employees and Trust<br>32:47 Reading List and Wrap Up</p>]]>
      </itunes:summary>
      <itunes:keywords>Machine Learning, AI, Deep Learning, Recommender Systems, Reinforcement Learning</itunes:keywords>
      <itunes:explicit>No</itunes:explicit>
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