Living together in a group is a strategy many animals use to survive and thrive. And a big part of what makes that living situation successful is listening. In this episode, we explore the collaborative world of the naked mole-rat. Threshold is nonprofit, listener-supported, and independently produced. You can support Threshold by donating today . To stay connected, sign up for our newsletter . Operation frog sound! Send us your frog sounds for an upcoming episode. We want you to go out, listen for frogs and toads, and record them. Just find someone croaking, and hit record on your phone. It doesn’t matter if there’s background noise. It doesn’t even matter if you’re not sure whether or not you’re hearing an amphibian—if you think you are, we would love to get a recording from you. Please also say your name and where you are in the world, and then email the recording to us at outreach@thresholdpodcast.org…
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Chain of Thought
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Galileo에서 제공하는 콘텐츠입니다. 에피소드, 그래픽, 팟캐스트 설명을 포함한 모든 팟캐스트 콘텐츠는 Galileo 또는 해당 팟캐스트 플랫폼 파트너가 직접 업로드하고 제공합니다. 누군가가 귀하의 허락 없이 귀하의 저작물을 사용하고 있다고 생각되는 경우 여기에 설명된 절차를 따르실 수 있습니다 https://ko.player.fm/legal.
Introducing Chain of Thought, the podcast for software engineers and leaders that demystifies artificial intelligence. Join us each week as we tell the stories of the people building the AI revolution, unravel actionable strategies and share practical techniques for building effective GenerativeAI applications.
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Galileo에서 제공하는 콘텐츠입니다. 에피소드, 그래픽, 팟캐스트 설명을 포함한 모든 팟캐스트 콘텐츠는 Galileo 또는 해당 팟캐스트 플랫폼 파트너가 직접 업로드하고 제공합니다. 누군가가 귀하의 허락 없이 귀하의 저작물을 사용하고 있다고 생각되는 경우 여기에 설명된 절차를 따르실 수 있습니다 https://ko.player.fm/legal.
Introducing Chain of Thought, the podcast for software engineers and leaders that demystifies artificial intelligence. Join us each week as we tell the stories of the people building the AI revolution, unravel actionable strategies and share practical techniques for building effective GenerativeAI applications.
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Chain of Thought

1 AI Won't Solve Your Toughest Engineering Problems | Honeycomb’s Charity Majors 41:48
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Generative AI dominates the conversation, but does it actually make it easier to build, lead, and sustain high-performing engineering teams? Host Conor Bronsdon sits down with Charity Majors, co-founder and CTO of Honeycomb (.io), and the mind behind charity.wtf. Known for her sharp insights and unfiltered opinions, Charity kicks off the discussion by expanding on her popular article: 'Generative AI is not going to build your engineering team for you.' Together, they explore how AI has altered the dynamics for engineering teams and leaders. The discussion navigates the complex dynamics of hiring in an AI-enabled era, challenging the "senior-only" trend and championing the vital role of junior engineers in creating learning organizations. Charity also explains why writing code is often the "easy part" compared to the full lifecycle of owning and operating systems, a challenge amplified by AI-generated code. Finally, Conor and Charity discuss the risk of "cognitive decay" from over-reliance on AI tools and why fostering deep system understanding remains paramount for engineers and leaders. Chapters 00:00 Introduction and Guest Welcome 01:51 Generative AI and Engineering Teams 02:26 The Writing Process and Inspiration 03:49 AI's Impact on Hiring and Team Building 05:30 Embracing AI and Automation 07:43 The Role of Junior Engineers 09:33 Building Effective Engineering Teams 17:01 Future of AI in Code Generation 20:07 High Performing Engineering Teams 21:48 Evolving Expectations for Engineering Managers 22:41 Cognitive Decay 25:00 Feedback Loops in Software Systems 26:56 Hiring for Potential vs. Experience 29:17 The Future of Observability 39:50 Closing Thoughts and Advice for Engineers Follow the hosts Follow Atin Follow Conor Follow Vikram Follow Yash Follow Today's Guest(s) Follow Charity: charity.wtf Learn more about Honeycomb: www.honeycomb.io Read: Generative AI is not going to build your engineering team for you Check out Galileo Try Galileo…
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Chain of Thought

1 Building IBM's watsonx & The Future of Enterprise AI | Dr. Maryam Ashoori 45:09
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Building trustworthy, scalable AI isn't just about models; it's about navigating a complex ecosystem of tools and regulations. Join hosts Conor Bronsdon and Atindriyo Sanyal as they explore these challenges with Dr. Maryam Ashoori, Head of Product for watsonx AI at IBM. To meet these challenges, Maryam explains how watsonx simplifies the AI stack, automates pipelines, and empowers enterprises to scale their AI operations while optimizing costs rapidly. Maryam also explores IBM's strategy for leveraging open-source and commercial models, enabling the potential of agentic systems. Plus, she shares insights from a recent survey of 1,000 developers, revealing key takeaways about the current landscape for enterprise AI implementation, and what results mean for both developers and the enterprises they support. Chapters 00:00 Introducing Dr. Maryam Ashoori 01:13 Overview of IBM's AI Strategy 01:47 Enterprise AI Challenges and Solutions 04:40 IBM's Approach to AI Models and Tooling 09:52 Simplifying the AI Stack 12:20 Challenges in Agentic AI 15:55 Importance of Data Management and Lineage 21:11 IBM's Strategy for Gen AI Products 23:43 Scaling Challenges with Agents 27:40 Effective Agent Evaluation Systems 35:18 Gaps and Opportunities in AI Tooling 41:35 Success Stories with watsonx 44:00 Closing Remarks Follow the hosts Follow Atin Follow Conor Follow Vikram Follow Yash Follow Today's Guest(s) watsonx.ai Check out Galileo Try Galileo…
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Chain of Thought

1 What is Information Symmetry and Will AI Unlock it? | DevRev’s Manoj Agarwal 40:54
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What if everyone in your organization had equal information at all times? Would meetings even exist? This week, we dive into the concept of information symmetry with Manoj Agarwal, co-founder and president of DevRev. Manoj, along with hosts Conor Bronsdon and Yash Sheth, explores how DevRev is connecting data, personalizing schemas, and automating complex tasks, offering a glimpse into the next generation of AI-driven workflows. This is revolutionizing enterprise data and decision-making by breaking down the silos that create information asymmetry. Learn how AI is reshaping business outcomes and collaboration, moving us closer to a world where everyone has the information they need. Chapters: 00:00 Welcome to Chain of Thought 00:57 Information Symmetry in Enterprises 02:03 Challenges of Decision Making 03:41 Recency Bias and Product Management 04:58 Data Silos and Information Waste 05:23 Structured vs. Unstructured Data 06:04 Collaboration and Data Retrieval Issues 08:17 DevRev's Approach to AI and Data Integration 09:23 Building a Business-Centric Knowledge Graph 10:00 Conversational AI and Automation 12:57 Agentic Interactions and Skills Programming 20:05 Multi-Agent Systems and Future Vision 21:25 Challenges in Multi-Agent Communication 25:10 Data Cleanliness and Governance 28:14 Trust and Reliability in AI Systems 36:58 Conclusion and Future Outlook Follow the hosts Follow Atin Follow Conor Follow Vikram Follow Yash Follow Today's Guest(s) devrev.ai DevRev University LinkedIn Manoj Agarwal Check out Galileo Try Galileo…
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Is the agentic AI bubble about to burst? Kelly Vaughn, Director of Engineering at Spot AI, questions whether the agent craze is overpromising potential and leading startups down a path of unsustainable expectations. Never one to shy away from a hot take, Kelly joins host Conor Bronsdon for a pragmatic look at AI, discussing the differences between building AI-enabled and traditional software, why replacing humans with AI teams will backfire (looking at you customer service), and the proliferation of AI tools. Kelly also shares insights on constructing AI teams, navigating data governance, and building user trust while avoiding common startup pitfalls. Chapters: 00:00 Introduction and Guest Welcome 01:13 Is Agentic AI a Bubble? 02:40 Startup Challenges and Market Noise 11:02 Building AI Products vs. Traditional Software 17:31 Ethical Implications and Governance 19:48 Constructing AI-Enabled Teams 22:07 AI Tooling and Productivity 26:00 Questioning Productivity Claims 32:28 Conclusion and Final Thoughts Follow the hosts Follow Atin Follow Conor Follow Vikram Follow Yash Follow Today's Guest(s) Kelly’s Newsletter The Modern Leader LinkedIn Kelly Vaughn Check out Galileo Try Galileo…
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Chain of Thought

1 Using AI to Modernize Your Legacy Applications | MongoDB’s Rachelle Palmer 43:37
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Imagine cutting your legacy code modernization timeline from years to months. It’s no longer science fiction and this week’s guest is here to tell us how. Rachelle Palmer, Director of Product Management at MongoDB, joins hosts Conor Bronsdon and Atindriyo Sanyal, for a discussion on the groundbreaking ways AI is modernizing legacy applications. At MongoDB, Rachelle's forward-deployed AI engineering team is tackling the challenge of transforming complex, outdated codebases, freeing developers from technical debt. She details how LLMs are automating tasks like improving documentation, test generation, and even business logic conversion, dramatically reducing modernization timelines from years to months. What once demanded teams of dozens can now be achieved with a small, highly efficient team. Chapters: 00:00 Introduction and Host Welcome 00:58 Challenges in Modernizing Legacy Applications 02:52 Real-World Examples of Code Modernization 04:00 The Role of LLMs in Code Modernization 08:01 Measuring Success in AI-Powered Modernization 12:28 The Future of AI in Engineering 16:17 Evaluating Modernization Success 21:12 Returning to Your Startup Roots 29:07 Forward Deployed AI Engineers 35:36 Importance of Academic Research in AI 42:10 Conclusion and Farewell Follow the hosts Follow Atin Follow Conor Follow Vikram Follow Yash Follow Today's Guest(s) Rachelle Palmer MongoDB Application Modernization Factory Check out Galileo Try Galileo…
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1 Can Your AI Strategy Be Future-Proof? | Galileo’s Vikram Chatterji 29:16
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This week, we're sharing a special episode courtesy of 'Dev Interrupted.' Our co-host, Galileo CEO Vikram Chatterji, recently joined theDev Interrupted team for an engaging discussion on AI strategy. We were so impressed by the conversation that we wanted to share it with our audience, and they were kind enough to let us. We hope you enjoy it! From Dev Interrupted: "Vikram Chatterji joins Dev Interrupted’s Andrew Zigler to discuss how engineering leaders can future-proof their AI strategy and navigate an emerging dilemma: the pressure to adopt AI to stay competitive, while justifying AI spending and avoiding risky investments. To accomplish this, Vikram emphasizes the importance of establishing clear evaluation frameworks, prioritizing AI use cases based on business needs and understanding your company's unique cultural context when deploying AI." Chapters: 00:00 Introduction and Special Announcement 01:14 Welcome to Dev Interrupted 01:42 Challenges in AI Adoption 03:16 Balancing Business Needs and AI 06:15 Crawl, Walk, Run Approach 10:52 Building Trust and Prototyping 13:07 AI Agents as Smart Routers 13:50 Galileo's Role in AI Development 16:25 Evaluating AI Systems 25:36 Skills for Engineering Leaders 27:35 Conclusion Follow the hosts Follow Atin Follow Conor Follow Vikram Follow Yash Follow Dev Interrupted Podcast Substack LinkedIn Follow Dev Interrupted Hosts Andrew Ben Check out Galileo Try Galileo…
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1 The Making of Gemini 2.0: DeepMind's Approach to AI Development and Deployment | Logan Kilpatrick 40:32
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Google’s strength in AI has often seemed to get lost in the midst of OpenAI announcements or DeepSeek fervor - yet Gemini 2.0 is more than good for many tasks; it’s the model to beat - and we have the research to back it up. This week, Logan Kilpatrick, senior product manager at Google DeepMind, joins us to discuss Gemini’s creation story, its emergence as the premiere model in the AI race, and why the launch of Gemini 2.0 is great news for developers. During the conversation Conor and Logan explore the exciting world of multimodal AI, Gemini's strengths in agentic use cases, and its unique approach to function calling, compositional function calling, and the seamless integration of tools like search and code execution. They also chat about Logan’s vision for a future where AI interacts with the world more naturally, offering a view of the potential of vision-first AI agents, and why Google's hardware advantage is enabling Gemini's impressive performance and long context capabilities. Follow along with the discussion using Galileo’s AI Agent Leaderboard: https://huggingface.co/spaces/galileo-ai/agent-leaderboard Chapters:00:00 DeepMind's Role in Gemini's Development 03:49 Gemini 2.0 Updates and Developer Highlights 06:08 Agentic Use Cases and Function Calling 11:29 Multimodal Capabilities 16:15 Putting AI in Production 21:06 Gemini's Differentiation and Hardware 31:22 Future Vision for Gemini and G Suite Integration 35:23 Gemini for Developers 39:02 Conclusion and Farewell Follow the hosts Follow Atin Follow Conor Follow Vikram Follow Yash Follow Logan Twitter: @OfficialLoganK LinkedIn: https://www.linkedin.com/in/logankilpatrick/ Show Notes Try Gemini for yourself: gemini.google.com Gemini for Developers: aistudio.google.com Check out Galileo Try Galileo…
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Chain of Thought

This week, hosts Conor Bronsdon and Atindriyo Sanyal discuss the fallout from DeepSeek's groundbreaking R1 model, its impact on the open-source AI landscape, and how its release will impact model development moving forward. They also discuss what effect (if any) export controls have had on AI innovation and whether we’re witnessing the rise of “Agents as a Service”. To tackle the increasing complexity of agentic systems, Conor and Atin highlight the need for robust evaluation frameworks, discussing the challenges of measuring agent performance, and how the recent launch of Galileo's agentic evaluations are empowering developers to build safer and more effective AI agents. Chapters: 00:00 Introduction 02:09 DeepSeek's Impact and Innovations 03:43 Open Source AI and Industry Implications 13:44 Export Controls and Global AI Competition 18:55 Software as a Service 19:29 Agentic Evaluations 25:14 Metrics for Success 31:34 Conclusion and Farewell Follow the hosts Follow Atin Follow Conor Follow Vikram Follow Yash Check out Galileo Try Galileo Show Notes On DeepSeek and Export Controls Introducing Agentic Evaluations…
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Chain of Thought

1 AI, Open Source & Developer Safety | Block’s Rizel Scarlett 33:43
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As DeepSeek so aptly demonstrated, AI doesn’t need to be closed source to be successful. This week, Rizel Scarlett, a Staff Developer Advocate at Block, joins Conor Bronsdon to discuss the intersections between AI, open source, and developer advocacy. Rizel shares her journey into the world of AI, her passion for empowering developers, and her work on Block's new AI initiative, Goose , an on-machine developer agent designed to automate engineering tasks and enhance productivity. Conor and Rizel also explore how AI can enable psychological safety, especially for junior developers. Building on this theme of community, they also dive into topics such as responsible AI development, ethical considerations in AI, and the impact of community involvement when building open source developer tools. Chapters: 00:00 Rizel's Role at Block 02:41 Introducing Goose: Block's AI Agent 06:30 Psychological Safety and AI for Developers 11:24 AI Tools and Team Dynamics 17:28 Open Source AI and Community Involvement 25:29 Future of AI in Developer Communities 27:47 Responsible and Ethical Use of AI 31:34 Conclusion Follow Conor Bronsdon: https://www.linkedin.com/in/conorbronsdon/ Rizel Scarlett LinkedIn: https://www.linkedin.com/in/rizel-bobb-semple/ Website: https://blackgirlbytes.dev/ Show Notes Learn more about Goose: https://block.github.io/goose/…
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1 AI in 2025: Agents & The Rise of Evaluation Driven Development 33:13
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"In the next three to five years, every piece of software that is built on this planet will have some sort of AI baked into it." - Atin Sanyal Chain of Thought is back for its second season, and this episode dives headfirst into the possibilities AI holds for 2025 and beyond. Join Conor Bronson as he chats with Galileo co-founders Yash Sheth (COO) and Atindriyo Sanyal (CTO) about major trends to look for this year. These include AI finding its product "tool stack" fit, generation latency decreasing, AI agents, their potential to revolutionize code generation and other industries, and the crucial role of robust evaluation tools in ensuring the responsible and effective deployment of these agents. Yash and Atin also highlight Galileo's focus on building trust and security in AI applications through scalable evaluation intelligence. They emphasize the importance of quantifying application behavior, enforcing metrics in production, and adapting to the evolving needs of AI development. Finally, they discuss Galileo's vision for the future and their active pursuit of partnerships in 2025 to contribute to a more reliable and trustworthy AI ecosystem. Chapters: 00:00 AI Trends and Predictions for 2025 02:55 Advancements in LLMs and Code Generation 05:16 Challenges and Opportunities in AI Development 10:40 Evaluating AI Agents and Applications 16:07 Building Evaluation Intelligence 23:41 Research Opportunities 29:50 Advice for Leveraging AI in 2025 32:00 Closing Remarks Show Notes: Check out Galileo Follow Yash Follow Atin Follow Conor…
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"This is the time. This is the time to start building... I can't say that often enough. This is the time." - Bob van Luijt Join Bob van Luijt, CEO and co-founder of Weaviate as he sits down with our host Conor Bronson for the Season 2 premiere of Chain of Thought. Together, they explore the ever-evolving world of AI infrastructure and the evolution of Retrieval-Augmented Generation (RAG) architecture. Bob's journey with Weaviate offers a compelling example of how to adapt to rapid changes in the AI landscape. He discusses the importance of understanding developer needs and building AI-native solutions, emphasizing the potential of generative feedback loops and agent architectures to revolutionize data management. Chapters: 00:00 Welcome to Season 2 1:43 The Evolution of AI Infrastructure 04:13 Navigating Rapid Changes in AI 07:39 Generative Feedback Loops and AI Native Databases 13:26 Challenges and Opportunities in AI Production 19:03 The Importance of Documentation and Developer Experience 27:13 Future Predictions and Paradigm Shifts in AI 31:17 Final Thoughts and Encouragement to Build Follow: Conor Bronsdon: https://www.linkedin.com/in/conorbronsdon/ Bob van Luijt: https://www.linkedin.com/in/bobvanluijt/ Weaviate: https://www.linkedin.com/company/weaviate-io/ Show notes: Learn more about Weaviate: https://weaviate.io/…
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1 How AI Assistants Can Enhance Human Connection | Twilio’s Vinnie Giarrusso 42:19
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Can AI assistants actually enhance human connection? As Season 1 of Chain of Thought comes to a close, Conor Bronsdon and Vinnie Giarrusso (Twilio) explore the transformative potential of AI assistants in the workplace. Discover how these assistants function as "async junior digital employees," taking on specific tasks and contributing to the organizational structure. But will AI assistants ultimately replace human connection? Vinnie argues the opposite is true, suggesting that AI can liberate employees from mundane tasks, allowing them to focus on building meaningful relationships and providing personalized experiences. This thought-provoking conversation takes a philosophical turn as Vinnie explores how AI could revolutionize education while potentially disrupting traditional mentorship roles. He shares his vision for a future where AI democratizes information and empowers individuals to personalize their learning journey. Finally, learn how Twilio and Galileo are partnering to shape the future of AI and what this collaboration means for both companies. Chain of Thought will be taking a break for the holidays, but we'll see you back here on January 8th for the start of Season 2! Chapters: 00:00 Twilio's AI Agent Platform 06:34 Ensuring Accuracy and Trustworthiness 09:49 Challenges and Failure Modes 17:39 Future of Fully Autonomous Agents 22:18 Human-AI Collaboration and Mentorship 31:24 Education and Democratization of Information 32:58 Partnership with Galileo 39:54 Conclusion and Season Wrap-Up Follow: Conor Bronsdon: https://www.linkedin.com/in/conorbronsdon/ Vinnie Giarrusso: https://www.linkedin.com/in/vinniegiarrusso/ Show notes: Twilio Alpha: https://twilioalpha.com OWASP GenAI: https://genai.owasp.org…
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1 Lessons from Deploying AI at Enterprise Scale | ServiceTitan, Indeed & Twilio 50:54
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This week, a panel of experts (Mehmet Murat Ezbiderli, ServiceTitan; Grant Ledford, Indeed; and Vinnie Giarrusso, Twilio) join Atin Sanyal (CTO, Galileo) and Conor Bronsdon (Developer Awareness, Galileo) to explore the challenges and opportunities of deploying GenAI at enterprise scale in a conversation that's a wake-up call for any business leader looking to harness the power of AI. Together, Atin & Conor break down key considerations like performance, cost, and model selection, emphasizing the need for robust evaluation frameworks and a shift in developer mindset. Atin then sits down with our panel of AI engineering experts to discuss their firsthand experiences with enterprise AI, including the trade-offs of building AI systems, the evolving tools and frameworks available, and the impact these technologies are having on their organizations. Chapters: 00:00 Enterprise Scale Deployment 05:17 Cost, Performance, and Model Selection 08:59 Building and Integrating GenAI Systems 15:26 Emerging Enterprise Use Cases 18:12 Predictions for AI in 2025 27:28 Panel Discussion: Deploying AI at Enterprise Scale 31:19 Gen AI Solutions and Challenges 33:12 Building & Deploying Traditional Infrastructure vs GenAI Infrastructure 34:36 How to Assemble Your GenAI Stack 40:39 Today's Best GenAI Use Cases 48:15 Enterprise AI Trends for 2025 50:36 Closing Remarks and Future Outlook Follow: Atin Sanyal: https://www.linkedin.com/in/atinsanyal/ Mehmet Murat Ezbiderli: https://www.linkedin.com/in/mehmet-murat-ezbiderli-b894a49/ Grant Ledford: https://www.linkedin.com/in/grant-ledford-36b146a5/ Vinnie Giarrusso: https://www.linkedin.com/in/vinniegiarrusso/ Show notes: Watch all of Productionize: https://www.galileo.ai/genai-productionize-2-0…
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1 Practical Lessons for GenAI Evals | Chip Huyen & Vivienne Zhang 48:02
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As AI agents and multimodal models become more prevalent, understanding how to evaluate GenAI is no longer optional – it's essential. Generative AI introduces new complexities in assessment compared to traditional software, and this week on Chain of Thought we’re joined by Chip Huyen (Storyteller, Tép Studio), Vivienne Zhang (Senior Product Manager, Generative AI Software, Nvidia) for a discussion on AI evaluation best practices. Before we hear from our guests, Vikram Chatterji (CEO, Galileo) and Conor Bronsdon (Developer Awareness, Galileo) give their takes on the complexities of AI evals and how to overcome them through the use of objective criteria in evaluating open-ended tasks, the role of hallucinations in AI models, and the importance of human-in-the-loop systems. Afterwards, Chip and Vivienne sit down with Atin Sanyal (Co-Founder & CTO, Galileo) to explore common evaluation approaches, best practices for building frameworks, and implementation lessons. They also discuss the nuances of evaluating AI coding assistants and agentic systems. Chapters: 00:00 Challenges in Evaluating Generative AI 05:45 Evaluating AI Agents 13:08 Are Hallucinations Bad? 17:12 Human in the Loop Systems 20:49 Panel discussion begins 22:57 Challenges in Evaluating Intelligent Systems 24:37 User Feedback and Iterative Improvement 26:47 Post-Deployment Evaluations and Common Mistakes 28:52 Hallucinations in AI: Definitions and Challenges 34:17 Evaluating AI Coding Assistants 38:15 Agentic Systems: Use Cases and Evaluations 43:00 Trends in AI Models and Hardware 45:42 Future of AI in Enterprises 47:16 Conclusion and Final Thoughts Follow: Vikram Chatterji: https://www.linkedin.com/in/vikram-chatterji/ Atin Sanyal: https://www.linkedin.com/in/atinsanyal/ Conor Bronsdon: https://www.linkedin.com/in/conorbronsdon/ Chip Huyen: https://www.linkedin.com/in/chiphuyen/ Vivienne Zhang: https://www.linkedin.com/in/viviennejiaozhang/ Show notes: Watch all of Productionize 2.0: https://www.galileo.ai/genai-productionize-2-0…
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1 The Real ROI of Enterprise AI | HP, ServiceNow & Accenture 41:16
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The “ROI of AI” has been marketed as a panacea, a near-magical solution to all business problems. Following that promise, many companies have invested heavily in AI over the past year and are now asking themselves, “What is the return on my AI investment?” This week on Chain of Thought, Galileo’s CEO, Vikram Chatterji joins Conor Bronsdon to discuss AI's value proposition, from the initial hype to the current search for tangible returns, offering insights into how businesses can identify the right AI use cases to maximize their investment. Next, we’re joined by a panel of AI experts to discuss the ROI of Enterprise AI, featuring Alex Klug, Head of Product, Data Science & AI at HP; Sriram Palapudi, Sr. Dir, ML Platform Engineering at ServiceNow; and Jay Subrahmonia, Global MD for AI Research & Products at Accenture. Together, they explore effective implementation strategies, how to measure the returns of AI adoption in the enterprise, and why AI's ROI isn't always just about the bottom line. Chapters: 00:00 Current State of AI Investments 03:59 Challenges and Solutions in AI Implementation 08:30 Identifying and Prioritizing AI Use Cases 10:53 Ensuring Trust and Explainability in AI 15:29 Measuring ROI and Efficiency Gains 21:10 Panel Discussion Begins 21:54 Trust and Risk Management at HP 23:27 Accenture's Approach to Operationalizing AI 26:06 ServiceNow's Trade-offs and Prioritization 31:17 Measuring the success of AI for customers 36:29 Frameworks and Best Practices 40:57 Conclusion and Final Thoughts Follow: Vikram Chatterji: https://www.linkedin.com/in/vikram-chatterji/ Conor Bronsdon: https://www.linkedin.com/in/conorbronsdon/ Alex Klug: https://www.linkedin.com/in/alex-klug-67ba3655/ Sriram Palapudi: https://www.linkedin.com/in/sriram-palapudi-11294b1/ Jay Subrahmonia: https://www.linkedin.com/in/jayashree-subrahmonia-99963a/ Show notes: Watch all of Productionize 2.0: https://www.galileo.ai/genai-productionize-2-0…
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