Gradient Dissent: Conversations on AI

Lukas Biewald

Join Lukas Biewald on Gradient Dissent, an AI-focused podcast brought to you by Weights & Biases. Dive into fascinating conversations with industry giants from NVIDIA, Meta, Google, Lyft, OpenAI, and more. Explore the cutting-edge of AI and learn the intricacies of bringing models into production.

  1. The Startup Powering The Data Behind AGI

    16. RUJ

    The Startup Powering The Data Behind AGI

    In this episode of Gradient Dissent, Lukas Biewald talks with the CEO & founder of Surge AI, the billion-dollar company quietly powering the next generation of frontier LLMs. They discuss Surge's origin story, why traditional data labeling is broken, and how their research-focused approach is reshaping how models are trained. You’ll hear why inter-annotator agreement fails in high-complexity tasks like poetry and math, why synthetic data is often overrated, and how Surge builds rich RL environments to stress-test agentic reasoning. They also go deep on what kinds of data will be critical to future progress in AI—from scientific discovery to multimodal reasoning and personalized alignment. It’s a rare, behind-the-scenes look into the world of high-quality data generation at scale—straight from the team most frontier labs trust to get it right. Timestamps: 00:00 – Intro: Who is Edwin Chen? 03:40 – The problem with early data labeling systems 06:20 – Search ranking, clickbait, and product principles 10:05 – Why Surge focused on high-skill, high-quality labeling 13:50 – From Craigslist workers to a billion-dollar business 16:40 – Scaling without funding and avoiding Silicon Valley status games 21:15 – Why most human data platforms lack real tech 25:05 – Detecting cheaters, liars, and low-quality labelers 28:30 – Why inter-annotator agreement is a flawed metric 32:15 – What makes a great poem? Not checkboxes 36:40 – Measuring subjective quality rigorously 40:00 – What types of data are becoming more important 44:15 – Scientific collaboration and frontier research data 47:00 – Multimodal data, Argentinian coding, and hyper-specificity 50:10 – What's wrong with LMSYS and benchmark hacking 53:20 – Personalization and taste in model behavior 56:00 – Synthetic data vs. high-quality human data Follow Weights & Biases: https://twitter.com/weights_biases https://www.linkedin.com/company/wandb

    56 min
  2. Arvind Jain on Building Glean and the Future of Enterprise AI

    5. KOL

    Arvind Jain on Building Glean and the Future of Enterprise AI

    In this episode of Gradient Dissent, Lukas Biewald sits down with Arvind Jain, CEO and founder of Glean. They discuss Glean's evolution from solving enterprise search to building agentic AI tools that understand internal knowledge and workflows. Arvind shares how his early use of transformer models in 2019 laid the foundation for Glean’s success, well before the term "generative AI" was mainstream. They explore the technical and organizational challenges behind enterprise LLMs—including security, hallucination suppression—and when it makes sense to fine-tune models. Arvind also reflects on his previous startup Rubrik and explains how Glean’s AI platform aims to reshape how teams operate, from personalized agents to ever-fresh internal documentation. Follow Arvind Jain: https://x.com/jainarvind Follow Weights & Biases: https://x.com/weights_biases Timestamps:  [00:01:00] What Glean is and how it works  [00:02:39] Starting Glean before the LLM boom  [00:04:10] Using transformers early in enterprise search  [00:06:48] Semantic search vs. generative answers  [00:08:13] When to fine-tune vs. use out-of-box models  [00:12:38] The value of small, purpose-trained models  [00:13:04] Enterprise security and embedding risks [00:16:31] Lessons from Rubrik and starting Glean  [00:19:31] The contrarian bet on enterprise search  [00:22:57] Culture and lessons learned from Google  [00:25:13] Everyone will have their own AI-powered "team"  [00:28:43] Using AI to keep documentation evergreen  [00:31:22] AI-generated churn and risk analysis  [00:33:55] Measuring model improvement with golden sets [00:36:05] Suppressing hallucinations with citations  [00:39:22] Agents that can ping humans for help  [00:40:41] AI as a force multiplier, not a replacement  [00:42:26] The enduring value of hard work

    44 min
  3. How DeepL Built a Translation Powerhouse with AI with CEO Jarek Kutylowski

    8. SRP

    How DeepL Built a Translation Powerhouse with AI with CEO Jarek Kutylowski

    In this episode of Gradient Dissent, Lukas Biewald talks with Jarek Kutylowski, CEO and founder of DeepL, an AI-powered translation company. Jarek shares DeepL’s journey from launching neural machine translation in 2017 to building custom data centers and how small teams can not only take on big players like Google Translate but win. They dive into what makes translation so difficult for AI, why high-quality translations still require human context, and how DeepL tailors models for enterprise use cases. They also discuss the evolution of speech translation, compute infrastructure, training on curated multilingual datasets, hallucinations in models, and why DeepL avoids fine-tuning for each individual customer. It’s a fascinating behind-the-scenes look at one of the most advanced real-world applications of deep learning. Timestamps: [00:00:00] Introducing Jarek and DeepL’s mission [00:01:46] Competing with Google Translate & LLMs [00:04:14] Pretraining vs. proprietary model strategy [00:06:47] Building GPU data centers in 2017 [00:08:09] The value of curated bilingual and monolingual data [00:09:30] How DeepL measures translation quality [00:12:27] Personalization and enterprise-specific tuning [00:14:04] Why translation demand is growing [00:16:16] ROI of incremental quality gains [00:18:20] The role of human translators in the future [00:22:48] Hallucinations in translation models [00:24:05] DeepL’s work on speech translation [00:28:22] The broader impact of global communication [00:30:32] Handling smaller languages and language pairs [00:32:25] Multi-language model consolidation [00:35:28] Engineering infrastructure for large-scale inference [00:39:23] Adapting to evolving LLM landscape & enterprise needs

    43 min
  4. GitHub CEO Thomas Dohmke on Copilot and the Future of Software Development

    10. LIP

    GitHub CEO Thomas Dohmke on Copilot and the Future of Software Development

    In this episode of Gradient Dissent, Lukas Biewald sits down with Thomas Dohmke, CEO of GitHub, to talk about the future of software engineering in the age of AI. They discuss how GitHub Copilot was built, why agents are reshaping developer workflows, and what it takes to make tools that are not only powerful but also fun. Thomas shares his experience leading GitHub through its $7.5B acquisition by Microsoft, the unexpected ways it accelerated innovation, and why developer happiness is crucial to productivity. They explore what still makes human engineers irreplaceable and how the next generation of developers might grow up coding alongside AI. Follow Thomas Dohmke: https://www.linkedin.com/in/ashtom/ Follow Weights & Biases: https://twitter.com/weights_biases https://www.linkedin.com/company/wandb

    1 h 10 min
  5. From Pharma to AGI Hype, and Developing AI in Finance: Martin Shkreli’s Journey

    20. SVI

    From Pharma to AGI Hype, and Developing AI in Finance: Martin Shkreli’s Journey

    In this episode of Gradient Dissent, Lukas Biewald talks with Martin Shkreli — the infamous "pharma bro" turned founder — about his path from hedge fund manager and pharma CEO to convicted felon and now software entrepreneur. Shkreli shares his side of the drug pricing controversy, reflects on his prison experience, and explains how he rebuilt his life and business after being "canceled." They dive deep into AI and drug discovery, where Shkreli delivers a strong critique of mainstream approaches. He also talks about his latest venture in finance software, building Godel Terminal “a Vim for traders", and why he thinks the AI hype cycle is just beginning. It's a wide-ranging and candid conversation with one of the most controversial figures in tech and biotech. Follow Martin Shkreli on Twitter Godel Terminal: https://godelterminal.com/ Follow Weights & Biases on Twitter https://www.linkedin.com/company/wandb   Join the Weights & Biases Discord Server: https://discord.gg/CkZKRNnaf3

    1 h 30 min
  6. Inside Cursor: The future of AI coding with Co-founder Sualeh Asif

    29. TRA

    Inside Cursor: The future of AI coding with Co-founder Sualeh Asif

    In this episode of Gradient Dissent, host Lukas Biewald talks with Sualeh Asif, the CPO and co-founder of Cursor, one of the fastest-growing and most loved AI-powered coding platforms. Sualeh shares the story behind Cursor’s creation, the technical and design decisions that set it apart, and how AI models are changing the way we build software. They dive deep into infrastructure challenges, the importance of speed and user experience, and how emerging trends in agents and reasoning models are reshaping the developer workflow. Sualeh also discusses scaling AI inference to support hundreds of millions of requests per day, building trust through product quality, and his vision for how programming will evolve in the next few years. ⏳Timestamps: 00:00 How Cursor got started and why it took off 04:50 Switching from Vim to VS Code and the rise of CoPilot 08:10 Why Cursor won among competitors: product philosophy and execution 10:30 How user data and feedback loops drive Cursor’s improvements 12:20 Iterating on AI agents: what made Cursor hold back and wait 13:30 Competitive coding background: advantage or challenge? 16:30 Making coding fun again: latency, flow, and model choices 19:10 Building Cursor’s infrastructure: from GPUs to indexing billions of files 26:00 How Cursor prioritizes compute allocation for indexing 30:00 Running massive ML infrastructure: surprises and scaling lessons 34:50 Why Cursor chose DeepSeek models early 36:00 Where AI agents are heading next 40:07 Debugging and evaluating complex AI agents 42:00 How coding workflows will change over the next 2–3 years 46:20 Dream future projects: AI for reading codebases and papers 🎙 Get our podcasts on these platforms: Apple Podcasts: https://wandb.me/apple-podcastsSpotify: https://wandb.me/spotifyYouTube: https://wandb.me/youtube Follow Weights & Biases: https://x.com/weights_biaseshttps://www.linkedin.com/company/wandb

    50 min
  7. Inside the Dark Web, AI and Cybersecurity with Christopher Ahlberg CEO of Recorded Future

    8. TRA

    Inside the Dark Web, AI and Cybersecurity with Christopher Ahlberg CEO of Recorded Future

    In this episode of Gradient Dissent, host Lukas Biewald talks with Christopher Ahlberg, CEO of Recorded Future, a pioneering cybersecurity company leveraging AI to provide intelligence insights. Christopher shares his fascinating journey from founding data visualization startup Spotfire to building Recorded Future into an industry leader, eventually leading to its acquisition by Mastercard. They dive into gripping stories of cyber espionage, including how Recorded Future intercepted a hacker selling access to the U.S. Electoral Assistance Commission. Christopher also explains why the criminal underworld has shifted to platforms like Telegram, how AI is transforming both cyber threats and defenses, and the real-world implications of becoming an "undesirable enemy" of the Russian state. This episode offers unique insights into cybersecurity, AI-driven intelligence, entrepreneurship lessons from a two-time founder, and what happens when geopolitical tensions intersect with cutting-edge technology. A must-listen for anyone interested in cybersecurity, artificial intelligence, or the complex dynamics shaping global security. 🎙 Get our podcasts on these platforms: Apple Podcasts: https://wandb.me/apple-podcasts Spotify: https://wandb.me/spotify YouTube: https://wandb.me/youtube Follow Weights & Biases: https://twitter.com/weights_biases  https://www.linkedin.com/company/wandb

    50 min
  8. AI, autonomy, and the future of naval warfare with Captain Jon Haase, United States Navy

    25. OŽU

    AI, autonomy, and the future of naval warfare with Captain Jon Haase, United States Navy

    In this episode of Gradient Dissent, host Lukas Biewald speaks with Captain Jon Haase, United States Navy about real-world applications of AI and autonomy in defense. From underwater mine detection with autonomous vehicles to the ethics of lethal AI systems, this conversation dives into how the U.S. military is integrating AI into mission-critical operations — and why humans will always be at the center of warfighting. They explore the challenges of underwater autonomy, multi-agent collaboration, cybersecurity, and the growing role of large language models like Gemini and Claude in the defense space. Essential listening for anyone curious about military AI, defense tech, and the future of autonomous systems. ✅ *Subscribe to Weights & Biases* → https://bit.ly/45BCkYz 🎙 Get our podcasts on these platforms: Apple Podcasts: http://wandb.me/apple-podcasts Spotify: http://wandb.me/spotify Google: http://wandb.me/gd_google YouTube: http://wandb.me/youtube Follow Weights & Biases: https://twitter.com/weights_biases https://www.linkedin.com/company/wandb Join the Weights & Biases Discord Server: https://discord.gg/CkZKRNnaf3

    1 h 2 min
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Opis

Join Lukas Biewald on Gradient Dissent, an AI-focused podcast brought to you by Weights & Biases. Dive into fascinating conversations with industry giants from NVIDIA, Meta, Google, Lyft, OpenAI, and more. Explore the cutting-edge of AI and learn the intricacies of bringing models into production.

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