Nathan Lambert

Sebastian Raschka, hands-on ML educator and author of practical LLM guides, and Nathan Lambert, post-training lead at AI2 and RLHF specialist, discuss China vs US competition, which chatbots excel at coding and long context, open vs closed model tradeoffs, architectural tweaks like MOE, where progress really comes from (systems, data, post-training), RL with verifiable rewards, scaling laws, tool use and agents, and timelines toward AGI.

Nathan Lambert, an AI researcher from AI2 and Interconnects.ai, returns to explore the evolution of Reinforcement Learning with Verified Rewards (RLVR). He discusses how RLVR shifts from subjective feedback to verifiable reward signals, enhancing scalability and reliability. Lambert highlights the challenges of tool use in RL frameworks and showcases the Tulu model series aimed at democratizing AI development. The conversation dives into the balance of fine-tuning, user data significance, and the implications for future AI performance and design.

Join Nathan Lambert, a writer for the Interconnects newsletter and AI researcher at the Allen Institute, as he delves into the captivating world of artificial intelligence. Discover why OpenAI’s strategies seem to favor engagement farming and how this affects user interactions. Explore the competitive landscape of AI innovation in China versus the U.S., and get insights into Meta’s culture's impact on its Llama models. Nathan also shares unconventional career advice for succeeding in the AI landscape and recommends a thought-provoking book.

Nathan Lambert and Luca Soldaini from AI2 dive into the groundbreaking OLMo 3 release, showcasing their approach to open-source AI with full transparency. They discuss the significance of releasing comprehensive model data and the distinction between base, instruct, and thinking models. The conversation highlights the impact of Meta's retreat from the open-source space, leading to the rise of Chinese models. Nathan and Luca also explore the challenges of reasoning in AI, emphasizing the need for U.S. innovation and broader engagement in shaping AI's future.

Nathan Lambert, AI researcher at Interconnects.ai, sketches how agents and Claude Code reshape engineering workflows. Jasmine Sun, journalist at Jasmi.news, shares hands-on experiments with AI tooling and mainstream adoption stories. They riff on vibe-coding, agent orchestration, local models, automating research tasks, and playful prompts imagining apps for public figures.

Nathan Lambert, an AI researcher at AI2, and Jasmine Sun, a Substack writer, dive into the fascinating ways AI is transforming media. They discuss the challenges of monetizing content and the disparities in pay within journalism. The duo debates the competitive landscape between U.S. and China in AI, advocating for transparency and innovation. They also explore the dynamics of gender and content creation, highlighting the unique barriers faced by female creators in the digital space. Tune in for a blend of humor and deep insights!

Jasmine Sun, a journalist who covers AI, labor, and tech economics, and Nathan Lambert, an AI analyst and co-founder focused on GPUs and infrastructure, trade sharp takes. They dive into GPU smuggling and export-control motives. They compare GPT-5.4’s style, debate open versus closed models, and unpack AI writing, local models, and researcher incentives.

In this engaging discussion, David Marcus, co-founder of Lightspark, elaborates on his vision for a decentralized payment network leveraging Bitcoin. Ben Thompson analyzes the evolving tech landscape and AI's influence on business models. Richard Socher shares insights from the AI research front, while Naeem Talukdar discusses the fusion of AI in filmmaking. Scott Belsky reflects on the changing nature of creativity in the digital age. The conversation weaves through key industry changes, highlighting innovation and adaptability in technology.

Nathan Lambert, a machine learning scientist at the Allen Institute for AI, and AI ethicist Tom Gilbert discuss the contentious debate over open versus closed AI systems. They dive into the competitive landscape of AI innovation, questioning if France can rival China's advancements. The pair highlight the importance of democratizing access to technology and the challenges small businesses face in adopting AI. They also share insights from the NeurIPS conference, stressing transparency and collaboration in the evolving AI research ecosystem.

Nathan Lambert, a Bay Area-based CS PhD and writer for the Interconnects newsletter, joins to discuss the psyche of AI engineers in Silicon Valley and what Washington should understand about it. He explores the advancements of GPT-40 and the implications of Google's AI Dev Day, emphasizing the race for innovation. The conversation delves into the contrasting cultures of OpenAI and Google, the importance of user-centric design in AI, and how increased computational power reshapes organizational dynamics. It's a deep yet engaging dive into the current state and future of AI.