Join Amir Haghighat, co-founder of Baseten, and Yineng Zhang, lead software engineer at Baseten, as they dive into the groundbreaking DeepSeek v3 model. This model boasts 671 billion parameters and has shaken up LLM inference platforms. They unravel the complexities of deploying massive models, discuss the innovations of SGLang, and delve into the challenges of caching technologies. With insights on optimizing AI workflows and a clear manifesto for crucial applications, this conversation is a must-listen for AI enthusiasts!

Simon Willison, a leading AI blogger, and Swyx, an AI expert, share insights on the evolving landscape of AI in 2025. They discuss exciting advancements in large language models, focusing on cost efficiency and competition challenges. The duo tackles the skepticism around AI agents, emphasizing their limitations and potential applications in various industries. They also dive into the role of AI influencers and the need for credibility in AI-generated content. Finally, they explore the future of AI interfaces and the rising interest in local LLMs and wearable technologies.

Join Will Bryk, CEO of Exa.ai and former SpaceX engineer, as he dives into redefining search technology. Explore how the shift from link-based to semantic search is revolutionizing user experience. Will discusses the power of neural PageRank, hyper-personalized results, and a groundbreaking $5M AI infrastructure. He contrasts traditional search models with a future focused on understanding context and enhancing scalability. Additionally, he offers insights into startup culture and innovative workplace solutions—like nap pods!

Discover the fascinating journey of ComfyUI, an innovative open-source tool for AI image generation that challenges traditional interfaces. Unpack the technical intricacies of diffusion models, prompt weighting, and model customization. Learn about the clever design philosophy behind a node execution engine and how it enhances the user experience. Explore the rise of ComfyUI among competitors, community contributions, and future projects, including the integration of new text features and exciting advancements in AI art.

Celebrate the evolution of AI engineering over the past two years. Discover insights into the shift from research to practical applications and the future of AI agents. Dive into discussions around agent collusion, synthetic vs. real data, and the competitive dynamics between major AI players. Explore the latest trends from AI conferences and the impact of memory technologies on machine learning. Reflect on the past year's achievements and exciting prospects for the coming year in AI.

Graham Neubig, a Professor at CMU and chief scientist at All Hands AI, dives into the future of coding agents. He discusses the rise of agents by 2025, highlighting the outstanding achievements of OpenHands in software engineering. The conversation covers the integration of human expertise into agent functionality, the significance of effective prompts, and the advancements in AI agents within the Sweebench repository. Neubig also tackles challenges in AI development, emphasizing the role of accessible technology and innovative benchmarks for improvement.

Lubna Ben-Alau, an AI researcher at Hugging Face, dives into the dynamic world of synthetic data and small language models. She discusses how 2024 saw a remarkable surge in synthetic data applications, with notable contributions like Apple's Rephrasing the Web and Hugging Face's Cosmopedia. Lubna emphasizes the transformative impact of synthetic data on model performance and diversity. The conversation also touches on the evolution of small models, highlighting their efficiency, improved privacy, and specialized applications for on-device use.

Dan Fu, an AI researcher soon to join UCSD, and Eugene Cheah, CEO of Featherless AI, delve into the future of post-transformer architectures. They discuss innovations like RWKV and state-space models, highlighting their collaborative and open-source nature. The duo examines the challenges of multilingual training and computational efficiency, while also exploring advancements in non-transformer models like Mamba and Jamba. Tune in for insights on scaling models, 'infinite context,' and how new architectures are reshaping the AI landscape!

Luca Soldaini, a research scientist at the Allen Institute for AI, and Sophia Yang, head of Developer Relations at Mistral AI, dive into the explosive rise of open models in 2024. They discuss breakthrough models like Llama 3 and the MOE model, highlighting the competitive dynamics in AI. Key challenges such as regulatory hurdles and limited training data access are explored. The conversation also emphasizes the need for collaboration and open-source methodologies to foster innovation in a rapidly evolving landscape.

In this engaging discussion, Isaac Robinson and Peter Robicheaux from Roboflow share insights on the latest trends and groundbreaking papers in computer vision for 2024. They highlight the shift towards video-based models like 'Sora' and advancements in real-time object detection. Vik Korrapati, founder of Moondream, presents challenges in developing vision language models and introduces a compact, pruned model. Together, they explore how these innovations can reshape the landscape of computer vision and enhance pre-trained model efficiencies.