Jul 23, 2026

Coding Agents Are Secretly General Agents

Jay Hack, head of AI at ClickUp, discusses the evolution of AI from early computer vision to generalist coding agents, highlighting how 'positive transfer' makes coding an 'AGI-complete' domain. He delves into the brutal economics of AI startups facing foundation model giants, ClickUp's strategy for convergence and first-party data as a moat, and the challenges of verifiability and catastrophic forgetting. The conversation also explores LLMs at the scientific frontier, the 'car wash test' revealing limits of world models, and speculative future applications like LLM resorts and game integration.

Jul 21, 2026

Causal Models Need Causal Data - Xaira’s X-Cell model (Bo Wang & Ci Chu)

Bo Wang and Ci Chu of Xaira Therapeutics introduce X-Cell, a 4.9-billion-parameter diffusion language model designed to predict cellular responses to genetic perturbations. Trained on PISCES, the largest genome-wide CRISPRi Perturb-seq dataset (25.6 million single cells across 16 contexts), X-Cell overcomes limitations of previous observational models. The discussion highlights the critical role of high-quality, causal data, X-Cell's architecture advantages, and its demonstrated ability to generalize to unseen cell types and primary cells, marking a significant step towards truly predictive virtual cell models in drug discovery.

Jul 19, 2026

From Tokens to Cells: Foundation Models for Single-Cell Biology - Akram Baharlouei, Altos Labs

Akram Baharlouei from Altos Labs discusses the engineering hurdles in developing foundation models for single-cell biology. The talk covers the importance of single-cell analysis for cellular rejuvenation and drug discovery, the complexities and challenges of single-cell data (particularly RNA-seq), and a comparative analysis of current foundation model approaches, highlighting the limitations of transformer-based models and the potential of flow matching techniques like PrimeFlow.

Jun 30, 2026

Multimodal & Embodied Intelligence (Pt 1), Panel on Multimodal AI: Progress, Pitfalls, Possibilities

This session explored Multimodal and Embodied Intelligence, featuring talks on hybrid AI in robotics (classical vs. end-to-end), AI's role in healthcare (focusing on NCDs, deployment, and uncertainty modeling), and fundamental perception challenges in multimodal reasoning (using educational video QA and visual puzzles). A panel discussed the impact of foundation models, the blurred lines between AGI and human-like AI, critical deployment pitfalls (human factors, efficiency, architectural limits), and future directions, emphasizing task-specific models and the redefinition of 'foundation models.'

Jun 26, 2026

Plenary Talk 3: Challenges and Research Opportunities for Global Hyperscale Services

This talk provides a comprehensive overview of cellular aging, brain function, and the mechanisms of cognitive decline, particularly focusing on Alzheimer's disease. It delves into the role of various cell types, neural communication, and methods for assessing cognition. The speaker highlights research challenges, the limitations of current pharmacological interventions, and the critical importance of non-pharmacological lifestyle interventions. A significant portion of the discussion is dedicated to the Centre for Brain Research's (CBR) multi-disciplinary efforts in India, including large-scale cohort studies, multimodal data collection, and the development of AI-driven tools and a localized foundation model for the Indian brain to address neurodegeneration.

May 26, 2026

How Cursor Trained Composer on Fireworks: Distributed Infrastructure for High-Performance RL

Cursor's Federico Cassano and Fireworks' Dmytro Dzhulgakov detail their collaboration on Composer 2, a specialized foundation model for software engineering. They discuss their top-down training strategy, the infrastructure challenges of large-scale distributed Reinforcement Learning on sparse models, and how model specialization achieves frontier performance with superior efficiency.