Jun 21, 2026

6 Things to Know about AIE World's Fair 2026

Discover the AI Engineering World's Fair 2026, the largest iteration yet, offering an unparalleled deep dive into AI engineering with expanded tracks on auto research, GPU specialization, and new verticals like finance and healthcare. Highlights include an innovative expo experience, exclusive leadership initiatives like the "Token Billionaires Program," and unique side events fostering community, including "Posters on AI" where attendees can defend their tweets. This event is designed to be a curated hub for practical, cutting-edge insights and networking in the AI/ML professional landscape.

Jun 10, 2026

Stop Making Models Bigger, Make Them Behave — Kobie Crawdord, Snorkel

Snorkel.ai's research demonstrates how a 4-billion-parameter model, fine-tuned with Reinforcement Learning for under $500, significantly outperformed a 235-billion-parameter model on financial analysis tool-use tasks. The key was cultivating 'tool discipline' and error correction capabilities, rather than relying on sheer model size or deeper reasoning. Single-table training generalized effectively to harder multi-table problems, emphasizing the importance of targeted behavioral fixes identified through detailed evaluation rubrics.

Jun 02, 2026

Task Fidelity Scaling Laws — Kobie Crawdord, Snorkel

An experiment by Snorkel AI reveals that in agentic AI training, the quality of tasks is paramount. Using the same model and compute, fine-tuning on high-quality tasks yielded a 6% performance improvement, a 5x greater uplift compared to the 1% gain from low-quality tasks. The key difference lies in the nature of the tasks: high-quality tasks are genuinely harder, featuring more tool calls and cleaner failure modes that provide a meaningful learning signal. In contrast, low-quality tasks often fail due to ambiguity and environmental noise, hindering effective model improvement.

May 26, 2026

End-to-End Foundation Models for the Energy Industry — with Jazmia Henry

Jazmia Henry details the end-to-end process of building specialized foundation models for the energy industry. She covers the four key stages from data curation of unstructured, handwritten documents to optimizing inference, and introduces her Grounded Continuous Evaluation (GCE) framework to combat reward hacking in reinforcement learning.

May 22, 2026

AI at college graduations and why Claude blackmails

The Mixture of Experts team discusses the growing skepticism towards AI among younger generations, a Microsoft study revealing how LLMs can corrupt data in complex workflows, Anthropic's data-centric fix for Claude's "blackmailing" issue, and the cultural debate over an AI-generated story potentially winning a literary prize, all circling the central themes of human ownership, trust, and the need for better processes in the age of AI.

Mar 31, 2026

Agentic Data Management and the Future of Enterprise AI — with Rohit Choudhary

Rohit Choudhary, CEO of Acceldata, discusses the imminent 10x annual growth of enterprise data and how most organizations are unprepared. He introduces Acceldata's agentic data management platform, designed to make data self-aware, self-optimizing, and AI-ready. He emphasizes the 1000x cost difference of fixing data early versus late, the need for operational, real-time data governance, and why clear thinking and deep domain expertise, not just programming skills, will be most valuable in the age of AI.