Large language models

Jul 28, 2025

Building Better Language Models Through Global Understanding

Dr. Mazi Fadai discusses the critical challenges in multilingual AI, including data imbalances and flawed evaluation methodologies. She argues that tackling these difficult multilingual problems is not only essential for global accessibility but also a catalyst for fundamental AI innovation, much like how machine translation research led to the Transformer architecture. The talk introduces new, more culturally aware evaluation benchmarks like Global MMLU and INCLUDE as a path toward building more robust and globally representative language models.

Jul 26, 2025

Intelligence = Doing More with Less (David Krakauer)

Prof. David Krakauer argues that we are confusing knowledge with intelligence. He critiques the AI community's superficial definition of "emergence" in LLMs, contrasting it with the true meaning from complex systems: a fundamental change in internal organization that allows for a simpler, more powerful macroscopic description. He introduces "exbodiment"—outsourcing cognition to external tools—as a key part of collective intelligence, but warns that our evolutionary drive to conserve energy will lead us to outsource our thinking to AI, causing a "diminution and dilution" of human thought.

Jul 24, 2025

Inside GPT – The Maths Behind the Magic • Alan Smith • GOTO 2024

A deep dive into the internal workings of Large Language Models like GPT, explaining the journey from a text prompt through tokenization, embeddings, and the attention mechanism to generate a response.

Jul 22, 2025

OpenAI Just Released ChatGPT Agent, Its Most Powerful Agent Yet

The OpenAI team details the creation of a new, powerful AI agent in ChatGPT, achieved by unifying the Deep Research and Operator models. They cover its unified architecture with shared state across tools, the reinforcement learning techniques used for training, and the critical safety measures required for an agent that can take real-world actions.

Jul 21, 2025

The Future of Software Development - Vibe Coding, Prompt Engineering & AI Assistants

A discussion on the state of technical infrastructure, focusing on how AI and Large Language Models represent a new, fourth foundational pillar alongside compute, network, and storage. The talk covers how AI is disrupting software itself, the investment landscape, and the future of the developer profession.

Jul 17, 2025

No Priors Ep. 123 | With ReflectionAI Co-Founder and CEO Misha Laskin

Misha Laskin, co-founder of Reflection AI and former researcher at Google DeepMind, discusses the company's mission to build superhuman autonomous systems. He introduces Asimov, a code comprehension agent designed to solve the 80% of an engineer's time spent on understanding complex systems, rather than just code generation. Laskin delves into the intricacies of co-designing product and research, the critical role of customer-driven evaluations, the bottlenecks in scaling reinforcement learning (RL) — particularly the "reward problem" — and why he believes the future is one of "jagged superintelligence" emerging in specific, high-value domains like coding.