LLMs Research Podcast

State space models like Mamba promised linear scaling and constant memory. They delivered on efficiency, but researchers kept hitting the same wall: ask Mamba to recall something specific from early in a long context, and performance drops.

Three pa... more

Episode Title: What ICLR 2026 Taught Us About Multi-Agent Failures

Episode Summary: We scanned ICLR 2026 accepted papers and found 14 that address real problems when building multi-agent systems: slow pipelines, expensive token bills, cascading erro... more

The podcast discusses the technical shift in large language models from a standard 512-token context window to modern architectures capable of processing millions of tokens. Initial growth was constrained by the quadratic complexity of self-attention... more

Jan 17–23, 2026: The Rise of the Action LayerHow multimodal AI is shifting from passive perception to active controlThe current landscape of research reflects a shift toward Multimodal Agentic Intelligence, where multimodal capabilities are no longer... more

Over the past several years, we have moved from the machine learning era through the large language model era and into what researchers now call the agent era. But we did not arrive here overnight. A series of research contributions, each building on... more

The focus of LLM research is undergoing a significant shift from simply increasing model size to making existing capabilities practically usable for deployment. This week’s papers highlight four emerging themes: Reasoning & Agents, Generation & Synth... more

Key takeaway from todays podcast:

Robust Reasoning: The Holonomic Network achieves perfect fidelity extrapolation 100x beyond training lengths, demonstrating a new universality class for logical reasoning with topological stability.

Efficient Infer... more

* Bayesian & Cognitive Advances: Transformers achieve ultra-precise Bayesian inference with 10⁻³ to 10⁻⁴ bit accuracy, while CREST boosts reasoning accuracy by 17.5% and cuts token usage by 37.6%.

* Model Efficiency & Scaling: TG reduces data needs ... more