Guide Labs debuts a new kind of interpretable LLM

The company open-sourced an 8 billion parameter LLM, Steerling-8B, trained with a new architecture designed to make its ...
Sify

All About India’s Indigenous AI LLM Models – Can They Help Tackle Bias?

The Indian technological space has been blowing up in February 2026, even as the India AI Impact Summit 2026 was underway in ...

Manifold-Constrained Hyper-Connections: The Architectural Breakthrough That Might Redefine LLM Training

If mHC scales the way early benchmarks suggest, it could reshape how we think about model capacity, compute budgets and the ...
DataBreachToday

Open-Weight AI Models Fail the Jailbreak Test

Cisco tested eight major open-weight artificial intelligence models and found multi-turn jailbreak attacks succeeded nearly ...
InfoWorld

Multi-token prediction technique triples LLM inference speed without auxiliary draft models

With reported 3x speed gains and limited degradation in output quality, the method targets one of the biggest pain points in production AI systems: latency at scale.
CSO Online

How to make LLMs a defensive advantage without creating a new attack surface

LLMs can supercharge your SOC, but if you don’t fence them in, they’ll open a brand-new attack surface while attackers scale faster.

Researchers baked 3x inference speedups directly into LLM weights — without speculative decoding

Researchers from the University of Maryland, Lawrence Livermore, Columbia and TogetherAI have developed a training technique that triples LLM inference speed without auxiliary models or infrastructure ...