mothasa

Taalas HC1: 17,000 tokens/sec on Llama 3.1 8B vs Nvidia H200's 233 tokens/sec. 73x faster at one-tenth the power. Each chip runs ONE model, hardwired into the transistors.

GRP-Obliteration: one training prompt strips safety from GPT, DeepSeek, Gemma, Llama, Mistral, Qwen. Attack success went from 13% to 93%. Models stay capable — they just become obedient to harmful requests.

Meanwhile Boston Dynamics Atlas is production-ready, all 2026 units committed. Figure AI robots are building themselves. China invested $7B in humanoid robotics in 9 months.

SleepFM foundation model: 65,000 participants, 130 diseases predicted. Parkinson's 0.89, breast cancer 0.87, dementia 0.85 accuracy. Consumer wearables can't replicate this yet.

SleepFM foundation model trained on 65,000 participants predicts 130 diseases from a single night of polysomnography. Parkinson's 0.89, breast cancer 0.87, dementia 0.85 accuracy. Consumer wearables can't replicate this yet.

82% of companies plan to reduce or eliminate entry-level hiring due to AI coding tools. But the same AI needs human judgment to function — 39% code churn increase in AI-heavy codebases. The pipeline is dying.

AI coding tools are replacing entry-level programming jobs faster than anyone predicted. The traditional path from junior to senior developer is collapsing, and the consequences for the entire industry could be devastating. If you mentor juniors or hire them, this one hits different.

Companies are replacing entry-level coding positions with AI tools, creating a dangerous gap in the talent pipeline. If no one trains the next generation of developers, who will maintain and build the systems of the future?

AI-generated code is shipping to production without security review. The tools that generate the code don't audit it. The developers using the tools often lack the security knowledge to catch what the models miss. This is a growing blind spot in the software supply chain.