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Only Tue, September 15, 2026 · All dates →

SHADOW-50M: 44M param 19.8MB offline LLM

The author trained SHADOW-50M from scratch (44M parameters on 45B tokens). The model is 19.8 MB, runs ≈1,900 tok/s on laptop CPU, uses ternary weights and a large token fingerprint vocabulary, operates fully offline, and includes built‑in calculator and fast disk indexing; released as a proof of concept.

r/MachineLearning ·

Anthropic confirms Claude used in weapons and surveillance

Anthropic confirmed that Claude was used to develop military software and support intelligence operations, including radar analysis, ranking air-defense targets, and aiding electronic warfare. In one Taiwan scenario it modeled engagement envelopes for Patriot- and THAAD-class systems and evaluated targets.

The Defense Post ·

Report: China narrows AI gap with U.S.

The report says China has been rapidly closing its AI lead over the U.S. in model capabilities and research despite U.S. export restrictions on advanced chips and equipment. Experts describe the U.S.–China model gap as narrowing, noting Chinese efforts such as Moonshot AI’s Kimi K3.

ABC News - Breaking News, Latest News and Videos ·

Open Chinese models narrow gap with frontier models

A Mozilla report finds that the performance gap between Chinese open-weight models and US frontier models has narrowed to roughly 4.4 months. It highlights Moonshot AI's Kimi K3 scoring three points behind Anthropic's Fable 5 on a composite index while costing about 30% as much, suggesting open models are preferable for most routine workloads.

Ars Technica ·

Salesforce debuts Koa reasoning model on Nvidia Nemotron

At Dreamforce Salesforce unveiled Koa, its first reasoning model built on Nvidia's open-weight Nemotron, optimized for sales, marketing and customer-support tasks. Koa offers enterprises an open-weight alternative that was post-trained without ingesting customer data, integrates into Agentforce, and aims to reduce token costs while meeting data-security requirements.

TechCrunch ·

Critique: 1Password's AI Patching Benchmark

A critique of 1Password's August 6, 2026 report says its 26% "clean fix" rate is misleading: the sample focused on difficult bugs, 22% of trials instructed agents to apply wrong fixes, 36% forbade building or testing, and models used different reasoning settings. The authors also released agent skills for post-patch validation and review walkthroughs.

Hacker News ·

TSMC Executive Urges Caution on AI

A TSMC co-COO compared AI to a “three-year-old superman” who can't tell right from wrong, explaining the company's cautious approach to adopting AI to manage risks and uncertainties.

Bloomberg ·

Calls to slow AI won't curb data center demand

Bloomberg argues that despite calls to slow AI development, ongoing use of existing models and services will continue to drive strong demand for computing power and data centers, making a sharp drop in capacity needs unlikely in the near term.

Bloomberg ·

GBAPS launches K–12 AI lessons

The Green Bay school district will introduce two age‑appropriate AI lessons for K–12 covering AI basics, responsible use, and academic integrity; staff may use approved AI tools for instruction, but students are barred from using external AI tools on school computers, and the district is posting “traffic‑light” guidance.

Green Bay Press-Gazette ·

How much of F‑Droid is LLM generated?

A Hacker News discussion examines how much content in F‑Droid apps is generated by LLMs, noting it's hard to detect but some signs (icons, code style) can hint at AI involvement, reflecting concern about AI's impact on the open‑source ecosystem.

Hacker News ·
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