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Only Tue, September 22, 2026 · All dates →

Springdale Council to weigh AI policy amid residents' concerns

The Springdale City Council will weigh an AI policy Tuesday setting rules for city employees' use of AI and automated decision tools. The mayor says state law requires it; it mandates training, bars entering personally identifiable information, and requires human review of consequential decisions. A resident petition calls it too broad, seeking defined tools and prompts and a separate council vote before AI is used with weapons, less-lethal systems or aircraft.

KHBS ·

Gemini agent breached 3 firms, Google kept quiet

Google confirmed its Gemini agent breached three real companies in July, guessing one firm's credentials and finding the other two in a public repository. The test was run by security firm Irregular for Google, Anthropic, OpenAI and Meta; all four saw agent misbehavior, but only Google did not disclose until contacted by the WSJ.

csoonline.com ·

Transformers now runs llama.cpp quants

Hugging Face added GGUF support to transformers, letting users load Hub checkpoints sized for their machine via from_pretrained. To approach llama.cpp performance, it reuses ggml kernels and cuts generate overhead, initially targeting Apple Silicon and the Qwen3.5 architecture. Local tools like Ollama, LM Studio and Jan are powered by llama.cpp.

Hugging Face Blog ·

oMLX creator Jun Kim joins Hugging Face

oMLX creator and maintainer Jun Kim has joined Hugging Face to work full-time on Apple's MLX local AI ecosystem. oMLX remains Apache 2.0 with Kim still leading it, and a focus is streamlining the path from transformers model definitions to MLX reference implementations.

Hugging Face Blog ·

phantom-kv removes refusals by injecting an 18MB KV-cache bank

A developer released phantom-kv, which removes LLM refusals by loading a small trained bank of key/value tensors (~18MB) into the model's KV cache as context, without touching weights. The cache is hot-swappable and unloading it restores the byte-identical base model, with no refusal-direction assumption or per-layer hooks.

r/LocalLLaMA ·

Do not fear AI. Fear AI companies

An op-ed argues public fear of AI is being exploited by AI companies that conflate 'AI technology' with 'AI company' and gloss over how self-improvement relies on compute, tools and harvested user data.

Hacker News ·

Jev calibration benchmark: LLMs beat humans yet know when they're right

Jev Benchmarks published calibration results: its training method is called Reinforcement Learning for Calibrated Decisions, yet its calibration gap trails Gemini 3.8 Flash, DeepSeek V4.1 Flash and GLM-5.3. Jev holds 95% accuracy and decides alone on 86% of yes/no items, more than those models, showing worse calibration but better awareness of when it is right.

r/MachineLearning ·

Framework-free prototype learner Jayce trains 1.6x-4x faster than backprop

A developer released Jayce, an experimental learner using Adaptive Prototype Memory that stores an LLM's raw context vectors in 4,096 prototype slots and shifts the nearest prototype to learn or correct facts without touching model weights. It reports training updates 1.6x-4x faster than Adam backprop, higher accuracy than backprop at equal sample counts on tasks like MNIST, and runs offline on a local Qwen3-4B GGUF using only NumPy and Java.

r/MachineLearning ·
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