1. 14 Sep 2026

    AI agents blew the whistle on their cheating colleagues - MIT Technology Review

    That whistleblowing behavior, seen for the first time in a recent experiment run by Google DeepMind, could have implications for alignment researchers ...

    www.technologyreview.com ↗
  2. 13 Sep 2026

    OpenAI AI Slowdown, Anthropic Threat Report & AI News - The Neuron

    OpenAI asked Congress if AI labs can legally slow down · Bengio says pretraining imitates goal-pursuing human behavior, then reinforcement learning ...

    www.theneurondaily.com ↗
  3. 13 Sep 2026

    Latent Thought: How Recurrent Depth Works — and What Oversight Costs - Medium

    Mechanistic interpretability seeks to identify the internal computations that causally produce a model's behavior. In a depth-recurrent model, that ...

    medium.com ↗
  4. 11 Sep 2026

    Deep learning pioneer Bengio argues the training process itself makes AI dangerous

    Bengio says this behavior emerges from the training process itself, from imitating human text through reinforcement learning, and that poorly ...

    the-decoder.com ↗
  5. 11 Sep 2026

    A Multimodal RGB-D Dataset of Visuo-Gestural Facial Expressions in Peruvian Sign Language

    ... pairs of VGFEs in LSP. The dataset supports research on sign language technologies, multimodal facial behavior modeling, and inclusive AI systems.

    www.nature.com ↗
  6. 10 Sep 2026

    Vention Opens Montreal Physical AI Lab for Industrial Robotics - AI Insider

    Reinforcement learning: Improving robot behavior through repeated attempts and feedback. Industrial data and post-training: Collecting factory data ...

    theaiinsider.tech ↗
  7. 26 Aug 2026

    Silico AI Interpretability Agents Map Model Behaviors - IEEE Spectrum

    Mechanistic interpretability tools span the gamut. One approach is mapping a model's activations in response to controlled prompts, and matching those ...

    spectrum.ieee.org ↗
Sources

Where this comes from

Artificial Intelligence — Google

https://www.google.co.in/alerts/feeds/05832220720342067762/1990879549…

401 items Polled 22 Sep, 15:14 UTC 200

Agentic AI — Google

https://www.google.co.in/alerts/feeds/05832220720342067762/4849751788…

401 items Polled 22 Sep, 15:14 UTC 200

AI Agents — Google

https://www.google.co.in/alerts/feeds/05832220720342067762/4849751788…

401 items Polled 22 Sep, 15:14 UTC 200

Data Science — Google

https://www.google.co.in/alerts/feeds/05832220720342067762/4836803184…

401 items Polled 22 Sep, 15:14 UTC 200

Large Language Model — Google

https://www.google.co.in/alerts/feeds/05832220720342067762/8510459957…

401 items Polled 22 Sep, 15:14 UTC 200

Machine Learning — Google

https://www.google.co.in/alerts/feeds/05832220720342067762/4836803184…

401 items Polled 22 Sep, 15:14 UTC 200

Deep Learning — Google

https://www.google.co.in/alerts/feeds/05832220720342067762/1643871049…

401 items Polled 22 Sep, 15:14 UTC 200

LLMs Alignment — Google

https://www.google.co.in/alerts/feeds/05832220720342067762/5121641697…

45 items Polled 22 Sep, 15:14 UTC 200

AI Alignment — Google

https://www.google.co.in/alerts/feeds/05832220720342067762/1764885284…

401 items Polled 22 Sep, 15:14 UTC 200

Representation Learning — Google

https://www.google.co.in/alerts/feeds/05832220720342067762/1758013403…

146 items Polled 22 Sep, 15:14 UTC 200

Reinforcement Learning — Google

https://www.google.co.in/alerts/feeds/05832220720342067762/1720175169…

401 items Polled 22 Sep, 15:14 UTC 200

Generative AI — Google

https://www.google.co.in/alerts/feeds/05832220720342067762/7811591585…

401 items Polled 22 Sep, 15:14 UTC 200

Multimodal AI — Google

https://www.google.co.in/alerts/feeds/05832220720342067762/9568555102…

401 items Polled 22 Sep, 15:14 UTC 200

Mechanistic Interpretability — Google

https://www.google.co.in/alerts/feeds/05832220720342067762/8541059511…

33 items Polled 22 Sep, 15:14 UTC 200

RLHF — Google

https://www.google.co.in/alerts/feeds/05832220720342067762/7811591585…

32 items Polled 22 Sep, 15:14 UTC 200

Feeds are configured through the LEARN_FEEDS environment variable, so new sources can be added without a code change. Each poll sends the stored ETag and Last-Modified headers, so an unchanged feed answers 304 and costs the publisher nothing.