1. 22 Sep 2026

    How Agentic AI Is Making Mobile Apps Easier to Attack

    Agentic AI describes systems capable of independent planning and execution, refining their strategy through continuous feedback loops until the ...

    zimperium.com ↗
  2. 21 Sep 2026

    How Do We Talk About LLMs? - The Good Men Project

    The language we use to describe large language models shapes how we understand their capabilities, limitations, risks, and role in society.

    goodmenproject.com ↗
  3. 21 Sep 2026

    Intent injection attacks are a new worry for AI-native 6G networks - Help Net Security

    They evaluated their detectors on 1,100 intents they constructed, partly with a large language model's help, so the reported figures describe ...

    www.helpnetsecurity.com ↗
  4. 20 Sep 2026

    ASD says prompt injection in AI cannot be fixed - iTnews

    ASD's Agentic AI harnesses: the layer above the model, uses harness to describe every component of an agentic system other than the large language ...

    www.itnews.com.au ↗
  5. 19 Sep 2026

    Open letter to US President Donald Trump: Carpe diem - opinion

    The same Anthropic report describes Iranian state-aligned actors employing AI in influence operations, surveillance, and what they themselves called “ ...

    www.jpost.com ↗
  6. 19 Sep 2026

    RobCo Highlights Reinforcement Learning Approach in Physical AI Robotics - TipRanks

    ... reinforcement learning-based approaches. The post describes how engineers use extensive simulation, feedback, and iterative training to build ...

    www.tipranks.com ↗
  7. 18 Sep 2026

    ComfyUI NSFW Guide Best AI Image Platforms and Nodes {vlZzzRl}

    ComfyUI NSFW generally describes ComfyUI-based workflows and node packs that generate or modify adult-oriented imagery using machine learning.

    www.uv.es ↗
  8. 18 Sep 2026

    ComfyUI NSFW Guide Best AI Image Platforms and Nodes {vlZzzRl}

    ComfyUI NSFW generally describes ComfyUI-based workflows and node packs that generate or modify adult-oriented imagery using machine learning.

    www.uv.es ↗
  9. 18 Sep 2026

    Why Studios Are Finally Embracing Generative Video|a16z - BigGo Finance

    fal engineers describe post-training the open-weight Minimax H3 video model with reinforcement learning and kernel-level optimization to reach ...

    finance.biggo.com ↗
  10. 18 Sep 2026

    Air Force taps DSD Laboratories for logistics IT, DevSecOps and agentic AI

    The contract is notable for its explicit reference to agentic AI sustainment, although the Air Force award announcement does not describe how ...

    www.militaryaerospace.com ↗
  11. 18 Sep 2026

    Measurements for understanding the pace of AI development inside frontier labs - Anthropic

    ... AI agents take on Anthropic's systems. Here, we consider three different metrics: coverage, which describes the share of an agent's actions that ...

    www.anthropic.com ↗
  12. 15 Sep 2026

    What are AI agents, and how do they actually work - Quartz

    The term describes a system built around a large language model that can perceive a task and form a plan. It invokes tools such as a code ...

    qz.com ↗
  13. 14 Sep 2026

    Emily Bender maps four ways AI research dehumanizes people | AI Weekly

    There is the 'computational metaphor,' which she describes as framing brains as computers and comparing child language acquisition to machine learning ...

    aiweekly.co ↗
  14. 11 Sep 2026

    SenseNova-U1.5 unifies 8B multimodal model with native 4K output | AI Weekly

    SenseNova has released SenseNova-U1.5, an 8.2B-parameter model its authors describe as an "8B-MoT native unified multimodal model that understands ...

    aiweekly.co ↗
  15. 19 Aug 2026

    How agent-native video representations advance AVA Encoding - AI CERTs

    Developers describe this approach as representation learning driven by reconstruction fidelity. Meanwhile, textual gradients supply clear optimization ...

    www.aicerts.ai ↗
Sources

Where this comes from

Artificial Intelligence — Google

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

401 items Polled 23 Sep, 04:22 UTC 200

Agentic AI — Google

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

401 items Polled 23 Sep, 04:22 UTC 200

AI Agents — Google

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

401 items Polled 23 Sep, 04:22 UTC 200

Data Science — Google

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

401 items Polled 23 Sep, 04:22 UTC 200

Large Language Model — Google

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

401 items Polled 23 Sep, 04:22 UTC 200

Machine Learning — Google

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

401 items Polled 23 Sep, 04:22 UTC 200

Deep Learning — Google

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

401 items Polled 23 Sep, 04:22 UTC 200

LLMs Alignment — Google

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

45 items Polled 23 Sep, 04:22 UTC 200

AI Alignment — Google

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

401 items Polled 23 Sep, 04:22 UTC 200

Representation Learning — Google

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

148 items Polled 23 Sep, 04:22 UTC 200

Reinforcement Learning — Google

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

401 items Polled 23 Sep, 04:22 UTC 200

Generative AI — Google

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

401 items Polled 23 Sep, 04:22 UTC 200

Multimodal AI — Google

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

401 items Polled 23 Sep, 04:22 UTC 200

Mechanistic Interpretability — Google

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

34 items Polled 23 Sep, 04:22 UTC 200

RLHF — Google

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

36 items Polled 23 Sep, 04:22 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.