1. 14 Sep 2026

    'It Is the Time to Go Bold': Alex Bores on New York's Role in…

    AB: There's a split among people who advocate for AI safety on whether you believe AI alignment could be solved, whether you could safely build it at ...

    nysfocus.com ↗
  2. 14 Sep 2026

    Elon survey finds most Americans believe human purpose is in peril in the 'age of AI'

    15% who do have confidence. A double-edged sword for users: Many large language models (LLM) users admitted to worrisome personal behavioral shifts: ...

    www.elon.edu ↗
  3. 14 Sep 2026

    Artificial Intelligence: Alignment 2.0 - A Last Chance To Change The Game | Crowdfund Insider

    His own alignment lead backed him the same day. Evan Hubinger: “Jacob is correct here – we really do earnestly believe AI could kill all humans! I ...

    www.crowdfundinsider.com ↗
  4. 13 Sep 2026

    Why AI researchers keep building something they think will kill humans - Business Insider

    "We really do earnestly believe AI could kill all humans! I personally think it is >10% within the next decade," Evan Hubinger, alignment science lead ...

    www.businessinsider.com ↗
  5. 12 Sep 2026

    If AI kills us, don't blame the machine - Salon.com

    OpenAI data scientist Evan Hubinger backed Coxon's story. “We really do earnestly believe AI could kill all humans! I personally think it is >10 ...

    www.salon.com ↗
  6. 12 Sep 2026

    Nvidia CEO Jensen Huang Believes Agentic AI Will Soon Become the Norm in the Workplace

    Artificial intelligence (AI) has come on fast and furious. Just four years ago, it felt like people were trying their first large language model (LLM) ...

    www.theglobeandmail.com ↗
  7. 12 Sep 2026

    Congress must not waste the AI policy window - Transformer | Substack

    Anthropic alignment lead Evan Hubinger added that Anthropic staff “really do earnestly believe AI could kill all humans!” The posts quickly went viral ...

    www.transformernews.ai ↗
  8. 11 Sep 2026

    The promise and peril of AI coming at us fast | Opinion - South Bend Tribune

    “[W]e really do earnestly believe AI could kill all humans!” Evan Hubinger, who works at Anthropic on developing AI systems that align with human ...

    www.southbendtribune.com ↗
  9. 11 Sep 2026

    Opinion | This Is Really Bad - The New York Times

    Evan Hubinger, Anthropic's lead for alignment science, soon responded. “Jacob is correct here — we really do earnestly believe A.I. could kill all ...

    www.nytimes.com ↗
  10. 11 Sep 2026

    Researchers fear there's a chance AI could kill us all. Here's how experts say that might play out.

    ... AI earnestly believe that it could kill us all by the end of the decade." Evan Hubinger, who leads Anthropic's alignment stress-testing team ...

    www.businessinsider.com ↗
  11. 10 Sep 2026

    Responsible AI Where Innovation Meets Oversight - William Blair

    We believe this evolving landscape creates both risk and opportunity. Companies that proactively align with emerging regulatory expectations are ...

    www.williamblair.com ↗
  12. 10 Sep 2026

    Few dispute researcher's warning that AI poses threat to human life - WCIV

    I believe Anthropic is trying its best, but we do not yet have a plan to solve alignment for superintelligence and are not clearly on track to." In a ...

    abcnews4.com ↗
  13. 10 Sep 2026

    AI & Tech Brief: The Coxon effect - The Washington Post

    “I believe Anthropic is trying its best, but we do not yet have a plan to solve alignment for superintelligence and are not clearly on track to.” The ...

    www.washingtonpost.com ↗
  14. 24 Aug 2026

    The remarkably human task of giving AI 'good enough' taste - Fast Company

    ... (RLHF), a process where a panel of experienced humans provide feedback ... RLHF and other types of post-training. Huffman says he believes ...

    www.fastcompany.com ↗
Sources

Where this comes from

Artificial Intelligence — Google

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

401 items Polled 21 Sep, 01:48 UTC 200

Agentic AI — Google

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

401 items Polled 21 Sep, 01:48 UTC 200

AI Agents — Google

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

401 items Polled 21 Sep, 01:48 UTC 200

Data Science — Google

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

401 items Polled 21 Sep, 01:48 UTC 200

Large Language Model — Google

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

401 items Polled 21 Sep, 01:48 UTC 200

Machine Learning — Google

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

401 items Polled 21 Sep, 01:48 UTC 200

Deep Learning — Google

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

401 items Polled 21 Sep, 01:48 UTC 200

LLMs Alignment — Google

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

45 items Polled 21 Sep, 01:48 UTC 200

AI Alignment — Google

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

401 items Polled 21 Sep, 01:48 UTC 200

Representation Learning — Google

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

138 items Polled 21 Sep, 01:48 UTC 200

Reinforcement Learning — Google

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

401 items Polled 21 Sep, 01:48 UTC 200

Generative AI — Google

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

401 items Polled 21 Sep, 01:48 UTC 200

Multimodal AI — Google

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

401 items Polled 21 Sep, 01:48 UTC 200

Mechanistic Interpretability — Google

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

33 items Polled 21 Sep, 01:48 UTC 200

RLHF — Google

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

27 items Polled 21 Sep, 01:48 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.