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X discussion: Scott Alexander's "Against SURA" criticizes the "stop unilaterally and raise awareness" line, as AI safety is accused of acting like a mass political movement

On October 31, Scott Alexander published "Against SURA" on LessWrong. He uses SURA (Stop Unilaterally + Raise Awareness) for the view that AI companies, their employees and countries should halt AI work on their own and focus on raising awareness, and argues it would hand the lead to companies that do not prioritize alignment and cost the US its bargaining chip with China. He cites AI Futures Project members' survival estimates for scenarios without a global pause, mostly in the 25%-50% range, to push back on 90%+ doom estimates. Blogger jessicat quoted it and said parts of AI safety now behave like a mass political movement with bad epistemics (about 359 likes, 63K views); Bloomberg Odd Lots co-host Joe Weisenthal summed it up as people competing to out-doom each other (about 287 likes, 38K views). This is an opinion debate, not a policy announcement from any organization.

X discussion: Scott Alexander's "Against SURA" criticizes the "stop unilaterally and raise awareness" line, as AI safety is accused of acting like a mass political movement

Key Takeaways

  • Source: Scott Alexander's "Against SURA" on LessWrong, posted 2026-10-31 19:32 UTC; SURA stands for Stop Unilaterally + Raise Awareness
  • AI Futures Project members' survival estimates for three no-global-pause scenarios (C+ / C / D), as cited: Daniel Kokotajlo 40%/20%/10%, Ryan Greenblatt 60%/63%/55%, Eli Lifland 50%/45%/32%, Thomas Larsen 45%/35%/20%, Romeo Dean 40%/35%/20%; the AI forecaster FutureSearch gave 44%
  • He says that if the US unilaterally passed Sanders' "Ban Artificial Superintelligence Act" (endorsed by MIRI), the AI forecaster he asked put the chance of China agreeing to a pause within a year at only 7%, up from 1%
  • jessicat's quote post (Oct 31, 23:01 UTC) has about 359 likes, 28 reposts and 63K views; Joe Weisenthal's quote (Nov 1, 14:57 UTC) has about 287 likes, 33 replies and 38K views
  • Note: the "10-40%" in Weisenthal's post is his paraphrase; the estimates in the essay's table range from 10% to 63%
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Block unveils Dessa: a full-duplex speech model trained from scratch only on human conversation audio, running locally on a MacBook Pro M4 Max

On 2026-10-23 (16:53 UTC) the official @blocks account unveiled Dessa, and Jack Dorsey called it the most authentic full-duplex speech model ever built. The official page block.xyz/dessa says Dessa is a true speech-to-speech model trained only on recordings of human conversation, with no text and no pretrained models. It is full-duplex, so it listens and talks at the same time, cuts in and backchannels naturally, runs faster than real time, and runs locally on a MacBook Pro M4 Max or better. Block says it was trained on a single NVIDIA GB200 NVL72 and learned language from hundreds of times fewer words than LLMs. There is no public API or weights yet; a small group of AI safety researchers is getting early access.

Block unveils Dessa: a full-duplex speech model trained from scratch only on human conversation audio, running locally on a MacBook Pro M4 Max

Key Takeaways

  • Trained only on human conversation audio, from scratch, with no text and no pretrained models (official page)
  • Full-duplex speech-to-speech: listens while talking, cuts in and backchannels, and natively hears and expresses emotion, sarcasm and laughter
  • Inference runs faster than real time and runs locally on a MacBook Pro M4 Max or better
  • Block says training used a single NVIDIA GB200 NVL72 and needed hundreds of times fewer words than LLMs
  • No public API, weights or third-party benchmarks yet; early access is limited to a small group of AI safety researchers
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Altman, Musk, and Hassabis Debate Frontier Pacing Protocol and Voluntary Audit Buffers

Following Dario Amodei safety essay, Sam Altman, Elon Musk, and Demis Hassabis engaged in public dialogues exploring a Frontier Pacing protocol. The proposed voluntary mechanism would trigger a 90-day external security audit buffer whenever next-gen models breach critical capability thresholds.

Key Takeaways

  • Frontier lab leaders explore voluntary 90-day third-party audit buffers for threshold models
  • Sets synchronized circuit breakers for critical cyber-offensive and bio capabilities
  • Reflects profound shift from blind compute scaling to verifiable safety alignment
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DeepMind pilots double-blind evals of a frontier model

DeepMind ran Gemini Flash Lite in a confidential setup so evaluators cannot see weights and Google cannot see prompts. Singapore’s AI Safety Institute is among the partners. No scores published.

Key Takeaways

  • DeepMind ran Gemini Flash Lite in a confidential setup so evaluators cannot see weights and Google cannot see prompts;
  • Singapore’s AI Safety Institute is among the partners;
  • No scores published.
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