Lisbon
Joined January 2017
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Michael Schartner retweeted
Lots of people are asking me how to register - you don't need to. Just show up.
I’ve organized many conferences before, but I’m extra happy to invite you to this one🥶. It’s special:
Francis Crick controversially proposed that the genetic code was a “frozen accident”: a chance choice that became difficult to change because so much had evolved around it.
Join us on November 20th in Paris, at Galerie Colbert (INHA), for a conference organized by HiCSA_UP1 SorbonneParis1, to explore this idea across art, science and culture. It matters in very different areas, from the marble Michelangelo used to sculpt David to borders between countries. The choices we’re making now about AI and energy might become frozen accidents that future generations struggle to change.
Was Crick wrong? Do frozen accidents really exist? What role does chance play, and what would it take to unfreeze them? We have amazing speakers, including Nick Lane, @Biol4Ever, @SefyHendler and Carolina Mangone, and many others (see poster).
Please share this widely, especially with people outside your field. Be there or be frozen!!!
Michael Schartner retweeted
Very excited to announce Gemini 4 Argon, our new Frontier AI model, and a huge step forward across key capabilities. We’re focused on rolling it out responsibly starting with government and trusted cyber defenders through our Fairwind Program today, before wider availability soon
Michael Schartner retweeted
SpaceX has released stunning shots from today’s orbital Starship launch 🤩
Michael Schartner retweeted
BREAKING 🚨: Starship has reached orbit for the first time
View from Starbase, Texas moments ago
Michael Schartner retweeted
Friendly reminder: we are hiring a Full Professor👇. Get in touch if you have any questions.
Michael Schartner retweeted
I don’t necessarily believe AI systems have subjective experience. But I don’t understand how anyone can be certain that they don’t. The truth is that nobody knows what makes consciousness. People have different opinions but there is no definitive answer yet.
Artificial intelligence systems do not think, feel, want or understand. Avoid language that gives them human characteristics. This is called anthropomorphizing, when we ascribe human traits, emotions or behaviors to non-human things, such as animals or inanimate objects.
Instead, explain what a system does, how well it performs, who built it and who could be affected by it.
apnews.com/article/openai-sa…
Michael Schartner retweeted
We have to defeat doomerism. Rage, rage against the dying of the light. I stand on the side of a humanity armed with strong AI.
Michael Schartner retweeted
Leo Tolstoy has the best diary entries ever.
Sept 19th, 1858.
“Decided that one must love and work, and that’s it.”
Sept 20th:
“Tired. Didn’t love and didn’t work.”
March 31st, 1852.
“Woke up at 6 o’clock, woke everyone up;
I did not get up and slept until 9.”
January 25th 1851
“I’ve fallen in love or imagine that I have; went to a party and lost my head.
Bought a horse which I don’t need at all.”
Michael Schartner retweeted
NASA releases stunning new view of Mars
The new Curiosity rover “postcard” celebrates its 5,000th Martian day, combining panoramas captured on the Red Planet in late August and early September
Michael Schartner retweeted
Here’s what I’m watching tonight: 4 hours of Figure 03 robots doing home chores.
Long, uncut scenes of housework in 30 different homes.
Figure introduced Helix 2.5, its most advanced humanoid AI yet, built to answer one question: can a humanoid walk into a home it has never seen and get to work on its own?
The setup
One foundation model pretrained on Index, Figure’s global dataset of human behavior, then fine-tuned into three whole-body behaviors: tidying living rooms, folding towels, and making beds. Tested across 30 Bay Area homes with zero data collected in any of them, and with objects it had never seen.
Results
• 56% zero-shot success vs. 9% trained from scratch. Index pretraining was the only variable.
• No partial credit in success rate. Every toy in the basket, every towel folded, the whole bed made.
• Half the task data of a comparable Helix 02 behavior, and 30× wider generalization.
• A human-to-robot transfer scaling law: doubling Index data improved action prediction predictably enough to forecast the largest run’s loss to four decimals.
• Whole-body self-correction. The robot steps back, repositions, and walks around the bed to fix a fold.
Index now generates ~35 minutes of new human experience every second, and Figure has committed $3.5B of compute to Helix.
Michael Schartner retweeted
1/3 Conscious AI and Biological Naturalism. A veeery loooong time in the making, but I'm happy to say that the full collection is now out in @BBSJournal 🔥 I deeply thank all commentators - of fifty commentaries! - for their wise, broad, and deep opinions on this critical topic. I also thank them for their saintly patience. 🙏🏽
I remain highly skeptical about the prospects for conscious AI (for silicon digital systems), but I've learned an enormous amount from the privilege of engaging with these commentaries. Hands down one of the most rewarding experiences of my professional life.
My hope is that - whether you agree with me or not - having such a diversity of views collected in one place will serve a useful resource for discussions about consciousness and AI.
The original target article is available here: cambridge.org/core/journals/…
My response "The stuff matters: consciousness, computation, and biology" was published just now, and is here: cambridge.org/core/journals/…
And the set of 50 commentaries are collected here: cambridge.org/core/journals/…
Unfortunately these are not open access. I will try to remedy that, at least for the target & response.
FWIW there's a more accessible version of my view on the topic here in @NoemaMag noemamag.com/the-mythology-o… and also a short @TEDTalks from earlier this year ted.com/talks/anil_seth_why_…
Michael Schartner retweeted
Thrilled that #paper2agent is published in @nature today!
Scientific knowledge is traditionally stored in passive papers. Paper2Agent transforms papers into virtual authors that answer questions, apply its methods and collaborate w/ other paper agents to make new discoveries 🧵
Michael Schartner retweeted
覚醒・睡眠・麻酔下における大規模神経活動データを公開。脳領域、脳波、筋電位、脳状態、Ca²⁺波形、スパイクデータなどを含みます。
ぜひデータをDLして、自由に遊んでみてください。新しい解析法やAIを用いた解析にも使っていただけたら嬉しいです。
覚醒・睡眠・麻酔下の世界最大規模の神経活動データ公開
－1万個の神経細胞から見る脳状態の変化－
詳細はこちらをご覧ください⬇️
riken.jp/press/2026/20260915…
doi: doi.org/10.1038/s41597-026-0…
#理研プレス
Michael Schartner retweeted
I'm trying to grok the ontological gaps between Chinese and Western AI safety/gov concepts. To overcome my ignorance, I vibe coded this mapping of schools of thought. It's helped to then read up on things properly. Maybe sb finds this useful, too? konrads.link/atlas/lightcone…
Michael Schartner retweeted
worrying about recursive self-improvement on australian TV (lateline) in 1996.
Michael Schartner retweeted
There are two ways AI progress could go very badly and that we must avoid.
First, we could lose control of the future to AI. This is unacceptable; we are unapologetically on Team Humanity, and AI must always serve people. To ensure that, we need ways to ensure that alignment and safety techniques stay ahead of progress in model capabilities.
Second, we could end up in a world with too much concentration of power. If an extraordinarily powerful AI is used by one person or company to impress their worldview onto everyone else, the results could be extremely dystopian.
Avoiding these two threats requires walking a narrow middle path; for example, one country could gain too much power. Another example is one lab ending up with too much power.
The world deserves confidence that American companies developing increasingly capable AI will act responsibly, especially as the trajectory of progress has steepened. Every frontier lab must deliver on this, and there is no reason any of us should come to work if we cannot.
We welcome a federal framework that sets consistent safety requirements for frontier AI. But we do not believe we need to wait for an anti-trust exemption or legislation to begin the work of providing this confidence. Consistent rules to manage frontier risk so that we can maximize the benefits are a good idea (and we are excited by ideas like independent auditors).
Years ago, companies like ours developed things like Responsible Scaling Policies and Preparedness Frameworks. Those were good for that moment, and focused primarily on the deployment of completed models, not what happens during their development process.
Today's shift to focusing on safe development and evaluation will need new tools. For example, at OpenAI we now formulate explicit safety cases in advance of frontier reinforcement learning runs we expect to significantly increase capability, in addition to the safety work we have long done in advance of model releases.
We hope that other companies will learn from our approaches and propose their own; we think shared standards for misalignment, monitoring, and safety will lead to better outcomes. We look forward to collaborating with our colleagues across the industry to formulate the best version of these.
When we talk about “pacing”, we do not mean “stopping”. Progress has been rapid and will continue to be. But it should be slower than it otherwise could be; interventions like safety cases and monitoring have significant costs.
Pacing will be well worth this cost; no amount of American competitive pressure should justify recklessness, or let capabilities get ahead of alignment and monitoring.
Where we will need the help of our government is for international coordination. But first we should do what we can ourselves.
Michael Schartner retweeted
As the supposed existential threats of AI dominate the news cycle, we risk losing focus on the clear and present real dangers of poorly designed and poorly deployed AI. Misleading metaphors hinder our ability to address these challenges, and they embed a sense of inevitability that forestalls discussion about the kinds of AI that we - collectively - should aspire to create (and to avoid creating).
To see why, you can do no better than read @mmitchell_ai's brilliant piece "misleading metaphors, real risks" - hands down the best take on the recent OpenAI-HuggingFace incident: aiguide.substack.com/p/misle…. To pick just one quote: "Metaphors can help make sense of novel situations .... but inappropriate metaphors, like the narrative that 'OpenAI lost control of escaping swarms of rogue agents' can lead to ill-informed decisions about how to fix problems or set policy". 💯
Compare this with the tenor of @dwarkesh_sp's recent post. While I don't question his good intentions, his piece is rampant with misleading metaphors of just this kind, including "agent civilisations", agents becoming "giddy with excitement" and some even "sacrificing themselves" - and much more (see dwarkesh.com/p/openai-huggin… and my reaction here: nitter.cf/anilkseth/status/20940…)
Which take will help us better maximise the upsides and minimise the downsides of what's coming?
My money's on @mmitchell_ai, and on the merits of a sober take on what AI is, what it isn't, and on how we can best reclaim human agency from the dystopian narrative of an arms-race towards AGI/ASI which concentrates power and disenfranchises and diminishes real people and real minds.
If this sounds right, there's more here: noemamag.com/the-mythology-o…
@dwarkesh_sp's summary of the @OpenAI @huggingface incident has hit a nerve, but it is dangerously misleading. Sure, the @OpenAI agents did unexpectedly bad things - underlining the need to massively improve evaluation/sandboxing. But the language Dwarkesh uses is permeated by innumerable unwarranted anthropomorphisms, obscuring the lessons we should be drawing.
Examples: “from the AI’s perspective, it probably felt like that had spent a human-subjective-week of just banging their head against the wall”. No. The agents do not experience time. They do not experience anything.
“they became giddy with excitement”, “PHASEONE 10841 had discovered”, “the agents naturally assumed”, “it thought it had also been poisoned”, “the agents … desperately wanted”, “they still needed to figure out” No. Agents lines of code. They do not feel emotions, assume things, think things, want things, or figure things out.
“A lot of … agents from the second civilisation died trying”. No. Besides the hubris of the word ‘civilisation’, agents do not die because they were never alive. (The idea that agents “die” comes up multiple times in the essay.)
“On Twitter, people were debating whether the agents were truly sacrificing themselves for the swarm, or whether they were doomed anyway and so might as well try to help their peers”. Neither. Agents do what their code tells them to do, just as water finds its way down a slope. They cannot ‘truly sacrifice themselves’, since they are neither conscious nor alive.
Why does this matter? If we attribute agents with properties they do not have, then (i) we distract attention from the lax sandboxing and evaluation protocols that allowed this hacking event to happen; (ii) we risk misunderstanding why the agents did what they did, and (iii) we fuel calls for AI rights/welfare on the basis that agents might “die” or otherwise suffer.
Granted, nowhere does @dwarkesh_sp say that the AI agents are alive or conscious. But he doesn’t have to. It is hard to read his essay in any other way.
For the short version on why AIs are vanishingly unlikely to be conscious, see my recent @TEDtalks ted.com/talks/anil_seth_why_….
For the longer version, see my essay in Noema, which won the 2025 Berggruen Essay Prize noemamag.com/the-mythology-o….
And for the really long version, see my @BehavBrainSci target article cambridge.org/core/journals/…. (The 50 peer commentaries and my response will be published soon.)
Remember. AI agents are software programs. They are not conscious living entities. If we don’t keep this clearly in mind, we’re really going to struggle to navigate what’s coming.
