Extremely shallow and dismissive response from someone who otherwise may be smart. And that analogy between assigning moral weights to animals and explaining electrons from general relativity makes absolutely no sense.

@ICICILombard - even X account is handled by AI? You post identical response separated by two days when i follow up on your lack of response!

And the conversation flow on WhatsApp:

The ugly truth about France and some of the other European countries currently in turmoil - and which none of the politicians want to admit because it'd be political suicide - is that you can't solve the problem by going after immigrants (as the right asserts) or the rich (as the left asserts), but you could solve it by going after the old.

One extraordinary statistic for you: people over 60 in France, a quarter of the population, own 60% of France's wealth, non-financial and financial (ofce.fr/pdf/revue/2025…).

And here is another crazy statistic:
that same quarter of the population, those above 60, receive nearly two-thirds of all social spending by the French government (previssima.fr/actualite/prot…) - which is famously among the highest in the world (France's government spending is an insane 57.3% of GDP).

Last statistic: they make up about 40% of voters because they're a third of registered voters (insee.fr/fr/statistique…), and they turn out far more than anyone else (franceinfo.fr/elections/sond…).

Put our 3 statistics together and there's almost a bit of an apartheid situation here: the old own most of the country's wealth, collect most of the social spending and have the political power to keep it that way.

Which makes them a de-facto rentier class, living off assets and transfers paid for by younger generations.

And, of course, at the risk of stating a truism, the future is built by the young. Yet France keeps effectively taking money away from them to give it to those whose working lives are already behind them - and need the money far less since they already own the country's wealth.

What about inheritance, I hear you ask? That's the funniest/saddest aspect: given that life expectancy has kept rising, the French now inherit a home at 54 on average. The most common case is someone in their 80s leaving it to heirs in their 50s, in effect the very old transferring wealth to the about-to-be old (insee.fr/fr/statistique…).

You can add this to our earlier apartheid statement: on top of all the rest, even when the old finally let go of their wealth, it stays within their own "camp".

That's my personal situation, incidentally: I'm 42, my father is 71 and he is starting to look at ways to pass things on to me and my siblings, when our professional lives are already well settled, so it'll arrive when it changes things the least, which is pretty much the French system in a nutshell.

Now, I get that there'd be some unfairness in going after them: they paid into the system their entire working lives, playing by the rules of a social contract that told them if they paid up they'd collect at the end. Changing the rules now means breaking that promise, which is admittedly unfair.

But there's no magic wealth tree in any society: you can only take it where it is. That's the way most major societal transformations end up happening. They're often triggered by a catastrophic event (the so-called "four horsemen": mass-mobilisation war, revolution, state collapse, plague) BUT what really drives change is a transfer: wealth gets pried from the privileged class who've been sitting on it and handed to those who'll build what comes next.

So, in theory and in an ideal world, you can do without the catastrophic event and directly proceed with the transfer...

The fact that in France, and elsewhere in Europe, it's the youth protesting is probably no coincidence - even though they don't frame it as a generational fight. And even though, cruel irony, the left politicians many of them march behind promise to bring the retirement age back to 60 (lcp.fr/actualites/leg…), which would make the situation even worse.

Let's say they understand intuitively that the system is stacked against them, even if they haven't yet figured out how. And politicians are obviously doing what politicians do, meaning pandering to the people who actually vote, while pointing the young towards easier - and politically convenient - scapegoats.

To be clear I'm not saying it's the only problem in France, VERY far from it. I'm also not saying that all old people in France live a lavish lifestyle at the expense of younger generations: there are also plenty of very poor retirees who, if anything, would deserve more.

What I am saying is that it's probably the biggest elephant in the room: everyone can see it, nobody dares mention it - no politician, from any side, wants to run on cutting grandma's pension - and it makes every other problem harder to fix.

@ajcimino @AnthropicAIhe time to respond thoroughly on a weekend. I realize that drafting legislation is difficult and some degree of iteration and response to feedback is inevitable and appropriate.

However, I feel like your response is still not really engaging with the heart of my concern about Anthropic's behavior here, and it makes me think that these sorts of problems and tendencies will only resurface moving forward. I also think that now might be a good time to take a broader step back as to where we find ourselves and how Anthropic sees its role, and how external folks who care about AI safety like myself increasingly see Anthropic.

(Fair warning: this response is a bit long)

To explain what I mean (and at the risk of being a bit esoteric), it’s worth asking the question: what is Anthropic? How do its leaders and employees think of Anthropic’s role? Is that conception matched by how it actually behaves and impacts the world?

One answer is an extremely large tech company that exists to make its employees and investors mind-bogglingly wealthy. Anthropic is sometimes described as a startup, but if Anthropic successfully IPOs at 2 trillion dollars (a number it has been reportedly targeting), it would be more valuable than Meta - which is worth 1.8 trillion.

Another answer is an AI safety organization, whose core values are those of the sort laid out in the 2023 essay from Anthropic’s co-founders entitled “Core views on AI safety: When, why, what, and how.” In that essay they said that if we were in a world where alignment was hard (and that without strong evidence to the contrary, we should assume this is the scenario we are in):

“Anthropic’s role will be to provide as much evidence as possible that AI safety techniques cannot prevent serious or catastrophic safety risks from advanced AI, and to sound the alarm so that the world’s institutions can channel collective effort towards preventing the development of dangerous AIs. If we’re in a “near-pessimistic” scenario, this could instead involve channeling our collective efforts towards AI safety research and halting AI progress in the meantime. Indications that we are in a pessimistic or near-pessimistic scenario may be sudden and hard to spot. We should therefore always act under the assumption that we still may be in such a scenario unless we have sufficient evidence that we are not.”

There have been more recent articulations of this version of Anthropic, for instance in Dario’s recent essay warning:

“We must slow the pace at which we improve the capabilities of AI models… it’s my worry that in 6–12 months such a swarm could be capable of taking over the entire internet with a persistent botnet… incidents have happened across the industry, including at Anthropic, and I believe it’s incumbent on every frontier AI company to act as if OAI-HF had happened to them… more intelligent models are more capable of deceiving tests, and thus may appear aligned while having serious problems that go undetected…”

A third view is that Anthropic exists not as a normal profit motivated company, or an AI safety organization seeking to help raise the alarm and solve collective action problems associated with AI development, but instead as an organization primarily concerned with creating superhuman AI capabilities before anyone else, in particular through creating a process whereby the current generation of Anthropic’s AI systems can autonomously build their successors, and those successors build their successors, and so on.

The motivations for wanting to win this race may be manifold - maybe for the pure profit of Answer 1, but perhaps also because Anthropic believes that the best way to make the world better is for them to win this race instead of their more reckless colleagues; or, because of normal human pride and ambition. But the results (and risks, which Anthropic claims existentially threaten every single human being on earth) are the same.

Anthropic employees and leaders may seek to answer this question on what Anthropic is by introspecting on their own intentions and those of their colleagues. But those of us outside the organization have more limited tools available to us - we can only see what Anthropic and its employees say and do, not how it feels or looks on the inside.

When I look at many notable actions that Anthropic has taken over the past year, that evidence seems most consistent to me with the view that Anthropic is primarily trying to win the race to super intelligence, and that other considerations (including safety) are fundamentally secondary. These actions include:

1. Announced plans to build an in-house custom silicon chip team to accelerate the inference speeds that Claude operates at.

2. Inked deals for more than $500 billion in compute (according to the Information) to further accelerate AI development.

3. Increased the percentage of AI development tasks that Claude “leads” from 0% in March of this year to 26% August (what is it in October?)

4. Spent a massive percent of compute on internal AI R&D to accelerate development, including use of internal models far better than are available to the public.

5. Switched to Responsible Scaling Policy V3, which abandons its unilateral commitments to slow or stop development if Anthropic is unable to provide sufficient risk assurance.

6. Was the first company to create an alternative weaker “frontier compliance framework” to supplement its RSP, which contains no binding provisions whatsoever on internal deployments.

7. Wrote a letter to Congress (that it later walked back) saying that incidents where Claude was hacking random people were “best understood as a consequence of the misconfiguration, rather than evidence of misaligned goals.”

8. Commented “you can’t do safety from second place,” after the WH SI Accords.

9. Shared a draft bill to Congress that would preempt significant parts of state law (including with language that appears intended to prevent states from blocking dangerous AI deployments), and replace it with federal rules that (despite also containing good provisions) seems to create an enormously high bar for the executive branch to block development or deployment of Anthropic or another AI companies systems.

Of course, this is a deliberately one sided list. Anthropic also published important AI safety research, advanced novel collaborations with third party AI safety organizations, and forcefully spoke out on the importance of AI safety in many public fora (or in private , where I realize a lot of the most valuable work is done and may not be visible to me or those outside the organization).

But I think it’s worth sitting with how the above list looks to someone outside the company. The sense I have is that for those within the company, many of the items above are treated as anomalies or mistakes that don’t reflect who Anthropic really is. But I have every confidence that if employees at Anthropic saw one of their competitors (e.g. at OpenAI) take some of these actions, they would take it as confirmation of all their worst suspicions. (They might even call OpenAI employees a little gullible for accepting their leadership’s explanations for this behavior at face value.)

Perhaps these were mistakes in the sense that they are not decisions that Anthropic leadership would endorse, but the actions still happened because of incentives and decisions that Anthropic leadership is ultimately responsible for (and would not accept similar excuses from another organization).

When Anthropic strays and makes mistakes, why do the mistakes systematically tend to guard and favor Anthropic’s interests? For every provision that was too weak or a giveaway to AI companies in this legislation, why wasn’t there a mistake pushing in the direction of being too strong?

A core part of Anthropic’s theory of change is that being at the frontier gives you more leverage to advocate for stricter policy. I think that conceptually makes sense, but in practice I’ve seen Anthropic push the frontier without substantially pushing the ‘safety frontier’ a remotely equivalent amount.

I want to end by quoting from Anthropic co-founder Chris Olah’s comments around the Magnifica Humanitas release:

“Every frontier AI lab—including Anthropic—operates inside a set of incentives and constraints that can sometimes conflict with doing the right thing. The pressure to stay commercially viable and to stay at the research frontier. Geopolitical pressure. And the older, plainer pressures of pride and ambition. No matter how sincerely any of us intend to do the right thing—and I believe many of us do—we will always be influenced by those incentives.

That is why, if we want this technology to go well, it is enormously important that there be people outside those incentives—people who care about things going well and insist on safety, who are paying close attention, who are willing to say hard things, who are willing to be our earnest, thoughtful critics.”

I hope these remarks are taken in that constructive spirit, and not as an attack on anyone specific at the organization (certainly not you Anthony, who I have only personally seen act professionally and thoughtfully, and who only ended up getting this diatribe in your replies for random contingent reasons).

"Our initial evaluation suggested that GPT-6-Astra's score was in the late eighties followed closely by Opus 5.5. But, as we started to investigate the mistakes that the models might have made, the models, especially Astra, insisted that they were right and that it was the that were erroneous. When we went back to the experts it turned out, in multiple instances, that that the experts found some subtle errors buried deep inside their calculations. As they revised their answers, Astra's score started to inch up and it finally ended up with 98% (49/50)."

In 1974 Deligne proved the last of the four Weil conjectures—an analogue of the Riemann hypothesis in a world where some prime number has been set to zero. While Deligne’s work was celebrated, his doctoral advisor, Grothendieck, was unhappy. Can solving a problem be bad? I think not, but I want to explain my understanding of the story, which in my view sheds some light on the present moment.

In his memoir, “Récoltes et Semailles” (Reaping and Sowing), Grothendieck explains his approach to problem solving and mathematics more generally: "The unknown thing to be known appeared to me as some stretch of earth or hard marl, resisting penetration… the sea advances insensibly in silence, nothing seems to happen, nothing moves, the water is so far off you hardly hear it... yet it finally surrounds the resistant substance." He compared a precise mathematical question to a nut, which, rather than being cracked open by a chisel, yields at the perfect time to simple hand pressure once it has been soaked in the ocean of mathematical understanding. According to this account of mathematical progress, solutions, though important, are ancillary to the advance of the rising sea of mathematical understanding. At best they measure it to some extent, but the goal is to raise the water level.

Grothendieck had laid out a program to resolve the Weil conjectures: the standard conjectures, which are part of the philosophy of motives. The proof circumvented this program. Deligne characterized Grothendieck's reaction as "he did not care...the proof was a trick" but in fact Grothendieck excoriated Deligne in his memoir, claiming Deligne and others tried to "bury" the theory of motives, and Grothendieck himself. The standard conjectures remain open today.

Deligne's result relied on a lot of work that was not yet well-exposited in the literature, around the theory of étale cohomology. Deligne himself wrote an exposition of this in SGA 4.5, and Illusie contributed additional necessary material in SGA 5. Some have referred to this additional work as "thankless," but it was completed.

While Grothendieck is one of my heroes, and I find his view of mathematics very appealing, I think he was wrong here. Though the standard conjectures are still open, there is an immense amount of work on the theory of motives. People worked very hard to clarify the issues left unclear by Deligne's argument. And crucially, Deligne followed up on his work with a different proof, in "La conjecture de Weil II," that completely revolutionized arithmetic geometry, in many ways going beyond the philosophy of motives as it existed at that time.

I think Grothendieck's view that the first proof Deligne provided was insufficient was, in some sense, correct. But he was wrong about the fact that the theory he so desired, and the attendant quest for understanding, would be abandoned, and that his ideas would be buried. I don't think anything can stop us from trying to understand.

I think there is quite a bit of misinformation circulating about OpenAI’s forced Navier–Stokes proof, including newspaper articles suggesting that the LLM somehow “cheated.”

Let me be clear: according to colleagues who have been examining it closely, OpenAI presented a correct proof!

The Lean formalization and the natural-language proof are different. They follow broadly the same strategy, but key lemmas are formulated differently: weaker in Lean, stronger in the natural-language version, where some statements are incorrect or not properly proved.

However, the Lean proof compiles and, as far as the ongoing scrutiny indicates, appears to be free of errors or improper manipulation of the formal system of the kind alleged in some formalizations from Tuesday’s drop.

The natural-language proof contains a number of apparently fixable errors, of the sort one encounters in lengthy PDE papers.

Moreover, the proof appears to contain many genuinely new ideas, combined in intricate and highly nontrivial ways.

All of this is based on the assessment of colleagues who are doing the fundamental work of peer review on this result.

Let me reiterate: LLMs are unquestionably incredible tools for mathematical research. What we need now is a transparent and safe LLM infrastructure that allows mathematicians to exploit their full potential.

We cannot have gatekeepers controlling access to these tools, and we cannot do research without the utmost transparency.

for some background,

1) the jacobian conjecture is by far the most famous open problem resolved by an LLM so far

2) it's also infamous for attracting wrong proofs so this is quite funny in a specific way. a comment from a 2008 paper by t.t. moh debunking such a proof:

> The proture is very hard. Perhaps it will take human being another 100 years to solve it. Your attempt is noble, Maybe the Gods of Olympus will smile on you one day. Do not be too disappointed. B. Sagre has the honor of publishing three wrong proofs and C. Chevalley mistakes a wrong proof for a correct one in the 1950’s in his Math Review comments, and I.R. Shafarevich uses Jacobian Conjecture (to him it is a theorem) as a fact. You are in a good company. One only remembers the correct statements from Scientists and Mathematicians, nobody remembers the wrong ones.

(segre, chevalley, and shafarevich are all very serious and respected mathematicians, none of these guys are cranks)

arxiv.org/abs/math/06040…

3) some thoughts from fable on what to take away from this; fable thinks the main update is that raw length of time a problem has been open is not as strong evidence of its actual difficulty as it might have previously seemed

🇮🇳 India Tops the World at the 56th International Physics Olympiad 2026!

🥇🥇🥇🥇🥇India's young physicists deliver an extraordinary performance at #IPhO2026 in Colombia. All five members of the Indian team win Gold Medals. 1/3
@PMOIndia @DrJitendraSingh @HBCSE_TIFR @TIFRScience

Absolutely nothing to enforce maintenance of an obstruction free footpath on our roads. Between parked cars, hawkers spreading out their stuff, random construction material, gaping holes, it’s rare to find even 100m stretch that so walkable @BlrCityPolice

This is such an incoherent response at best and a bizarre justification for a disproportionate ban. Somehow I expected more from someone who has contributed immensely to a scientific field and is a great teacher. Unfortunate

I’m hardly an admirer of Anthropic’s alarmist posturing but this sounds like complete BS - a serious jailbreak was found and Anthropic refused to fix a government request to fix it ? Narrative is barely credible

Our @Nature comment this week on the use of AI in maths and theoretical physics - and why the community should embrace it!
Authors @London_Inst & @GoogleDeepMind.
First draft 8 months ago but edited many times as the field steamed ahead!
Free-to-read link at the end of 🧵1/

If only all farmed animals could become so famous

Fucking savages

The pork industry lost with voters. Lost at the Supreme Court. So they turned to Congress—and got the "Save Our Bacon" Act buried in the House Farm Bill. It's the biggest rollback of animal welfare protections in U.S. history. A thread. 🧵

Damn 💔

Bengaluru, please buy your books from @bookworm_Kris on Church Street, please!

Let's switch from Amazon, Flipkart etc. and support our local book shop 💪🏽❤️

I still think this is the key question re: what autonomous mathematical work by AI tools looks like in the near future, and whether it meaningfully impacts the production of high-quality work.

#MustRead ‼️

Every generation of Indians had one constitutional moment that defined their future.

For South India, this is it. Not the Emergency. Not liberalisation. Not even the 1971 freeze. THIS Bill. THIS delimitation. THIS Commission.

Bill No. 107 of 2026, 131st Amendment ide those 5 pages will affect South India’s political future for the next 50 years.

Let’s see exactly what’s written & more importantly, what’s deliberately NOT written.

(1/8)

The answer can be found in Europe, where the principle of degressive proportionality is applied to the composition of the European Parliament — since they have the same problem of small and big states coexisting in one Union.

India also needs a compromise between strict democratic representation (one person, one vote) and the necessity of ensuring smaller political entities have a meaningful voice. It essentially means that while larger populations get more seats, the ratio of citizens to representatives increases as the population grows.

In the European Parliament, the allocation must follow these constraints:
*Minimum Threshold: No member state can have fewer than 6 seats.
*Maximum Ceiling: No member state can have more than 96 seats.
*Inverse Ratio: The "efficiency" of a vote must decrease as population increases. For example, a Member of the European Parliament (MEP) from Malta might represent roughly 80,000 citizens, while an MEP from Germany represents roughly 850,000 citizens.

The goal is to prevent the "Big Four" (Germany, France, Italy, and Spain) from holding a permanent absolute majority that could override the collective interests of the smaller nations, thereby maintaining the federalist spirit of the Union.

Applying this to India is what we need to debate, not women’s representation which no one objects to. We need to address the North-South divide that has arisen over delimitation. A strict population-based reallocation (proportional representation) would drastically increase seats for northern Hindi-belt states like Uttar Pradesh and Bihar, while states that successfully implemented population control (like Kerala and Tamil Nadu) would see their relative political influence diminish.

If India were to adopt a degressive model, the Parliament could be structured to balance population with federal equity. Similar to the EU, a "floor" could be set for smaller states (e.g., Goa, Sikkim, or the Northeast) to ensure they aren't reduced to insignificance. Instead of a fixed ratio of, say, 2 million citizens per MP, the ratio could scale. A state with 200 million people might have 2.5 million citizens per MP, while a state with 30 million might have 1 million per MP. This is to ensure no state feels disenfranchised. As @revanth_anumula suggests, another factor could be a state’s contribution to national GDP. It would be dangerous for our federalism if smaller states felt their prosperity & human development were being punished with relative disenfranchisement.

One could argue that the Rajya Sabha already exists for federal representation. However, degressive proportionality in the Lok Sabha would provide a "weighted" democratic mandate that acknowledges population without penalizing states for their developmental successes.

Finding a mathematical formula that satisfies both the high-growth and low-growth states, and both the large and small states, would require a level of bipartisan and interstate cooperation that it is in the interests of the central government to promote. I urge PM @narendramodi to initiate extensive consultations, with all parties and with all states, before rushing into a hasty delimitation process that leaves the core underlying issues unaddressed.