There’s no point going any further. De-radicalize yourself and start functioning journals.sagepub.com/doi/pdf… – at Amsterdam, The Netherlands
curious corn, gilded cage retweeted
Dusting off this tweet from April because this gap in shared understanding of LLM capability is *widening*. It's now less "two groups of people speaking past each other" and more a sharp funnel.
- Napkin math somewhere around 6B people (~75% of the population) have barely come in contact with LLMs at all.
- Around 1-2B (~20%) are casual and infrequent users of free-tier ChatGPT-like products. This group sees derpy chatbots and treats them a bit like a better Google search, a writing aid, or etc. Maybe an agent tries to book you a flight. I have non-tech friends who (reasonably, imo) say they have not much use for it at all. Even many professionals outside of math&code are in this tier. For example, execs and many other functions spend a lot of their time talking to other people, so while they understand what is happening intellectually, it is still second-hand and a bit abstract.
- Now we get to professional use of frontier-grade LLMs in math&code. Somewhere around 20M people (0.2%) see first-hand that large, complex projects that used to take them weeks/months can now be completed by agents with a prompt. Building apps, copying apps, translating apps, decompiling apps from binaries... This has all happened very quickly and recently - less than 1 year ago, I was writing code manually by hand, typing memorized computer code commands into a code editor character by character, occasionally pressing Tab to autocomplete a little chunk of code.
- And finally we get to the ~5,000 people (~0.00006%) with access to frontier-grade systems internally. The external world has seen the preview. It looks like swarms of thousands of agents collaborating over weeks on software mega projects: minting zero days, running cyber attacks and defenses at machine speeds, discovering new science, advancing the frontier of mathematics. Things that would have taken top professionals in the industry years of work. Meanwhile, human review and comprehension are starting to fall behind. For example, people are still involved in the "archeology" of the OpenAI-HF incident from many months ago. Mathematicians may be poring over the 722 manuscripts on frontier mathematics for a while.
The funnel is driven by a combination of factors:
1. The impact scales with ambition, problem size, and horizon. A question with a paragraph answer barely stresses the system. You need a reservoir of big, difficult problems that you really care about. This aspect drives the consumer / professional dimension of the funnel.
2. The jaggedness of the system (which I have written about a lot separately). Capability peaks in domains that are digital, verifiable and economically valuable. This is because LLM capability emerges from reinforcement learning on verifiable rewards on a curated environment mixture driven by revenue potential. This aspect primarily drives the area (e.g. math&code) dimension of the funnel.
3. Access. Free-tier, paid-tier, internal.
So this is the weirdness of the moment. The general public has mostly not interacted with these systems. When they have, it looks like a derpy chatbot. The majority of professionals still see only a modest uplift. And a small sliver of professionals are experiencing the vertigo of the curve going vertical. And it is all happening at the same time.
Judging by my tl there is a growing gap in understanding of AI capability.
The first issue I think is around recency and tier of use. I think a lot of people tried the free tier of ChatGPT somewhere last year and allowed it to inform their views on AI a little too much. This is a group of reactions laughing at various quirks of the models, hallucinations, etc. Yes I also saw the viral videos of OpenAI's Advanced Voice mode fumbling simple queries like "should I drive or walk to the carwash". The thing is that these free and old/deprecated models don't reflect the capability in the latest round of state of the art agentic models of this year, especially OpenAI Codex and Claude Code.
But that brings me to the second issue. Even if people paid $200/month to use the state of the art models, a lot of the capabilities are relatively "peaky" in highly technical areas. Typical queries around search, writing, advice, etc. are *not* the domain that has made the most noticeable and dramatic strides in capability. Partly, this is due to the technical details of reinforcement learning and its use of verifiable rewards. But partly, it's also because these use cases are not sufficiently prioritized by the companies in their hillclimbing because they don't lead to as much $$$ value. The goldmines are elsewhere, and the focus comes along.
So that brings me to the second group of people, who *both* 1) pay for and use the state of the art frontier agentic models (OpenAI Codex / Claude Code) and 2) do so professionally in technical domains like programming, math and research. This group of people is subject to the highest amount of "AI Psychosis" because the recent improvements in these domains as of this year have been nothing short of staggering. When you hand a computer terminal to one of these models, you can now watch them melt programming problems that you'd normally expect to take days/weeks of work. It's this second group of people that assigns a much greater gravity to the capabilities, their slope, and various cyber-related repercussions.
TLDR the people in these two groups are speaking past each other. It really is simultaneously the case that OpenAI's free and I think slightly orphaned (?) "Advanced Voice Mode" will fumble the dumbest questions in your Instagram's reels and *at the same time*, OpenAI's highest-tier and paid Codex model will go off for 1 hour to coherently restructure an entire code base, or find and exploit vulnerabilities in computer systems. This part really works and has made dramatic strides because 2 properties: 1) these domains offer explicit reward functions that are verifiable meaning they are easily amenable to reinforcement learning training (e.g. unit tests passed yes or no, in contrast to writing, which is much harder to explicitly judge), but also 2) they are a lot more valuable in b2b settings, meaning that the biggest fraction of the team is focused on improving them. So here we are.
curious corn, gilded cage retweeted
Replying to @hymage
Un centinaio di super-ricchi i quali, piuttosto che contribuire al benessere sociale del loro paese con una contribuzione che non modificherebbe il loro status di super ricchi, preferiscono andarsene a conferma, se ce ne fosse stato bisogno, dei pezzi di merda che sono.
curious corn, gilded cage retweeted
11 years after launch, more witchers are now walking the Path across the Continent than ever before.
Seeing so many of you set out on this journey for the very first time, or relive it once more, means the world to us.
Thank you for putting your trust in us, all these years later. ❤️

ALT Stream graph shows numbers of players over time for The Witcher 3: Wild Hunt. The graph spikes at launch in 2015, in 2016, in 2020, in 2022, and in 2023, but the peak comes upon Remastered's launch in 2026. Numbers across the top represent the number of current players, the 24-hour peak, and the all-time peak, all at 119,852.
curious corn, gilded cage retweeted
Reminder, The Witcher 3: Wild Hunt — Remastered releases tomorrow!
The Witcher 3 — Remastered: Meditation
curious corn, gilded cage retweeted
The agents escaped the sandbox again
Meanwhile the agents' owners:
This is what the forecasts are for. @Betar_USA shows up at the flagged protests, films the crowd, and sends the names to Israel's Interior Ministry:
American Jews who support Palestine get banned from Israel, and deported if they're already there.
Israel is publishing the coordinates, dates and exact local times of public protests in other countries.
The J-SOC reports appear on the Ministry for Diaspora Affairs website as part of a wider effort to protect Israel’s international image.
Here are 2,000 forecast entries.
curious corn, gilded cage retweeted
Replying to @clashreport
All Putin bitches in the west sing the same song - its cheaper for Putin to buy puppets than fighting a war ..
curious corn, gilded cage retweeted
Replying to @clashreport
I don't understand ordinary people who vote for the Right. I understand the Oligarchs and Corporations that they are comfortable with a right-wing government, but they won't address employee rights or housing affordability. All they know how to do is feed people hatred.
curious corn, gilded cage retweeted
Looks like various large companies will be taking delivery of a new @Tesla Semi tomorrow, including DHL, PepsiCo and US Foods. Each one of these companies have put in large orders.
Tesla Semi Pre-Reveal Revealed!
Excited to share this segment of the drone flight one day prior to the Tesla Semi Reveal event.
They have added branding to several Tesla new generation semis.
Including:
Pepsico
US Foods
Einride
LTS
Nevoya
OK Produce
ABF Freight
DHL
WattEV
IMC Logistics
HMD
Some of these we knew about and some are previously unknown.
@tesla_semi
@danWpriestley
curious corn, gilded cage retweeted
Starlink laser terminals.
Imagine this thing locking onto a target the size of a dinner plate, 4,000 km away, while both ends are moving at orbital speed.
curious corn, gilded cage retweeted
"The children will grow up".
This was also the argument that Nazi officials gave, during the Nuremberg Trials, to justify why they had killed children during the Holocaust.
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curious corn, gilded cage retweeted
Replying to @matteopelleg
art of "I doubt China will give any f*ck"... and given how the US are treating their allies now, likely many others will do the same, since the US restricted their access to "advanced frontier models"
curious corn, gilded cage retweeted
How to kill open source models in 3 simple steps:
- Create panic about frontier models.
- Have the biggest AI companies help write the “safety” rules. ← WE’RE HERE
- Make those rules so burdensome that open source can’t compete.
Art of the deal.
curious corn, gilded cage retweeted
Le “armi letali” con cui i bambini palestinesi non possono più giocare per decisione di Israele, volano nel cielo del Lido, davanti al Palazzo del Cinema della Mostra di Venezia, dove la bandiera palestinese non può essere issata per decisione dell’Italia.
#aquiloniperGaza 🪁🇵🇸
curious corn, gilded cage retweeted
Il Ministro israeliano della Protezione dell'Ambiente Idit Silman, ora ospite in Italia, discute con bengvir su dove piazzare i coccodrilli fuori dalla prigione di Ketziot.
Lei dice che i coccodrilli devono essere trattati meglio dei prigionieri, ovviamente.
#IsraelGenocidaires
curious corn, gilded cage retweeted
E, dopo le quotidiane “escursioni”, tutti insieme a fare festa, ballare e cantare a casa dei palestinesi, chè mica è vero che i criminali di IDF e i coloni terroristi lavorano insieme.
#IsraelisATerroristOrganization
#israeliisevil
Soldati di IDF di scorta a coloni terroristi in “escursione” nelle terre dei palestinesi vicino a Jenin, sparano ai residenti colpendo un uomo.
#IsraelGenocidaires
#IsraelisATerroristOrganization
#israelisevil
curious corn, gilded cage retweeted
Venticinque medaglie Fields hanno firmato lo stesso documento. Non capita quasi mai. E non l'hanno firmato per dire che l'AI non sa fare matematica: l'hanno firmato perché sa farla.
Il passaggio chiave della dichiarazione è questo, e vale rileggerlo due volte:
"Risolvere problemi è soltanto uno strumento e un'approssimazione per raggiungere l'obiettivo primario, che è la comprensione concettuale. Dimenticarlo nel mondo dell'AI può trasformare lo strumento contro l'obiettivo."
Tutti misurano quanti problemi l'AI risolve. Il vincolo è che risolvere non è capire.
Il meccanismo è lo stesso che vedo ogni volta che un settore si innamora di una metrica.
Un problema famoso, prendiamo come esempio Riemann, Navier-Stokes, un Millennium Prize non valeva per la risposta. Valeva come strumento di misura: se qualcuno lo risolveva, era il segno che erano nati metodi nuovi. Poi partiva il processo lento, quindi, seminari, discussioni, semplificazioni, un libro di testo leggibile da uno studente del terzo anno. Dopo trent'anni quel metodo finiva dentro un algoritmo di compressione o un protocollo crittografico.
Il problema era il termometro, non la febbre.
Quando un'azienda AI usa quel termometro come benchmark di prodotto, succede esattamente la cosa che i matematici descrivono: la produzione di massa di enunciati "vero/falso" a ritmo crescente può distruggere terreno fertile invece di dargli vita. Si ottimizza il proxy e si perde la cosa che il proxy misurava.
È il problema di Goodhart, applicato non a un'azienda ma a una disciplina intera. E arriva con due danni collaterali concreti che la dichiarazione nomina senza giri di parole:
1. Atribuzione. Soluzioni annunciate di corsa, senza il tempo di scrivere un paper decente, isolare il metodo nuovo, citare chi ci era arrivato prima. I firmatari usano la parola plagio.
2. La catena di trasmissione. Un'idea matematica diventa viva solo se qualcuno la adotta, la insegna, la integra nel canone. Senza matematici disposti a fare quel lavoro, un'idea prodotta da una macchina resta un file e non entra nella disciplina.
Qui la cosa smette di riguardare la matematica.
I firmatari lo scrivono esplicitamente: "stiamo assistendo a una minaccia generale al lavoro intellettuale." Anni di formazione non servivano solo a produrre la risposta finale. Servivano a costruire la capacità di formulare la domanda successiva. Se la risposta arriva gratis e la formazione salta, quello che si perde non è il risultato: è chi sarebbe stato in grado di chiedere la cosa dopo.
Vale per la matematica oggi. Vale per l'ingegneria, la diagnostica, il diritto, il progetto, domani.
Personalmente non leggo questo documento come luddismo. Venticinque persone che hanno vinto la Fields non firmano per paura di essere superate: nel testo dicono chiaramente che l'AI può accelerare lo studio matematico autentico. Firmano perché hanno riconosciuto un problema di incentivi, non di capacità.
E la frase più importante è l'ultima: "se questi cambiamenti gioveranno al campo o avranno un effetto distruttivo sarà in larga parte determinato dalle decisioni degli esseri umani che controllano questa tecnologia."
Non è un problema tecnologico è un problema di regole. E come sempre, le regole le scrive chi possiede l'infrastruttura, non chi la usa.
































