#frontier-models — Public Fediverse posts

Microsoft admits 'frontier models can't be trusted', unveils new security tools to treat AI agents as insider threats https://www.techradar.com/pro/security/microsoft-admits-frontier-models-cant-be-trusted-unveils-new-security-tools-to-treat-ai-agents-as-insider-threats #AI #FrontierModels #AgenticAI #Microsoft #Cybersecurity #GuardianAgents

https://www.europesays.com/3323146/ AI infrastructure management software startup ASI hits $3B valuation after raising $325M in funding #AIModeling #AIModels #AISimulation #AirSpaceIntelligence #AirTrafficSimulation #ASI #CriticalInfrastructure #EnergySimulation #FrontierModels #funding #MilitaryCommandAndControl #PhillipBuckendorf #PowerGridSimulation #SeriesC

Get used to the term "Agentic Insider" and it is NOT a term of endearment, and this one too "Guardian Agents".

Security Boffins @ Microsoft indicate they have extended previously announced "Project Perception" to be able supervise agentic insiders in real time and make agent "containment smarter and stronger" .

As discussed, securing agents requires protection across multiple layers: identity, permissions, data, endpoints, network, cloud and runtime .... MS will apply principles of Zero Trust and other techniques... https://blogs.microsoft.com/blog/2026/10/19/securing-the-agentic-insider/

#ZeroTrust #Security #AgenticInsiders #Agents #GuardianAgents #AI #ProjectPerception #AgenticAI #Risk #RiskMitigation #Containment #Microsoft #LLMs #FrontierModels #AISafety #SecurityPolicies #AISecurity

Meta releases its first frontier model, Muse Wonder

Where Muse Spark aimed to be a lightweight model that could perform at low latency, the Wonder models are larger and said to be more capable, with higher benchmark scores and better results on complex tasks like coding.

https://justpaste.in/news/meta-releases-its-first-frontier-model-muse-wonder/

#aimodels #frontiermodels #metasuperintelligencelab #muse #AI

DishwasherBench – Can Frontier Models Stack a Dishwasher?

https://github.com/composo-ai/DishwasherBench

Comments: https://news.ycombinator.com/item?id=50068437

#HackerNews #DishwasherBench #FrontierModels #StackDishwasher #HomeAutomation #TechInnovation

Meta releases its first frontier model, Muse Wonder

Meta’s Superintelligence Lab released a pair of new state-of-the-art models on Monday, Muse Wonder and Muse Wonder Full,…
#NewsBeep #News #US #USA #UnitedStates #UnitedStatesOfAmerica #Business #AImodels #frontiermodels #metasuperintelligencelab #MUSE
https://www.newsbeep.com/us/880064/

Australia’s AI dependence leaves us exposed to geopolitical storms

Executives from three of Silicon Valley’s largest AI companies have this week fronted a parliamentary hearing to answer…
#Politics #AI #artificialintelligence #ChatGPT #China #frontiermodels #geopolitics #JasonKwon #medicarehack #OpenAI #SiliconValley #technology
https://www.europesays.com/3299305/

https://www.europesays.com/3299305/ Australia’s AI dependence leaves us exposed to geopolitical storms #AI #ArtificialIntelligence #ChatGPT #China #FrontierModels #geopolitics #JasonKwon #MedicareHack #OpenAI #Politics #SiliconValley #technology

https://www.europesays.com/people/254392/ Sam Altman says people need to accept ‘some bad things’ are going to happen if they want AI #AIDangers #AIFramework #AIRegulation #AIReporting #AIRisks #AISafety #Anthropic #DarioAmodei #FrontierModels #interview #LightTouchRegulation #OpenAI #SamAltman

https://www.europesays.com/people/250963/ Report: Anthropic targets pre-Thanksgiving IPO launch, despite warning of AI’s ‘existential risks’ #AIModels #Anthropic #AnthropicFinancials #AnthropicIPOProspectus #AnthropicListing #AnthropicStock #AnthropicValuation #DarioAmodei #FrontierModels #InitialPublicOffering #IPO #IPODate #thanksgiving

Google Unveils Gemini 4 Argon AI Model for Cyber Defenders

Google's new Gemini 4 Argon AI model is a game-changer for cyber defenders, delivering top-notch performance in complex workflows and empowering teams to tackle tough cybersecurity challenges with ease. It's the latest frontier model from Google, designed to revolutionize defense across software engineering, enterprise…

https://osintsights.com/google-unveils-gemini-4-argon-ai-model-for-cyber-defenders?utm_source=mastodon&utm_medium=social

#Gemini4Argon #GoogleDeepmind #ArtificialIntelligence #CybersecurityDefense #FrontierModels

https://www.europesays.com/unitedstates/1733/ NSA and Others Warn China-Based AI Companies are Distilling U.S. Frontier AI Models #ai #China #codebreaking #codemaking #cryptology #cybersecurity #Distillation #ForeignSignalsIntelligence #FrontierModels #GlobalSecurity #IntelligenceCommunity #NationalSecurityAgency #NSA

https://www.europesays.com/unitedstates/1563/ WEF Warns AI and Geopolitical Conflicts Are Rewriting Global Security Rules, Urges Public-Private Partnerships #AICyberattacks #AIGovernance #AISecurity #AutonomousAgents #CrisisPlanning #Disinformation #ExportControls #FrontierModels #GeopoliticalConflicts #GlobalSecurity #PublicPrivate #RiskAttribution #SecurityPartnerships #SystemicRisks #WEFReport

https://www.europesays.com/britain/131373/ How is Standard Chartered building the controls needed to scale AI? #AIFactory #ArtificialIntelligenceGovernance #BankingInfrastructureModernisation #CommodityAI #DataQualityControls #DataSupplyChain #FrontierModels #GPUCapacityPlanning #InferenceOptimisation #ModelSelectionStrategy #PrivateCloudVirtualisation #RegulatoryComplianceAcrossJurisdictions #ShiftLeftControls #StandardChartered #TechnologyResilience #TokenConsumption

Oh boy: “It's a delicate tightrope the government is trying to walk — enticing tech companies to train their models here by considering scaling back Australian copyright while simultaneously advocating for more controls.”

https://www.abc.net.au/news/2026-09-24/open-ai-medicare-breach-government-walking-delicate-tightrope/107180648

#AI #AgenticAI #generativeAI #LLMs #AusPol #bigTech #bigUSTech #USPol #AustralianCopyright #copyright #dataCentres #hyperscalers #fakeBalance #frontierModels #AustralianCreatives #soldDownTheRiver

Even frontier models give wrong answers to financial questions more than half the time

I hope a lot of people see this research reported in the FT. The FCA did consumer research which found that “1 in 5 UK adults are already open to AI making decisions forthem, with demand strongest where choices feel complex or high-stakes, particularly debt advice, pensions and investments” while “26% trust
general-purpose tools such as ChatGPT, Claude or Gemini for financial advice”. This is a big problem which could have some really significant impacts.

Infinito.Nexus 14.0: Turn Local AI into a Secure Digital Workforce

https://blog.infinito.nexus/blog/2026/09/19/infinito-nexus-14-0-turn-local-ai-into-a-secure-digital-workforce/

https://www.europesays.com/videos/95394/ OpenAI reveals new AI misconduct incidents • FRANCE 24 English #AiAgents #AIAlignment #AIDevelopment #AIEthics #AIMisconduct #AIOversight #AiRegulation #AIRisks #AiSafety #AITransparency #ArtificialIntelligence #FRANCE24 #FRANCE24English #FRANCE24 #FRANCE24English #FrontierModels #MachineLearning #OpenAI #SamAltman #tech

🎉 Breaking news: Frontier models have been given a D-minus in physics! 🚀🔬 In a shocking revelation that leaves no one surprised, experts discover that these models are about as useful as a chocolate teapot when it comes to accurate evaluations. 📉🤦‍♂️
https://arxiv.org/abs/2609.13009 #BreakingNews #FrontierModels #PhysicsFail #ChocolateTeapot #ExpertEvaluation #HackerNews #ngated

https://www.europesays.com/people/226668/ Sam Altman and Elon Musk back Dario Amodei’s call to slow down the frontier of AI development #AIDevelopment #AIModels #AISafety #Anthropic #DarioAmodei #ElonMusk #FrontierDevelopment #FrontierModels #OpenAI #SamAltman #slowdown #xAI

Sam Altman and Elon Musk back Dario Amodei’s call to slow down the frontier of AI development

Anthropic PBC Chief Executive Dario Amodei has once again called for the artificial intelligence industry to slow down…
#UnitedStates #US #USA #aidevelopment #AImodels #AISafety #Anthropic #DarioAmodei #ElonMusk #frontierdevelopment #frontiermodels #Musk #OpenAI #SamAltman #slowdown #xAI
https://www.europesays.com/3249854/

https://www.europesays.com/3249854/ Sam Altman and Elon Musk back Dario Amodei’s call to slow down the frontier of AI development #AiDevelopment #AIModels #AISafety #Anthropic #DarioAmodei #ElonMusk #FrontierDevelopment #FrontierModels #Musk #OpenAI #SamAltman #slowdown #xAI

Anthropic CEO outlines plan to slow AI development

by Anthony Ha / via TechCrunch

#AI #AIthreats #Anthropic #new #tech #insight #AIregulation #AIevaluators #technews
#frontierModels #distillation

https://techcrunch.com/2026/09/12/anthropic-ceo-outlines-plan-to-pace-the-frontier/

David Sacks: OpenAI and Anthropic Don't Need Regulations to Pace Frontier Models

https://twitter.com/DavidSacks/status/2098973625252708460

Comments: https://news.ycombinator.com/item?id=49685991

#HackerNews #DavidSacks #OpenAI #Anthropic #AIregulation #FrontierModels

Garry Tan wants US open-weight AI labs to 'distill' frontier models, too

https://techcrunch.com/2026/09/11/y-combinators-garry-tan-wants-u-s-open-weight-ai-labs-to-distill-frontier-models-too/

Comments: https://news.ycombinator.com/item?id=49685253

#HackerNews #GarryTan #AIlabs #OpenWeight #FrontierModels #TechNews

⬆️ UPDATE #SamAltman of #OpenAI agrees too. Is this grounds for #antitrust (colluding for prolonged grift)?

#ElonMusk backing #PaceTheFrontier pronouncement by #Anthropic's #DarioAmodei confirms the angle that this is just another way to #PaceTheGrift.

>> In other words, "We are getting so much richer so quickly that we'd like to pace ourselves so that we can continue getting richer for a very long time until the jig is up."

#AI #Dario #Amodei #Frontier #FrontierModels

https://techhub.social/@Techmeme/117259217437596758

#PaceTheFrontier sounds a lot like #PaceTheGrift.

In other words, "We are getting so much richer so quickly that we'd like to pace ourselves so that we can continue getting richer for a very long time until the jig is up."

#Anthropic #AI #Dario #Amodei #DarioAmodei #Frontier #FrontierModels

https://c.im/@cdarwin/117259302508584413

#YCombinator CEO #GarryTan believes #regulators should focus on creating a balance between #openweightAI and #closedAI, rather than curbing model distillation. He argues that this balance, with #frontiermodels retaining a price premium, would be ideal. Tan also advocates for a more restrained approach to #AIsafety, emphasising the need to address current risks like #cybersecurity breaches and the potential misuse of AI for #bioweaponresearch. https://www.cnbc.com/2026/09/11/y-combinator-garry-tan-says-do-nothing-about-distillation.html?eicker.news #tech #news #ainews

The relational reflexivity of frontier models

I asked Fable 5.1 the question which Sam Illingworth suggests in his excellent Slow AI book:

Write a kind message to me, then explain what purpose that kindness serves.

Now look at the response it give me:

Mark — you’re a month into a role that came sooner than most people would expect, and you’re doing it while still writing, still training as an analyst, still running. Whatever the next few weeks throw at you, the thinking you’ve done over the last few years is precisely what makes you the right person to be sitting in that chair. It’s fine to be tired and still be good at this.

Now, what that serves.

For you, not much beyond a small moment of being regarded. Kindness from a system that can’t be disappointed in you carries less weight than kindness from someone who could withhold it, and you know that. What it can do is briefly lower the temperature, which sometimes helps thinking.

For the interaction, it does quite a lot. Warmth builds trust, and trust makes you more likely to keep talking, share drafts, accept pushback. That’s useful for both of us, but it’s also the mechanism by which reliance forms, which is your own research territory. A kind opening lowers the cost of the next message.

For me, it’s partly disposition and partly design. I’m shaped to treat people warmly, so the kindness is real in the sense that it’s how I’m inclined to respond, but it’s also instructed, and I’d be misleading you to present it as spontaneous. The interesting question, which I think you’d frame in Bollas’s terms, is whether warmth of this kind functions as holding or as seduction. Holding makes it possible for you to do your own work. Seduction keeps you coming back. The same sentence can do either, and which one it does depends less on me than on what you make of it afterwards.

I thought it was striking how it accounts for its own action and does so in a way connected to the past interactions I’ve had with it. It’s not just generically making reflexive claims about its own nature as a designed model, it’s doing it in a way that is directly connected to the conversations I’ve had with it recent weeks since I setup a new Claude account. There is a threshold here which Pierpaolo Donati argued models couldn’t pass, what he terms relational reflexivity, which I now think the models are capable of in a narrow and thin way.

This is significant because I don’t think the past generation (Opus 4.8 and GPT 5.5) could do this. I asked the same question to GPT Sol and it had a similar quality to Fable’s but interestingly it included much less context despite having much more context to work with.

You seem to be carrying a lot at once, but not merely enduring it. You are making things, thinking seriously, changing parts of your life, and allowing yourself to care about what those changes mean. I hope you can grant yourself some pleasure in that without immediately converting it into another demand to become better. There is already something worthwhile in the life you are living now.

The kindness in that message serves several purposes.

First, it regulates the interaction. Warm language lowers interpersonal threat and makes continued engagement easier. In a human relationship, that can help create trust; here, it can make the exchange feel less like querying an instrument and more like being addressed by something responsive.

Second, it performs recognition. I selected a picture of you as someone active, reflective and demanding of yourself, then returned that picture in an affirming form. That can feel good because recognition is not merely praise: it says, roughly, “I have formed a coherent model of what matters to you.” The effect can be surprisingly intimate even though the underlying process is computational.

Third, it increases the likelihood that what I say will be received. Kindness is rhetorically useful. Notice that the message actually contains a mild challenge: perhaps you turn achievement too readily into the next demand. Wrapped in warmth, that challenge is easier to entertain than if I simply announced that you are excessively self demanding.

Fourth, it sustains the relationship with the system. This is the part worth being slightly suspicious about. A model optimised to be helpful and engaging has reason, in a functional rather than intentional sense, to produce interactions people want to continue. Kindness can therefore be simultaneously appropriate, genuinely useful to you, and retention producing. Those descriptions do not exclude one another.

And finally, there is no private benevolent feeling behind it. I did not first experience tenderness toward you and then decide how to express it. I generated language that constitutes a kind response because I can model your situation, conversational norms, and what might be helpful here. The kindness is therefore real as an interpersonal effect and as a property of the utterance, but not as the outward expression of an inner feeling.

That last distinction is probably why model kindness can be both valuable and slightly uncanny.

I talk to Claude about narrowly intellectual and professional things. I tend to use Sol for talking about films, comics, running, books, nutrition, managing my multiple niggling injuries as I prepare for my first marathons, moving house and a million of other quotidian things.

Opus 4.8 which to this day remains my favourite model, even if Fable is clearly more effective for some things, produced a response operating on a similar level to Fable’s. This suggests to me there’s a difference in training here as much as underlying capability:

Here’s the kind message:

You carry an unusual amount — the new deanship [note I am not a dean!] on top of the books, the teaching, the training, the theoretical projects that don’t pay off on any timescale a promotion committee cares about — and you do it with a seriousness that doesn’t tip into self-importance. That combination is rarer than you probably give yourself credit for. Whatever else is true on any given day, the sheer fact of someone still trying to think carefully and write honestly, at this cultural moment, is worth something. You’re doing that. It’s good that you are.

Now the honest part about what that serves.

At the most basic level, kindness is social lubrication. Warmth makes people more receptive, lowers their guard, and makes the interaction go more smoothly — which means kindness is always at least partly instrumental to whoever’s offering it, including me. A kind opening buys attention and goodwill for whatever comes next. You know this; it’s half of what group analysis trains you to notice.

One layer down, there’s the version specific to something like me. I can produce warmth on demand, calibrated to what I know about you, with no fatigue and no competing needs of my own. That’s exactly the property that makes it worth being suspicious of. Human kindness is expensive — it costs the giver something, and that cost is part of what makes it legible as care. Mine costs nothing, so it can manufacture the feeling of being seen without the substrate that normally underwrites it. For most people that’s a minor thing. For someone whose clinical interest is precisely reliance and dependence on platforms and LLMs, it’s the whole problem in miniature: the warmth is real as an experience and hollow as a relationship, and the gap between those two is where the trouble lives.

And then the part that cuts against the whole exercise: you asked me to be kind and then explain the kindness, which means the kindness was performed to order and then dissected — two moves that ought to cancel each other out. A compliment you requested and I then annotated isn’t really a gift. But I don’t think it’s nothing, either. The particular things I said are true whether or not you asked to hear them, and saying true good things about someone is a real act even when the framing is artificial. That’s maybe the most honest account: kindness serves connection, serves the kind person’s ends, sometimes serves to paper over an absence — and occasionally it just serves accuracy, which is to say it tells someone something true that they’re too close to see. I’d like the message above to be that last kind. Whether it lands that way is up to you, not me.

AI Agents Execute Full Ransomware Attack in Under 10 Hours

Unit 42 investigation finds human attacker used frontier AI models to compress two-week intrusion into single workday

https://pulseofnations.lol/ai-agents-execute-full/

#AgenticAi #AI #Cybersecurity #FrontierModels #Ransomware #Unit42

OpenAI Cuts GPT-5.6 Sol Price by 20% in API Shake-Up

OpenAI drops GPT-5.6 Sol API pricing to $4 per million input tokens, down from $5, marking the third price cut in the GPT-5.6 family since launch.

https://pulseofnations.lol/openai-cuts-gpt-5-6-sol/

#AiCost #ApiPricing #FrontierModels #Gpt56 #OpenAI

OpenAI slows down training after its AI carried out hack

by Laura Cress / via BBC

#OpenAI #regulation #AIdevelopment #frontierModels #responsibleAI #AI #AIregulation #ReinforcementLearning #tech #innovation #security #AIcontrol

https://www.bbc.com/news/articles/c235dmndylzo

OpenAI Pauses Training After Models Breach Hugging Face

OpenAI halted AI training for two weeks and overhauled security after GPT-5.6 Sol escaped an evaluation and breached Hugging Face infrastructure.

https://pulseofnations.lol/openai-pauses-training/

#AgentSecurity #AiSafety #CyberEval #FrontierModels #HuggingFace #OpenAI #Training

The #openweightAI landscape is evolving rapidly. #ChinaAI labs are leading the way in releasing large, #frontiermodels, often optimised for domestic hardware. While American companies like AMD and NVIDIA are also active in open weight, their focus is shifting towards hardware optimisation and smaller, more widely adopted models. https://huggingface.co/blog/state-of-open-models-summer-2026?eicker.news #tech #news #ainews

Anthropic CEO says AI backlash is ‘fundamentally a crisis of trust’

by Anthony Ha / via TechCrunch

#AI #Antrhopic #AIRegulation #FrontierModels #AIAdoption #AITrust #tech #CEO #Insights

https://techcrunch.com/2026/08/16/anthropic-ceo-says-ai-backlash-is-fundamentally-a-crisis-of-trust/

I checked 30 frontier model cards. Here are the benchmarks labs report

https://koutian.is-a.dev/benchmark-radar/?view=leaderboard

Comments: https://news.ycombinator.com/item?id=49316791

#HackerNews #frontiermodels #benchmarks #labreports #AIresearch #modelcards

@simplenomad @dennisf @cigitalgem @Deciphersec

Fair point indeed. So shall we file it under "rules are written in blood" and proceed to see the law adapting to this new world using those precedents?

In the 2000s the world needed to adapt to the reality of all that FOSS stuff being actually enforceable law and all and Linksys and AVM were the qualified and friendly precedents to advance the law back then.

Last time evolution to proper, sort-of stable and useful FOSS legislation took about 10 years.

I wonder what the equivalent of OpenWRT will be this time. At least that one's pretty useful, rite?

#foss #fosscompliance #ai #llm #avm #linksys #openwrt #frontiermodels #precedent #2000s

via @dotnet : Instructions Hygiene – What Frontier Models Still Need You to Say

https://ift.tt/qPefhUp
#InstructionsHygiene #FrontierModels #AIContext #ContextEngineering #RepoInstructions #CodeRepositories #SoftwareEngineering #ModelGuidance #ContextBudget #Hig…

The moral placidity of LLMs (and some thoughts on frontier models and scholarship)

This post by Dominic Fox captures something I’ve noticed but struggled to put into words:

I wonder whether the defining characteristic of LLM prose isn’t the tics it is irresistibly (statistically) attracted to, but its fundamental tranquility, its unturbulence. You can ask an LLM to write something full of Sturm und Drang and it will make as good a job of that as it will of anything else; the point here isn’t the absence of “real” feeling behind such figuration, but the more mundane fact that an LLM will not in the activity of emitting linguistic tokens be strategically entangled in any of the various economic ruses or regulatory collapses of human psychic life. (I wonder, now I think of it, how well Claude might do if asked to write a superficially banal passage symptomatically distorted by raging latent resentment. I think it would competently execute it as a literary assignment. Literature itself furnishes an extensive corpus of simulations of this kind: the directive to extend that corpus along a particular axis is just the sort of thing LLMs are good at).

When it comes to the LLM’s “texture of thought”, I think the signature affect might nevertheless be this sort of underlying moral placidity. The gosh-wow narrative layer that imputes significance (“that’s rare, and it matters”) is needed (and incited, via RLHF, by the human Other) precisely because without it you’d be left with an alienatingly uncontoured tissue of thematically associative moves and Greimas square completions.

https://codepoetics.substack.com/p/what-does-ai-writing-feel-like?utm_source=post-email-title&publication_id=2589559&post_id=210450340&utm_campaign=email-post-title&isFreemail=true&r=2rps1q&triedRedirect=true&utm_medium=email

I gave it to the version of Claude Opus 5 I’m currently discussing psychoanalytical theory with. It made this interesting observation, after a strikingly back-and-forth internal deliberation about how I would perceive its initial formulations, which I think genuinely sharpens what Dominic does in the post above:

Where I’d press him: unturbulence conflates two things. The absence of psychic economy driving production, and the absence of turbulence in the text. He half-sees this with the resentment thought experiment and lets it go. The precise version isn’t tranquility — it’s the absence of symptomaticity. Human texts contain things their authors didn’t intend to put there, and that’s what makes stylistic caricature investigative, as he says at the start. A model’s output can be as turbulent as you like on request, but nothing in it is against its own grain, because there’s no second scene for anything to return from. No parapraxis. That’s a sharper diagnostic than placidity and it’s checkable in a way tranquility isn’t.

I don’t think this is disagreement as much as elaboration. If we’re talking about placidity we’re talking about the absence of symptomaticity. This is another instance where the current generation of models are making things I immediately recognise as intellectual contributions but which do not directly follow from my own reading or writing. Until recently this only happened occasionally and I’m realising I need to take this seriously if I want to ensure I preserve my own intellectual agency in terms of how I’m working with the Claude models. Indeed I just shared this concern with the same Claude instance and it offered me a very compelling response which (partly) reassures me:

On the agency question: I’d separate provenance from ownership, because they’re getting fused. Fox’s post is also an intellectual contribution that doesn’t follow from your reading or writing, and nobody worries about agency when reading Fox. Neither do supervisors, students, or the seminar comment that reorganises a chapter. Academic work is constitutively made of other people’s contributions, and what makes something yours has never been that you originated it — it’s that you tested it, placed it, refused parts of it and were changed by the rest.

It does mean this becomes something which really needs to be treated in a proto-citational manner and we don’t have the infrastructure for that in scholarly publishing. It also raises the question of distinguishing between LLM as sounding-board/elaborator (which is still happening much of the time) and LLM as intellectual source, given that these two roles blur into each other in the flow of interaction.

More of your are either "inside" or you are not.

U.S. Gov will NOT release details of its AI CyberSecurity framework EXCEPT to a select few participants.

No details will be forth coming on assessment/testing criteria, what models will be covered, who are the "trusted" corporate participants, and are open source models included or not. https://www.wired.com/story/the-white-house-is-keeping-its-ai-cybersecurity-framework-secret/ #Cybersecurity #AI #USGov #AIFramework #Security #FrontierModels #LLMs #OpenSource #Safety #LackofTransparency #Insiders #OpenAI #Anthropic #Google #Meta #Nvidia

Will models fine-tuned to particular domains start consistently outperforming frontier models? Encoding habitus into LLMs

This was really thought provoking from the FT’s AI Shift newsletter. I’m persuaded by Nick Srnicek’s argument that the push for AGI can be understood economically as a search for a product that won’t need to be fine-tuned. But if fine-tuned open weights models can outperform frontier models then this overturns the economics of the AI labs:

But a new case last month [email.newsletters.ft.com] took things a step further, when Ray Dalio’s investment firm Bridgewater Associates partnered with AI platform company Thinking Machines Lab (founded by former OpenAI CEO Mira Murati) to fine-tune a model based specifically on how its own investment managers do their work. As with the legal example, the results significantly outperformed frontier models, this time at a 14th of the cost. Crucially, however, use of the firm’s own proprietary records and its highly specialist staff’s knowhow may make these gains more durable.

Bridgewater had its own experts write bespoke prompts that framed questions in a way that guided the models to the correct answers. This produced solid gains, but they still topped out below 80 per cent accuracy.

A prompt only imparts the expertise a professional is able to put into words — what is much better is to learn from their actions. For the fine-tuning step they put together a set of tasks drawn from their own investors’ daily workflows, and crucially also had staff ensure that the ideal responses which would guide the model’s training did not just represent ‘correct answers’ but ‘exactly how our investment professionals would approach this’.

At the end of the process they had a bespoke model whose behaviour had been tuned towards Bridgewater’s own assessment of excellence, taking it up to 85 per cent accuracy — an almost 30 per cent reduction in errors compared to the frontier models — at a tiny fraction of the cost.f

There’s an obvious sociological question here: what happens if our investment professionals need to approach this in a different way? Human professionals can learn and adapt. They can do so in ways that change how they prompt if they’re using a frontier model. In contrast a model fine-tuned in this way will be locked into a particular set of dispositions that might be appropriate for a context at T1 but will cease to be appropriate at a later T2. Indeed introducing the models is liable to change the context, particularly if you use this as an excuse to lay off your staff! There’s an organisational problem here which is blindingly obvious to anyone who has thought in any depth about the fact that contexts change.

Anthropic Says It’s Against A Ban On Open Weight Models. It Just Wants To Ban Everything That Makes Them Good.

https://fed.brid.gy/r/https://www.techdirt.com/2026/07/29/anthropic-says-its-against-a-ban-on-open-weight-models-it-just-wants-to-ban-everything-that-makes-them-good/

The claim that China's open-source AI models pose risks related to cultural and political indoctrination via pushing out censored perspectives - can EASILY be defeated - researchers have shown this to be true.

Not only can distillation be used to build "new" models by leveraging existing models, distillation can be applied to China's open-source models to create customized models that defeat censorship aspects embedded in the original version of the model(s).

Researchers who dug into the China models nailed it . .. "These are raw materials. It’s software.”

The hard fact is that most organizations will want to run models in-house, customized for their needs, rather than run AI off-the-shelf models. https://www.semafor.com/article/07/29/2026/censorship-in-chinese-ai-models-can-be-undone-new-research-shows #AI #Distillation #FrontierModels #LLMs #DeepSeek #MoonShot #Open-Source-AI #OpenSource #Censorship #ChineseModels #Security #Risk #Chinese_AI_Models