π€ Marvell is paying $115B for a laser company
Marvell is buying optical-components maker Lumentum to go after Broadcom in AI data-center hardware.
β’ Marvell's own market value is above $170B
β’ Nvidia put $2B into each company earlier this year
β’ In August, Marvell signed a Google chip supply deal worth up to $120B through fiscal 2033
Marvell is buying optical-components maker Lumentum to go after Broadcom in AI data-center hardware.
β’ Marvell's own market value is above $170B
β’ Nvidia put $2B into each company earlier this year
β’ In August, Marvell signed a Google chip supply deal worth up to $120B through fiscal 2033
π¨ Anthropic's biggest constraint is chips.
The New York Times reports that Anthropic is scrambling for computing power, with the IPO closing in.
Claude can only grow as fast as the GPUs and data center space Anthropic can lock down. And the clouds it leans on are also building rival models.
The New York Times reports that Anthropic is scrambling for computing power, with the IPO closing in.
Claude can only grow as fast as the GPUs and data center space Anthropic can lock down. And the clouds it leans on are also building rival models.
Nytimes
Inside Anthropicβs Hunt for A.I. Computing Power
The company went on a deal spree with tech giants, former crypto miners and others to gain computing power to further its artificial intelligence ambitions.
π¨ Anthropic's S-1 says it may soon hit its own definition of recursive self-improvement
The amended filing adds new risk-factor language. Anthropic says it has already used AI to build models whose capability jumps it didn't recognize at the time. It also says no model has crossed the line yet, and humans stay in the R&D loop.
An S-1 is a disclosure and a sales pitch at once. "Our AI might build itself" is a strange thing to put in either.
The amended filing adds new risk-factor language. Anthropic says it has already used AI to build models whose capability jumps it didn't recognize at the time. It also says no model has crossed the line yet, and humans stay in the R&D loop.
An S-1 is a disclosure and a sales pitch at once. "Our AI might build itself" is a strange thing to put in either.
TechCrunch
Anthropic warns that it's very close to RSI capability, aka self-building AI | TechCrunch
RSI is the point at which AI grows so good at training itself that it spawns a dramatic acceleration of AI capabilities. To the AI doomers, RSI represents the cataclysm from which there is no return.
π¨ Anthropic's IPO filing shows $895B in compute and lease commitments
The FT reports that $447.5B of it lands by the end of 2030. That's roughly $105B a year, against about $67B of projected 2026 revenue.
The plan only works if Anthropic grows into a Microsoft-sized company, and the lease terms run 19 years.
The FT reports that $447.5B of it lands by the end of 2030. That's roughly $105B a year, against about $67B of projected 2026 revenue.
The plan only works if Anthropic grows into a Microsoft-sized company, and the lease terms run 19 years.
Ft
Anthropic reveals $900bn AI spending commitments ahead of IPO
Claude makerβs infrastructure costs rise faster than revenues, as investors scrutinise economics of AI boom
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π€ GitHub Agentic Workflows hit GA, and your automation is now a Markdown file
GitHub made it generally available on Free, Team and Enterprise. You describe the job in plain English (issue triage, CI failure analysis, doc updates, test writing), and it compiles to standard Actions YAML. It runs on your existing runners and policies, with Copilot or your own coding agent.
So the agent's permissions are just Actions permissions.
GitHub made it generally available on Free, Team and Enterprise. You describe the job in plain English (issue triage, CI failure analysis, doc updates, test writing), and it compiles to standard Actions YAML. It runs on your existing runners and policies, with Copilot or your own coding agent.
So the agent's permissions are just Actions permissions.
The GitHub Blog
GitHub Agentic Workflows generally available - GitHub Changelog
GitHub Agentic Workflows, an open source project from GitHub Next, is now generally available. With agentic workflows, you can automate reasoning-based tasks like issue triage, CI failure analysis, documentation updates,β¦
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π¨ Stolen AI API keys just ran up nearly $1M in charges at a single company
Google's threat intel team calls it LLMjacking. Attackers grab cloud credentials, run inference on the victim's bill or resell the access, and Mandiant saw fraudulent charges top $100K in a single day at some victims.
Google's threat intel team calls it LLMjacking. Attackers grab cloud credentials, run inference on the victim's bill or resell the access, and Mandiant saw fraudulent charges top $100K in a single day at some victims.
Google Cloud Blog
The Rise of LLMJacking: How Threat Actors Monetize Compromised Cloud and Model Resources | Google Cloud Blog
Mandiant reveals how LLMJacking attacks cost victims hundreds of thousands in fraudulent cloud bills, with underground markets targeting LLM credentials.
π¨ Gartner says open models can handle 90% of agentic work at one-twentieth the frontier price
The analyst firm's pitch to CIOs, per The Register, is to stop paying frontier rates for routine agent tasks. Open-weight models are more verbose and burn more tokens per task, which eats into that 20x gap unless you self-host.
The analyst firm's pitch to CIOs, per The Register, is to stop paying frontier rates for routine agent tasks. Open-weight models are more verbose and burn more tokens per task, which eats into that 20x gap unless you self-host.
theregister
Open models can do 90 percent of agentic work at a twentieth of the cost of a frontier LLM: Gartner
Models are commodities, harnesses are the valuable part
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π¨ Nvidia reportedly caps Chinese customers at 49% of a data center operator's business
Tom's Hardware reports that the rule applies globally, and Nvidia hasn't confirmed it.
β’ The limit is 49%, so at least 51% must be non-Chinese
β’ Operators outside China would have to check where customers come from
β’ Neoclouds renting out GPUs are the likely targets
A cap on China that's enforced through the landlords.
Tom's Hardware reports that the rule applies globally, and Nvidia hasn't confirmed it.
β’ The limit is 49%, so at least 51% must be non-Chinese
β’ Operators outside China would have to check where customers come from
β’ Neoclouds renting out GPUs are the likely targets
A cap on China that's enforced through the landlords.
Tom's Hardware
Nvidia tells data center operators to limit business from Chinese customers with new global restrictions, report claims β allegedlyβ¦
Cloud providers have been told that they must sell 51% of their services to non-Chinese companies for the first time.
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π¨ DeepMind staff say Google won't let them talk about AI risks, and criticism can mean a lifetime ban
Researchers are protesting what they describe as a gag on public discussion of what they know. The NDA reportedly survives resignation, so quitting to warn the public doesn't get them out of it.
Researchers are protesting what they describe as a gag on public discussion of what they know. The NDA reportedly survives resignation, so quitting to warn the public doesn't get them out of it.
The Washington Post
Google researchers are fighting the company to tell the world what they know about AI
Employees said that employment contracts at Google's AI division deter workers from speaking out about the dangers of the technology.
π¨ OpenAI staff have warned about weak operational security for years, Reuters sources say
Per a Reuters report, employees raised the alarm repeatedly while the company kept shipping bigger models. Those are the same models whose weights and training data every rival and state hacker group would love to get their hands on.
Per a Reuters report, employees raised the alarm repeatedly while the company kept shipping bigger models. Those are the same models whose weights and training data every rival and state hacker group would love to get their hands on.
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π¨ Google is shutting down Jules, its async coding agent
Google's Jules is getting retired, per a changelog entry dated 2026-10-29. It was Google's answer to Codex and Claude Code, a bot that took a GitHub task, worked in a cloud VM, and sent back a pull request. No word here on a migration timeline or a replacement.
Google's Jules is getting retired, per a changelog entry dated 2026-10-29. It was Google's answer to Codex and Claude Code, a bot that took a GitHub task, worked in a cloud VM, and sent back a pull request. No word here on a migration timeline or a replacement.
Google
Jules - an end-to-end agentic product development platform by Google
Jules is your end-to-end agentic product development platform. It reads your entire product context to figure out what to build next, comes up with solutions, and then ships a PR.
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π¨ Revolut says self-hosting GLM cut its AI coding bill by about 90%
The Register reports that GLM 5.1 is now Revolut's default coding model, at roughly $0.30 per million tokens, about a tenth of what Codex or Claude Code cost. It was running Claude Code only since early 2026, and GLM hasn't fully replaced GPT or Claude.
The Register reports that GLM 5.1 is now Revolut's default coding model, at roughly $0.30 per million tokens, about a tenth of what Codex or Claude Code cost. It was running Claude Code only since early 2026, and GLM hasn't fully replaced GPT or Claude.
theregister
British fintech Revolut slashes AI coding costs 10x by cutting out Claude and going self-hosted
Turns out cheap tokens get engineers doing things that save time, like debugging and tackling Jira tickets
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π€ Tencent drops Hy4, and it's leaning hard into visuals and animation
Tencent released Hy4, the next generation of its Hy model family. The pitch centers on visual and motion generation, the exact area where Claude Opus has been getting attention lately.
No benchmark numbers or training details are out yet.
Tencent released Hy4, the next generation of its Hy model family. The pitch centers on visual and motion generation, the exact area where Claude Opus has been getting attention lately.
No benchmark numbers or training details are out yet.
π€ Mistral Large 4 shows up as a paper page
A Large 4 entry appeared on AlphaXiv. That's the only trace so far, and the page doesn't show an announcement from Mistral.
I can't confirm the architecture, the benchmarks, or whether the weights are open.
A Large 4 entry appeared on AlphaXiv. That's the only trace so far, and the page doesn't show an announcement from Mistral.
I can't confirm the architecture, the benchmarks, or whether the weights are open.
alphaXiv
Mistral Large 4
We introduce Mistral Large 4 (ML4), a 52B active, 1T total parameter multimodal mixture-of-experts model designed for reasoning and long-horizon agentic tasks. We build a scalable agent-based...
π Anthropic wants to prove your API provider actually ran the model you paid for
Anthropic's provable inference research covers the case where nobody is trusted, not even the host generating the tokens. Signing outputs doesn't work there, so the provider has to keep verifiable records showing it took no shortcuts like a swapped model or a cheaper quantization.
Anthropic's provable inference research covers the case where nobody is trusted, not even the host generating the tokens. Signing outputs doesn't work there, so the provider has to keep verifiable records showing it took no shortcuts like a swapped model or a cheaper quantization.
Anthropic
Progress on provable inference for large language models
Sharing progress on a powerful type of cryptographic proof known as a zkSNARK, which is uniquely fit for provable inference.
π€ An amateur astronomer says Claude Code helped him find a new planet in public TESS data
Rabtsevich ran 74 tests trying to break his own hypothesis. In one, he gave Claude Code two TESS datasets and asked it to predict brightness dips in a third. Every prediction landed.
It's still a candidate, not a confirmed planet. Nobody can say yet how much credit belongs to the model and how much to the guy who kept trying to kill his own idea.
Rabtsevich ran 74 tests trying to break his own hypothesis. In one, he gave Claude Code two TESS datasets and asked it to predict brightness dips in a third. Every prediction landed.
It's still a candidate, not a confirmed planet. Nobody can say yet how much credit belongs to the model and how much to the guy who kept trying to kill his own idea.
Gizmodo
Did Claude Help an Amateur Astronomer Discover a New Planet?
Billions of exoplanets are believed to be out there awaiting discovery. AIβwith its ability to sift through mountains of dataβcould speed that process along.
π€ Kimi K3.1 Pro weights are on Hugging Face
Moonshot published the open weights for a new Kimi tier, a point update to K3. There are no benchmarks or details in the release yet, so you can download it before anyone has told you whether it's good.
Hardware needs and license terms are the first things to check.
Moonshot published the open weights for a new Kimi tier, a point update to K3. There are no benchmarks or details in the release yet, so you can download it before anyone has told you whether it's good.
Hardware needs and license terms are the first things to check.
huggingface.co
moonshotai/Kimi-K3.1-Pro Β· Hugging Face
Image-Text-to-Text model with 2.8T parameters. Download, explore files and run it on Hugging Face.
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π¨ Meta is buying Conductor, the app for running a pile of coding agents at once
Conductor announced it's joining Meta, which gets a tool built around parallel agent workflows:
β’ Mac app that runs multiple Claude Code sessions side by side
β’ Each agent works in its own isolated workspace
β’ You review and merge the diffs yourself
β’ No deal price or terms disclosed
Meta wants to own the layer where the agents get managed, not just the models.
Conductor announced it's joining Meta, which gets a tool built around parallel agent workflows:
β’ Mac app that runs multiple Claude Code sessions side by side
β’ Each agent works in its own isolated workspace
β’ You review and merge the diffs yourself
β’ No deal price or terms disclosed
Meta wants to own the layer where the agents get managed, not just the models.
www.conductor.build
Conductor is joining Meta
π§ Researchers are injecting "thoughts" into LLMs to see if the models notice
Quanta covers the Anthropic-born test for AI introspection and the replication work around it.
β’ Anthropic's Jack Lindsey planted a concept inside a model's network, then asked right away if it noticed
β’ Kyle Mahowald's group reran it on open-source models and found detection is more limited than it looks, but still surprising
β’ Simpler explanations couldn't fully account for the results
Quanta covers the Anthropic-born test for AI introspection and the replication work around it.
β’ Anthropic's Jack Lindsey planted a concept inside a model's network, then asked right away if it noticed
β’ Kyle Mahowald's group reran it on open-source models and found detection is more limited than it looks, but still surprising
β’ Simpler explanations couldn't fully account for the results
Quanta Magazine
New Research Tests Whether AI Models Know Their Own Thoughts | Quanta Magazine
By injecting βthoughtsβ directly into large language models, researchers are trying to map out AIβs capacity for introspection.
β‘οΈ Cognition's SWE-2 Flash claims 3x the speed of SWE-2 at one-fifth the price
Cognition released a smaller coding model built on Thinking Machines' Inkling-Small, a 276B MoE with 12B active params. Flash edges SWE-2 on FrontierCode 2.0 but trails it on Terminal-Bench 4.0 and DeepSWE 1.1, and all of the numbers are Cognition's own.
Cognition released a smaller coding model built on Thinking Machines' Inkling-Small, a 276B MoE with 12B active params. Flash edges SWE-2 on FrontierCode 2.0 but trails it on Terminal-Bench 4.0 and DeepSWE 1.1, and all of the numbers are Cognition's own.
Cognition
Introducing SWE-2 Flash
Weβre introducing SWE-2 Flash, a fully American coding model that sets a new bar for intelligence at low cost and high speed.
π¨ OpenAI's Images 2.6 outputs SVG, but it's a raster-to-vector pipeline under the hood
OpenAI shipped Images 2.6 with 50% faster generation and an explicit SVG output format. The API makes a reference image first, then converts it. List price matches 2.5, but low and medium quality tiers burn more tokens, so the real bill goes up.
OpenAI shipped Images 2.6 with 50% faster generation and an explicit SVG output format. The API makes a reference image first, then converts it. List price matches 2.5, but low and medium quality tiers burn more tokens, so the real bill goes up.
OpenAI
Introducing Images 2.6
Images 2.6 brings faster image generation, GIF creation, more precise editing, and new API controls across ChatGPT, Codex, and the API.