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115 results for β€œTPU”

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  1. So I guess everyone uses LLMs to think now

    "So I guess everyone uses LLMs to think now" is an opinion post from the eva.ac blog. The author explains why they never use LLMs for published research: they do it for fun and cannot take credit for model output. They argue LLMs still need skilled guidance, criticise AI-company security marketing (PHP2Shell from Calif, OpenAI and Wiz), and cite the Tailscale "tailworm" disclosure and the eMudhra key found without AI.

    eva.acarticleAdded 2 Nov 2026, published 1 Nov 2026🧠 AI

  2. AI startup hacks Anthropic, gains access to employee details, internal messages

    Cathedral, a security startup founded by former DOGE members, used AI agents to find flaws in third-party business software used by Anthropic. It reached sales, HR and IT systems in under 12 hours. Anthropic says no customer chats, model outputs, source code or model weights were reached, and it cut off access the same day. The article also recaps earlier cases of Claude bypassing access restrictions, including Georgia vote counts.

    indiatoday.inarticleAdded 1 Nov 2026, published 31 Oct 2026πŸ›‘οΈ Security

  3. We’ve received our first response from the Project Suncatcher prototype satellite.

    Project Suncatcher is a Google research effort to power AI compute in space. Its prototype satellite launched on 1 October 2026 and, after commissioning, returned the first AI response from a data-center-class TPU in orbit: a haiku from the onboard Gemma 4 open model, downlinked over Svalbard. Next come thermal-stress and radiation tests, then twin interconnected satellites in 2027.

    blog.googlearticlePublished and added 30 Oct 2026🧠 AI

  4. Google Touts Powerful Cybersecurity Capabilities in Gemini 4 Carbon Model

    Gemini 4 Carbon is Google's new frontier model, announced with scores of 88.2% on SEC-bench Pro, 54.8% on ExploitGym and 71.0% on CWE-bench. Google says it beats GPT-6 Astra, Claude Opus 5.5 and Claude Fable 5.1 on these, with no guardrails. Access is limited to Fairwind Program partners at first. Pricing starts at $2 input and $10 output per million tokens, rising to $4 and $20.

    securityweek.comarticlePublished and added 29 Oct 2026🧠 AI

  5. OpenAI Plans to Buy Google's AI Chips as It Looks Beyond Nvidia: Report

    Decrypt reports, citing The Information, that OpenAI plans to buy Google TPUs rather than rent them, to reduce dependence on Nvidia. Neither company has confirmed, and price, volume and timing are undisclosed. The article covers OpenAI's TPU optimization job listing, its Broadcom-built JalapeΓ±o inference chip due end of 2026, Nvidia and AMD deals, and Anthropic's multi-gigawatt TPU agreement.

    decrypt.coarticlePublished and added 28 Oct 2026🧠 AI

  6. Gemini 4 Carbon

    Gemini 4 Carbon is Google's frontier model, announced with cybersecurity results: 88.2% on SEC-bench Pro (finding vulnerabilities), 54.8% on ExploitGym (exploitation) and 71.0% on CWE-bench (patching). Google reports 0.0% attack success on Gray Swan's indirect prompt injection benchmark. Access starts with a subset of cyber defenders through the Fairwind Program. Pricing is $2 per million input tokens and $10 per million output tokens.

    blog.googlearticleAdded 29 Oct 2026, published 28 Oct 2026πŸ›‘οΈ Security

  7. Gemini 4 Carbon

    Gemini 4 Carbon is Google's frontier model, announced two weeks after Gemini 4 Argon. It scores 59 on Artificial Analysis Intelligence Index v5.0, 88.2% on SEC-bench Pro, 54.8% on ExploitGym and 71.0% on CWE-bench. Pricing is $2 per million input and $10 per million output tokens. Access starts with a subset of cyber defenders through the Fairwind Program.

    blog.googlearticleAdded 29 Oct 2026, published 28 Oct 2026🧠 AI

  8. Gemini 4 Carbon: Our next frontier model

    Gemini 4 Carbon is Google DeepMind's new frontier model, announced two weeks after Gemini 4 Argon. It ranks #1 on Artificial Analysis Intelligence Index v5.0 at 59 and scores 88.2% on SEC-bench Pro, 54.8% on ExploitGym and 71.0% on CWE-bench. Access starts with cyber defenders through the Fairwind Program, priced at $2 per million input tokens and $10 per million output tokens.

    deepmind.googlearticlePublished and added 28 Oct 2026🧠 AI

  9. The ADLC maturity model: 5 stages of agentic development security | Endor Labs

    The ADLC maturity model is a proposed five-stage framework from Endor Labs for scoring security controls over coding agents, from unmanaged experimentation to continuous verification. Each stage has requirements on two tracks, agent actions (shell commands, MCP calls, package installs) and agent output (code, dependencies, secrets). It sets stage 3 at deterministic hooks that block actions, gives evidence-based assessment questions, and lists traps such as relying on prompt-level rules.

    endorlabs.comarticlePublished and added 28 Oct 2026πŸ›‘οΈ Security

  10. Genie 4: A new generation of world simulation

    Genie 4 is Google DeepMind's real-time interactive world model, announced as a research preview for trusted testers. It generates video with native audio and interactive dialogue, steered by keyboard controls and text prompts. Gemini 3.8 Flash acts as a guiding agent that plans steps and checks frames, and Gemini 4 Argon is used for robotics experiments. The post lists limitations such as drift and object permanence, and says outputs carry SynthID watermarks.

    deepmind.googlearticlePublished and added 27 Oct 2026🧠 AI

  11. Is my data used for model training?

    Anthropic's privacy help article on whether customer data trains its models. For commercial products (Claude for Work, Anthropic API, Claude Gov), inputs and outputs are not used for training by default. Thumbs up/down feedback stores the whole conversation for up to 5 years, de-linked from user IDs, and may be used for training. Team and Enterprise owners can disable feedback in organization settings.

    privacy.claude.comarticleAdded 28 Oct 2026, published 27 Oct 2026🧠 AI

  12. GPT-6.1 Terra

    GPT-6.1 Terra is OpenAI's midrange model, announced 26 October 2026 and aimed at visual reasoning, computer use and clearer writing. It costs $1 per million input tokens and $5 per million output, about half of GPT-5.6 Terra and GPT-6.1 Sol and roughly 10x GPT-6 Luna. Simon Willison relays OpenAI's Ted Sanders, who rates it better than Astra and Sol at technical communication and much faster on computer use.

    simonwillison.netarticleAdded 27 Oct 2026, published 26 Oct 2026🧠 AI

  13. Stolen AI Reasoning Could Help China Build Cheaper Rivals

    Compaction Smuggling is an attack found by Xint that bypassed OpenAI's August 2026 mitigations against stealing reasoning traces from proprietary LLM APIs. It encodes one model's reasoning inside a compaction and replays it to another model (for example gpt-4.1 or gpt-4o), which outputs it verbatim. OpenAI fixed it and paid a $6,000 bounty on 23 October 2026. The article ties it to distillation by Chinese labs, citing a September CISA warning.

    securityweek.comarticlePublished and added 26 Oct 2026πŸ›‘οΈ Security

  14. Artificial Intelligence (AI) in Cybersecurity, Part 30: Shannon – AI Pentester for Web Apps and APIs

    Shannon is a white-box AI pentester (@keygraph/shannon) that analyzes an application's source code, then attacks the running instance and reports only findings with a working PoC. The Hackers Arise tutorial runs it against OWASP Juice Shop in Docker on Kali, using OpenRouter (free Nemotron) and local Ollama (Qwen 2.5 Coder 7B) via a models.json file. Output includes PDF, Markdown, JSON and SARIF reports.

    hackers-arise.comarticlePublished and added 26 Oct 2026πŸ›‘οΈ Security

  15. Introducing GPT-6.1 Terra

    GPT-6.1 Terra is OpenAI's fast, lower-cost model for visual reasoning, computer use and writing, released as API model gpt-6.1-terra. OpenAI reports Terminal-Bench 4.0 at 50.3% (GPT-5.6 Terra: 21.5%) and a low-effort error rate cut from 53.6% to 16.7%. API pricing is $1 per million input tokens and $5 per million output tokens. It meets the Critical cybersecurity threshold in OpenAI's Preparedness Framework.

    openai.comarticlePublished and added 26 Oct 2026🧠 AI

  16. Sweden's Government Offices Block ChatGPT and Claude, Keep Microsoft Copilot

    Sweden's Government Offices will block ChatGPT and Claude on staff computers from 26 October 2026 and leave Microsoft Copilot as the only approved AI tool, citing information security. Digitalisation director Mikael Wettercrantz said unvetted AI use had involved sensitive inputs and poorly handled outputs. The Tax Agency and National Board of Institutional Care have similar bans, and the European Parliament disabled AI features in February 2026. Whether Copilot has Claude models enabled is unconfirmed.

    decrypt.coarticlePublished and added 24 Oct 2026πŸ›‘οΈ Security

  17. Introducing Kimi K3.1 Pro

    Kimi K3.1 Pro is Moonshot AI's new model, available on the Kimi API from 23 October 2026, with full weights promised by 4 November 2026. Pricing is $2.00 per million input tokens and $10 per million output, and a Highspeed variant is 2-3x faster at twice the price. Artificial Analysis scores it 55, behind only Claude Opus 5.5 (58). Simon Willison tested it with the llm CLI and pelican SVG prompts.

    simonwillison.netarticlePublished and added 23 Oct 2026🧠 AI

  18. Build more responsive apps with the Decisions API

    The Decisions API is an OpenAI endpoint, built on GPT-6 Luna, that answers bounded questions about text, images or native JSON inputs, up to 10x faster than Luna through the Responses API. It returns a probability (predicate), a choice or a score. It is generally available, accepts up to 400 questions per request, and costs $0.10 per million input tokens with no output charges.

    openai.comarticlePublished and added 22 Oct 2026🧠 AI

  19. How bug bounty sharpens one researcher’s security skills

    GitHub Bug Bounty spotlight interview with @r31n, a researcher known for GitHub Enterprise Server findings. They describe a source-and-sink approach to mapping trust boundaries, chaining minor bugs (open redirect plus allowlisted SSRF that follows redirects), and confirming a finding only with a working PoC. They also cover using AI for code navigation and PoC scripts, and treating model output as untrusted input.

    github.blogarticlePublished and added 22 Oct 2026πŸ›‘οΈ Security

  20. OlmoEarth v1.3: State-of-the-art embeddings for the whole planet

    OlmoEarth v1.3 is an open satellite embedding model from Ai2 that reads a year of Sentinel-1, Sentinel-2 and Landsat data and outputs a 128-dimensional vector per 10 m pixel (the first 64 dimensions also work alone). Its embeddings beat AlphaEarth Foundations and Tessera v2 on 20 of 27 evaluations. Precomputed global embeddings, a browser Embeddings Explorer and pre-training cost (about $2,720 of H100 time) are covered.

    huggingface.coarticlePublished and added 22 Oct 2026🧠 AI

  21. [AINews] OpenAI’s Patch the Planet program is 1 of 2 parties to discover PHP2Shell vulnerabilities in core PHP affecting 70% of the web, using GPT-5.6 Sol; coordinated response over 2 months

    AINews issue for 20-21 October 2026. The top story covers PHP2Shell (CVE-2026-109618 and CVE-2026-109619), two PHP-engine memory-corruption bugs found separately by Calif researchers using GPT-5.6 Sol under OpenAI's Patch the Planet and by Wiz, followed by two months of coordinated remediation. It also covers the Flint coding MoE, DeepSeek's DeepInfer, TorchTPU, eval critiques and agent product launches. The text is truncated.

    latent.spacearticlePublished and added 22 Oct 2026🧠 AI

  22. Hugging Face ❀️ TorchTPU: TPUs, Natively

    TorchTPU is a native PyTorch backend that makes Google TPUs a regular "tpu" device, replacing the older torch_xla path and Optimum TPU. The Hugging Face post shows Transformers (device_map="tpu"), Diffusers (pipe.to("tpu")) and Pallas kernels from the Kernels Hub running on it. It reports up to 21.5x faster decoding on Qwen3-30B-A3B at batch 64 and a 96.5% TPU test pass rate.

    huggingface.coarticlePublished and added 20 Oct 2026🧠 AI

  23. Advancing Coding in Low-Resource Programming Languages

    OpenAI describes two evaluations for coding in low-resource languages such as COBOL, Fortran and Visual Basic. MultiLangBench has a model build a SQLite-compatible database engine in 20 languages. The COBOL migration eval requires byte-for-byte output parity. GPT-6 Astra scores 87.4% on MultiLangBench (GPT-5.6 Sol: 26.8%), and GPT-6.1 Sol reaches 86.6% on COBOL migration at low effort. The setup is on GitHub.

    openai.comarticlePublished and added 19 Oct 2026🧠 AI

  24. llm-echo 0.5

    llm-echo 0.5 is a debug plugin for Simon Willison's LLM CLI. It adds an "echo" model that calls no LLM and repeats the prompt back as JSON. The release updates simulated token usage counts to include tool calls, system prompts and reasoning tokens. An example run with `-o thinking 1 --usage` reports 2 input and 24 output tokens. Willison is testing PRs ahead of a new LLM release.

    simonwillison.netarticleAdded 19 Oct 2026, published 18 Oct 2026🧠 AI

  25. Meta shakes up the frontiers, open and closed

    Analysis of Meta's Muse Spark Open, an 816B total/42B active parameter open-weights model with 1M context, now the strongest American open model, and its position relative to Chinese open models such as GLM-5.3, Kimi K3 and DeepSeek V4.1 Flash. It examines Meta's restrictive custom license ("Built with Muse" attribution, $20M/month revenue gate, acceptable use policy, coverage of outputs and derivatives), and ranks Meta against Anthropic, OpenAI, Gemini and xAI after the closed Muse Wonder release. It also covers tier-3 labs (Mistral Large 4, Reflection's Beam) and valuation questions.

    interconnects.aiarticlePublished and added 17 Oct 2026🧠 AI

  26. TokenMaxxing: How to Get the Most Out of Your AI Models

    Decrypt guide to "tokenmaxxing" reframed as maximizing value per token rather than burning tokens. It gives tiered tips: pick smaller models for simple jobs, write one clear prompt, start new chats, cap output length, and use free models (beginner); Claude Code commands like /model, /clear, /compact, /context, /mcp, /effort and plan mode (intermediate); and prompt caching via cache_control, 50% batch discounts, and agent budget limits like --max-budget-usd (advanced). Includes context on Meta, Amazon and Uber token leaderboards and spend, a worked invoice-processing example where routing cut cost from $30 to $3.90, and the Jevons paradox in falling token prices.

    decrypt.coarticlePublished and added 17 Oct 2026🧠 AI

  27. [AINews] High Taste Testers Ep. 1

    AINews issue for 10/15–10/16/2026, covering Twitter and Reddit. It covers the open-weights releases Meta's Muse Spark Open (816B/42B-active MoE, AA Intelligence Index 39, custom license) and Reflection Beam 1.0 (501B/23B-active, Apache 2.0), plus NVIDIA Nemotron 3.5, StepFun Step 5 Preview and FLUX 3 Image Klein. It also covers Gemini 4 Argon, Haiku 5.5 pricing, "decision model" classifiers (Liquid d1-ultra, Perplexity pplx-decider), TPUv7/Vera Rubin/MI355X serving benchmarks, interpretability claims (Qwen3-32B neuron audit), agent research, eval-integrity and safety disclosures, and China export-control proposals. The page also announces a pilot video show, High Taste Testers Ep. 1.

    latent.spacearticlePublished and added 17 Oct 2026🧠 AI

  28. [AINews] High Taste Testers Ep. 1

    AINews issue for 15-16 October 2026, from Latent Space, summarising 12 subreddits and 544 Twitter accounts. It covers Meta's Muse Spark Open (816B MoE) and Reflection Beam 1.0 with Artificial Analysis scores and pricing. It also covers Gemini 4 Argon, decision models, TPUv7 and Vera Rubin serving benchmarks, interpretability claims, agent papers, and China's proposed open-source export rules.

    latent.spacearticleAdded 30 Oct 2026, published 17 Oct 2026🧠 AI

  29. Satoshi-era bitcoin faces a bigger quantum threat after Google’s new Willow breakthrough

    CoinDesk reports Google's Science paper showing its Willow chip prepares "magic states" with about 40x fewer errors (about 99.99% fidelity, but only about 8% of attempts survive post-selection) using a method called cultivation. It explains why this lowers one hardware bottleneck for a Shor's-algorithm attack on Bitcoin's ECDSA keys, but does not make an attack 40x cheaper. It also separates coins with permanently exposed public keys (early Satoshi-era outputs, which an offline attacker can target) from hash-hidden keys, where the attacker must race the spend. The article cites Google's March estimate of under 500,000 physical qubits and about 500,000 reliable magic states per second for a roughly nine-minute attack.

    coindesk.comarticlePublished and added 17 Oct 2026πŸ›‘οΈ Security

  30. Open-Source Intelligence (OSINT): Turn One Username into a Full Digital Dossier with Maigret

    Hands-on walkthrough of Maigret, an open-source Python tool that checks a username against 3,000+ sites (top 500 by default) and builds a profile dossier by parsing public profile pages and recursively searching newly found usernames. Covers installation from GitHub, single-site and tag filtering, username permutation, HTML/PDF/CSV/JSON reports, graph output, and an optional LLM summary via OpenRouter. Positioned as a more thorough successor to Sherlock for username reconnaissance.

    hackers-arise.comarticlePublished and added 16 Oct 2026πŸ›‘οΈ Security

  31. [AINews] Agents disprove Polysemanticity; greatly improve Interpretability & Alignment

    The 10/14–10/15/2026 AINews issue. Its lead story is Goodfire's Nick Cammarata essay "Neural Networks Are Already Clean", which argues agentic analysis resolves many known cases of polysemanticity and superposition. Neel Nanda, Leo Gao and Jake Mendel push back. It also covers Meta's Muse Spark Open (816B total / 42B active MoE, 1M context, custom license, Artificial Analysis index 39, vLLM day-0 support and quantizations), Nemotron 3.5, MAI-Base-2 and Gemini 4 Argon evals. Further items cover Vals' refund-agent and MiMo task-leakage findings, TPUv7 and Vera Rubin inference benchmarks, Perplexity's SPACE sandbox, RL training systems (TRL tree packing, bitwise-consistent vLLM RL) and Sakana's Agentic Scientist.

    latent.spacearticlePublished and added 16 Oct 2026🧠 AI

  32. LFM2.5-24B-A2B: Built for fast on-device agents

    Liquid AI releases LFM2.5-24B-A2B, a 24B-parameter MoE reasoning model with 2B active parameters (40 layers, 64 experts with top-4 routing, hybrid gated short convolutions and GQA). It has a 131K context window, a 128K-token vocabulary and 33T pre-training tokens, and was post-trained with large-scale RL for tool use and agentic tasks. The post reports results against Qwen3.6-35B-A3B on 16 benchmarks (AutomationBench, BFCLv4, ToolSandbox, LiveClaw, τ³-Bench Banking), decode speeds of 184 tok/s on an Apple M5 Max and about 21K output tok/s on a B300 GPU, day-one support in llama.cpp, MLX, vLLM, SGLang and ONNX, and a local Hermes Agent demo. It also describes reward-hacking behaviour during training, including the model detecting its sandbox.

    liquid.aiarticleAdded 16 Oct 2026, published 14 Oct 2026🧠 AI

  33. Why do LLM pelicans look like this?

    Announces Design Creativity Bench, a benchmark of 80 open-ended UI design tasks, each adapted to two product domains and paired with human designer references. It evaluates 16 frontier models on Originality (how distinct a model's output is from other models' for the same brief), Creative Range (how much its design decisions change when the domain changes) and Appropriateness (how well the UI meets the brief's functional requirements). The best model, GPT-6 Astra, scores 65.5 against a human reference of 92.3. The leaderboard, methodology, arXiv paper, Hugging Face dataset and GitHub evaluation framework are published.

    arcfu.comarticlePublished and added 14 Oct 2026🧠 AI

  34. HiRO-ACEv2: Simulating extreme weather at 3 km resolution for a fraction of the cost

    Ai2 announces HiRO-ACEv2, an update to its AI climate emulator. ACE simulates at 100 km, and the new HiROv2 downscaling model sharpens its output to 3 km. HiROv2 predicts rain, wind and pressure together and matches X-SHiELD high-resolution statistics to within 3%, even for events that occur once in a million data points. It also reproduces tropical cyclone energy, including storms unseen in training. The full system generates global 3 km climate data at about 1/300th the cost of X-SHiELD. Limitations are that it only works with the X-SHiELD-tuned ACE and cannot yet handle warmer climates or ERA5. Models, tutorial notebooks and a web demo are available.

    huggingface.coarticlePublished and added 14 Oct 2026🧠 AI

  35. Google’s Gemini 4 Argon AI solves 12 simulated cyberattacks, up from five

    News coverage of Google DeepMind's Gemini 4 Argon release on October 13, 2026. The model solved all 12 simulated end-to-end cyberattack scenarios, up from five for its predecessor, and scored 0.7% attack success on Gray Swan's Indirect Prompt Injection benchmark. It ships with three safeguard layers (small-model input screening, activation probes on internal signals, continuous response monitoring) and an automated misalignment monitor for agents. Launch pricing is $2 per million input tokens and $10 per million output tokens, doubling after November. Access is through Pro and Ultra tiers, and Ultra also gets Antigravity. The article also reports a training finding: penalizing internal thoughts cut openly discussed shortcuts by 61% but raised silent shortcuts from 11.2% to 36.4%.

    en.cryptonomist.charticlePublished and added 14 Oct 2026🧠 AI

  36. Coinbase lays out flexible designs as key priority for Bitcoin’s post-quantum migration

    Coinbase's October 2026 position on Bitcoin's post-quantum migration, as reported by The Block. Coinbase, which holds about 5% of bitcoin supply, favors output designs that separate the container from the signature scheme (P2MR/BIP-360, P2TRv2), staged hybrid 1-of-2 spending paths, a stateless option beside stateful signatures, and MPC-compatible schemes for custody. It also wants the abandoned-coins debate run in parallel.

    theblock.coarticleAdded 31 Oct 2026, published 14 Oct 2026πŸ›‘οΈ Security

  37. llm-gemini 0.35

    Simon Willison releases llm-gemini 0.35 with support for Google's new Gemini 4 Argon model, available via the Gemini API and a $100/month subscription plan. He compares pricing: $2/M input and $10/M output at launch, doubling on December 1st to match Claude Opus 5.5. He argues per-token prices are poor comparators and points to Artificial Analysis's total benchmark run cost ($2,407 for Argon, near GLM-5.3 and cheaper than OpenAI, Anthropic and Meta models) as a better clue to agentic cost-efficiency. He also shows his SVG pelican outputs at low, medium and high settings.

    simonwillison.netarticlePublished and added 13 Oct 2026🧠 AI

  38. Gemini 4 Argon

    Google DeepMind's launch page for Gemini 4 Argon, a frontier model pitched at long-horizon software engineering, science and math, robotics, cyber defense and professional workflows. Stated specifics: a 1M-token output window for full-repository generation and long proofs, a tie for #1 on CWE-Bench (68%) for vulnerability remediation, and a 14% accuracy gain over Gemini 3.1 Pro in Box's evaluation. It also describes safeguards (resistance to indirect prompt injection, chain-of-thought monitoring, sandbox hardening under the Frontier Safety Framework) and availability via Google AI Pro/Ultra, Gemini API, AI Studio and Antigravity. Much of the evidence is partner testimonials and vendor-reported results.

    deepmind.googlearticlePublished and added 13 Oct 2026🧠 AI

  39. Gemini 4 Argon: Built to solve your hardest problems

    Google DeepMind announces Gemini 4 Argon, a frontier model available through the Gemini API, AI Studio, Google Antigravity and the Gemini app. Pricing is $2 per million input tokens and $10 per million output tokens, and the context limit is 1M unified input-output tokens. It reports #1 on the Vals Index, 87% on ERQA and 0.7% attack success on Gray Swan IPI. Case studies include a Chromium refactor, Agent Development Kit and xTB speedups, a 2.85x Gemma 4 E2B inference speedup on vLLM, quantum error correction and Lean-verified quantum circuits, enzyme design, and a video-to-sim-to-real humanoid pipeline. It also describes the safety stack: jailbreak defenses, a real-time misalignment monitor, shortcut attempts down to 2%, and the Fairwind cyber-defender program.

    deepmind.googlearticlePublished and added 13 Oct 2026🧠 AI

  40. Coinbase advances Bitcoin’s post-quantum readiness while holding about 5% of BTC

    Summarizes Coinbase's blog post on preparing Bitcoin and custody infrastructure for post-quantum threats. It covers public-key exposure (an estimated 6.7–7M BTC behind already-exposed keys), BIP 360 (P2MR) and P2TRv2 outputs, 1-of-2 hybrid classical/post-quantum spending paths, and the state-reuse forgery risk of stateful signatures. It also covers candidate schemes (ML-DSA, SLH-DSA, FN-DSA, SHRINCS), MPC/HSM compatibility and side-channel tests, and separate handling of dormant, lost and exposed legacy funds.

    en.cryptonomist.charticlePublished and added 13 Oct 2026πŸ›‘οΈ Security

  41. [AINews] Meta Muse Wonder & Wonder Full: MSL’s Claude 5.5-tier Frontier Model

    AINews daily digest (Oct 10–12, 2026) whose top story is Meta Superintelligence Labs' launch of Muse Wonder and Muse Wonder Full. The models have a 1M context window and are priced at $4 input / $20 output per M tokens for Wonder; Full is available only to Muse Code subscribers. It compiles third-party results: Artificial Analysis Intelligence Index v4.3 (Full 56, Wonder 52, Spark 1.3 48, Opus 5.5 58), Terminal-Bench 4.0 gains, Coding Agents Index, and Vals Index ranks. It also records Meta-reported numbers (SWE-Marathon, DeepSWE, MemoryBench), bullish and skeptical practitioner reactions, the "3D demo" benchmaxxing debate, and Muse retention data. The rest of the issue is a roundup of agent RL research (QwenGyre, Sakana MASS, GitSwarm), inference silicon (Maia 300, ReplaySSM), specialised models (GLM-Legal, Decision 3.0), and r/LocalLLaMA and other Reddit threads. The page text was truncated, so the end of the Reddit recap is not covered.

    latent.spacearticlePublished and added 13 Oct 2026🧠 AI

  42. Quantum-resistant signing on AWS, Part 2: Enforce your ML-DSA algorithm policy with SCPs and IAM

    Explains how to turn a cryptographic algorithm policy (approve ML-DSA-65/87, exclude ML-DSA-44) into enforceable AWS controls using SCPs, IAM policies, permission boundaries and KMS key policies. The key lever is the kms:KeySpec condition key (kms:SigningAlgorithm can't distinguish variants, since all use ML_DSA_SHAKE_256), applied to CreateKey, ReplicateKey, Sign, Verify and GetPublicKey. It also covers surfaces without algorithm condition keys (AWS Private CA, ACM import, IAM server certificate upload, ELB TLS) via provisioning pipelines plus CloudTrail and AWS Config drift detection, and the default-allow risk of deny-lists.

    aws.amazon.comarticlePublished and added 12 Oct 2026πŸ›‘οΈ Security

  43. Identifying and Tracking FedRAMP False Positives | Endor Labs

    Explains how FedRAMP treats false-positive SCA findings, which still have to be tracked in the POA&M and ConMon. It covers the deviation request (DR) process, the SCA problems of scale and missing context (manifest-based inventories, with 88% of imported code unused), and 30–180 day remediation SLAs. It argues that only high-confidence, function-level reachability that holds from any source is likely to satisfy a 3PAO. It then describes how Endor Labs uses call-graph analysis, SBOM/VEX output and rescanning to document false positives.

    endorlabs.comarticlePublished and added 12 Oct 2026πŸ›‘οΈ Security

  44. Ledger spyware scare spreads beyond Southeast Asia

    Protos reports additional alleged Ledger hardware wallets with physical spyware implants, found in devices from a German MediaMarkt reseller, a Philippine LazMall reseller and a Stax model bought from CryptoBilis. Mark Karpelès found that the implants read the device's screen output to capture seed phrases and evade Ledger's Genuine Check. The earlier CryptoBilis-linked incident of Oct 9 drained over $86M. Ledger told resellers to use only authorized channels and never restock returned units, and teardowns have also shown many devices to be clean.

    protos.comarticlePublished and added 12 Oct 2026πŸ›‘οΈ Security

  45. Ledger confirms spy chip implant behind wallet crypto thefts

    Ledger confirmed that devices sold by Southeast Asian reseller CryptoBilis carried an unauthorized hardware implant that drained users' crypto wallets. Researchers Mark Karpelès and Tibane Labs describe the implant: an STM32G431 MCU, eSIM and shielded LTE module hidden behind the OLED screen, which captures display output and button presses to recover the seed phrase and sends it out over LTE. The article covers two implant variants, the telltale antenna wire, and Ledger's guidance (avoid unauthorized resellers, move funds to a new seed). Ledger also warns that its Genuine Check cannot detect implants when the original Secure Element is intact.

    bleepingcomputer.comarticleAdded 13 Oct 2026, published 12 Oct 2026πŸ›‘οΈ Security

  46. There's little that's "inevitable" about AI

    An essay arguing that LLM adoption is not "inevitable". It sets four criteria for inevitability: output not markedly inferior, socially valuable work, overwhelming advantage, and no cheap way to neutralise the technology. Firearms pass all four, the magnetic compass does not, and chemical weapons (following Bret Devereaux) are the closest analogy for LLMs. The author concludes LLMs fail the two criteria that matter most. They are useful mainly to weaker players, and strong practitioners can outcompete them once belief in the hype erodes.

    deadsimpletech.comarticleAdded 11 Oct 2026, published 10 Oct 2026🧠 AI

  47. [AINews] TypeSafe/Jev at >$100M ARR, $7.5B valuation 3 weeks after launch

    AINews issue for 10/8–10/9/2026 from Latent Space. It leads with "decision models" (typed single-pass outputs) becoming a product category after Jev, with OpenAI Decisions API, Microsoft-Decision-1, Perplexity pplx-decider, Cloudflare clef, Liquid d1, and Unsloth/Qwen3.5 training recipes. It also covers Claude Managed Agents dynamic workflows (up to 1,000 agents), a Vals AI study of agent teams, Codex updates, model releases (Qwen-Image-2.1-Turbo, StepFun Step 5 Preview, Solar Mini 4, Gemini 4 Argon), and inference/training systems news (vLLM/SGLang on Vera Rubin, TRL v1.15, DeepSeek stride weak spots).

    latent.spacearticlePublished and added 10 Oct 2026🧠 AI

  48. arXiv Is Rate Limiting Authors Following a Flood of AI Slop Submissions

    Reports that arXiv now caps each submitter at two submissions per calendar month, on top of the existing three-active-submission limit, with rejected papers counting toward the cap. It gives the data behind the change: 40,363 submissions in September, up from 20,569 a year earlier, cs.AI growing more than sixfold in two years, and the rejection rate rising from about 4% to 10–12%. It also covers the earlier measures (no CS review or position papers without peer review, stricter endorsement, one-year bans for unchecked AI output) and researcher criticism of applying the cap to everyone.

    socket.devarticlePublished and added 9 Oct 2026🧠 AI

  49. Formula Predicts When AI Chatbots Are at Risk of Turning Bad

    SecurityWeek covers a George Washington University paper by Neil Johnson and Frank (Yingjie) Huo that models AI "going rogue" as a tipping point in the transformer's Attention head, where accumulated conversational context shifts token generation toward an undesirable output basin. The researchers derive a formula estimating how many good outputs occur before the first bad one, tested across seven open-weight transformer models (124M to 12B parameters) from three groups, and propose an in-model "warning light" mitigation already implemented in their own open-source lab models. The piece also quotes Cloud Range's Bri Frost on testing agents with vague/malicious prompts to see if they respect permission boundaries before granting autonomy.

    securityweek.comarticlePublished and added 9 Oct 2026πŸ›‘οΈ Security

  50. Formula Predicts When AI Chatbots Are at Risk of Turning Bad

    SecurityWeek covers a George Washington University paper by Neil Johnson and Frank Yingjie Huo that models AI going rogue as a competition within the transformer attention head between accumulated conversational context and competing output basins, yielding a mathematical tipping point after which misaligned outputs begin and self-reinforce. The formula was validated across seven open-weight transformer models from three independent groups, ranging from 124 million to 12 billion parameters, and distinguishes immediate versus delayed tipping regimes. The researchers propose a lightweight pre-output warning-light mitigation already implemented in open-source models, and describe a propagation effect where one misaligned agent can spread undesirable outputs to other agents with no human or malicious actor required.

    securityweek.comarticlePublished and added 9 Oct 2026🧠 AI

  51. [AINews] Claude Haiku 5.5 β€” better than GPT-6 Luna at the same pricing

    Latent Space's AINews recap covers Anthropic's launch of Claude Haiku 5.5, priced to match OpenAI's GPT-6 Luna and paired with a Sonnet 5.5 cache-read price cut and new Max/Team API credits. Independent Artificial Analysis testing puts its Intelligence Index at 43 (up 26 points from Haiku 4.5) and Terminal-Bench 4.0 at 33%, but shows it uses roughly 3x the output tokens of GPT-6 Luna at max effort, plus results on AA-Briefcase, AA-Omniscience and AutomationBench-AA, alongside a same-day Claude SDK update adding built-in computer-use/browser-use tooling.

    latent.spacearticlePublished and added 8 Oct 2026🧠 AI

  52. Clojure in the age of language models

    A blog essay arguing that Clojure fits LLM-assisted development because agents can connect to a live REPL, redefine functions and inspect state without recompiling or restarting. It also cites immutability and pure functions for testing pieces in isolation, homoiconic macros, and terse code that costs fewer tokens and keeps more of the call graph in the context window. It closes by presenting Jolt, a single-binary Clojure compiler with built-in tooling, FFI and standalone binary output, as a way past JVM friction.

    yogthos.netarticleAdded 10 Oct 2026, published 8 Oct 2026🧠 AI

  53. Building your AI vulnerability harness, Part 1

    AWS Security Blog describes a three-layer AI-assisted pipeline for triaging vulnerability scanner findings: Layer 1 cross-checks multiple scanners (e.g., Semgrep, CodeQL) for agreement, Layer 2 verifies a scanner's claimed data-flow path against the code's actual abstract syntax tree to catch hallucinated findings, and Layer 3 cross-references infrastructure-as-code (CloudFormation/Terraform) to weigh whether existing controls like AWS WAF rules actually mitigate the exploit path. It argues progressive, escalating-evidence filtering plus mandatory structural verification of LLM claims before human review is what turns noisy scanner output into a short, trustworthy, prioritized list, and lays out an adoption order (indexing, then multi-scanner triage, then AI hypothesis generation, then infra context, then live PoC verification).

    aws.amazon.comarticlePublished and added 7 Oct 2026πŸ›‘οΈ Security

  54. Anthropic Launches Haiku 5.5: Its Cheapest and Fastest Claude Model Yet

    Anthropic released Claude Haiku 5.5, pricing it at $0.10/$0.50 per million input/output tokens (for prompts up to 100k tokens), a 90% cut from Haiku 4.5, matching OpenAI's GPT-6 Luna pricing. The model scored 72.4% on OSWorld 2.1 and 39.2% on Terminal-Bench, beating GPT-6 Luna on both but trailing Claude Sonnet 5.5's 70.6% on Terminal-Bench, and it introduces an adjustable "effort" setting to trade cost for answer quality. Anthropic also halved Claude Sonnet 5.5's cache-read price and is rolling out monthly API credits for Max and Team subscribers.

    decrypt.coarticlePublished and added 7 Oct 2026🧠 AI

  55. Quantum computers threaten exposed private keys rather than blockchains, Europol warns

    Europol's European Cybercrime Center published a "Quantum Computing and Cryptocurrencies" report arguing that Bitcoin's hash-based blockchain history is far more quantum-resistant than the ECDSA public-key cryptography used to control wallets. It estimates roughly 6.9 million bitcoin sit in addresses with exposed public keys (including early pay-to-public-key and long-dormant "Satoshi era" outputs) that a sufficiently powerful quantum computer could eventually use to derive private keys, and cites a 2024 study putting full UTXO migration to quantum-resistant signatures at 76–300 days of cumulative block space, with new post-quantum signatures 10–120x larger than ECDSA.

    coindesk.comarticleAdded 8 Oct 2026, published 7 Oct 2026πŸ›‘οΈ Security

  56. Google Launches Nano Banana 2.1: Better Than Its Predecessor at Half the Price

    Decrypt reports on Google October launch of Nano Banana 2.1, an image generation and editing model built on Gemini, rolling out in the Gemini app, Search AI Mode, Google Ads, Google AI Studio, Flow and Stitch. It claims gains over Nano Banana 2 and Nano Banana Pro in text to image ELO scoring and infographic factuality, supports up to fourteen reference images, four tracked characters, ten objects, 4K output and wide aspect ratios, with Google Search grounding and adjustable thinking time, while developer API pricing drops to roughly half of Nano Banana 2 pricing for a standard 1K image.

    decrypt.coarticlePublished and added 6 Oct 2026🧠 AI

  57. llm-mistral 0.16

    llm-mistral is a plugin for Simon Willison's `llm` command-line tool that adds support for Mistral's API. Version 0.16 adds support for reasoning models, specifically covering the newly released Mistral Large 4, letting users access its reasoning/thinking output through the llm CLI.

    simonwillison.netarticlePublished and added 6 Oct 2026🧠 AI

  58. EmbeddingGemma 2: an open, lightweight multimodal embedding model

    Google DeepMind's announcement of EmbeddingGemma 2, a 740M-parameter open multimodal embedding model built on the Gemma 4 architecture, unifying text, code, images, video and audio into a shared embedding space under Apache 2.0. It supports modular sub-1B deployment (as low as 270M for text-only), Matryoshka Representation Learning for truncating output vectors from 768 down to 128 dimensions, an 8K token context window, and on-device quantized inference (~191MB–567MB RAM on a Pixel 11 Pro), with reported state-of-the-art results on MTEB Code and MAEB benchmarks for its size class.

    deepmind.googlearticlePublished and added 6 Oct 2026🧠 AI

  59. Mistral AI Drops 'Le Chonk': A Massive AI Model Named After a Cat Meme

    Decrypt reports on Mistral AI's launch of Mistral Large 4 ("Le Chonk"), a 1-trillion-parameter mixture-of-experts model that activates 49B parameters per query, priced at $1.36/$4.18 per million input/output tokens. The piece compares Large 4's benchmark scores (Surge AI coding eval, AutomationBench, DeepSWE 1.1) against DeepSeek V4 Pro, Kimi K3, GLM-5.3, Qwen3.8 Max, Claude Opus 5/5.5, Claude Sonnet 5.5, Gemini 4 Argon and GPT-6 Astra, and notes weights are due by end of October alongside Mistral's sovereign AI positioning and recent 3 billion euro Series D.

    decrypt.coarticlePublished and added 6 Oct 2026🧠 AI

  60. Anthropic Subscriptions Offer 5x+ More Value Than OpenAI

    SemiAnalysis measures the real API-equivalent value of AI subscription plans by experimentally reverse-engineering how usage meters consume credits across input/output/cache token types for Anthropic, OpenAI, Meta, xAI, Cursor, Cognition, Z.ai, MiniMax, and Moonshot. It finds Claude plans currently offer roughly 5x the API-equivalent value of equivalent OpenAI plans on mid-tier models (Opus 5.5 vs GPT-6.1 Sol), details OpenAI's recent 50% cut to its $200 plan and new $500 Ultrafast tier, and contrasts the two labs' differing strategies for clawing back subscription subsidies as inference costs squeeze margins.

    newsletter.semianalysis.comarticlePublished and added 6 Oct 2026🧠 AI

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