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AI News — Daily Top 5

UPDATED 2026-11-03 00:15 PST

2026-11-01 · SUNDAY · 21:17 PST

  1. 1 Police scanned 1.38 million faces in a five-month facial recognition trial in Western Australia THE GUARDIAN Western Australia Police said a five-month trial of real-time facial recognition that ended Saturday scanned 1,380,882 faces over 100 deployments at 43 locations, producing 122 arrests and nine incorrect alerts. Police put the error rate at 0.00065 percent, and Commissioner Col Blanch said nobody was arrested on a false match. Civil Liberties Australia's Bill Rowlings said it should be measured against convictions.
  2. 2 Singapore data center operator STT GDC is in talks for a S$3.1 billion syndicated loan BLOOMBERG Singapore-based data center operator STT GDC Pte. is in talks with banks over a S$3.1 billion syndicated loan, about $2.4 billion, Bloomberg reports, citing people familiar with the matter. It frames the deal as another sign that the AI boom keeps driving demand for debt among the companies building the infrastructure behind it.
  3. 3 Patches run eight 250K-context agents on two 3090s by reading one percent of the tokens each step GITHUB · VIA R/LOCALLLAMA · DISCUSSION A developer published sparsekv-hyperqwen, vLLM patches that hold each agent's whole key-value cache in system RAM as int4 and at each decode step pick about one percent of tokens with a rank-64 key sketch. Eight Qwen3.8-27B agents at 176K to 205K context averaged 657 tokens a second on an RTX 3090 Ti plus a 3090. The author notes the attention is approximate and a kernel module roughly doubled 3090 throughput.

2026-11-01 · SUNDAY · 18:15 PST

  1. 1 A Strata fork cuts a new DeepSeek V4.1 agent session from 100 seconds to 5 on a 16GB card GITHUB · VIA R/LOCALLLAMA · DISCUSSION A developer forked the Strata inference engine so agent sessions stop re-reading their whole system prompt. The patch splices a new prompt against saved conversation state, and while reading a prompt it routes tokens only to experts already in VRAM or RAM. On an RX 9070 XT a new OpenCode session on DeepSeek V4.1 Flash falls from about 100 seconds to 5, and SSD traffic for a 1.2K-token prompt from 58GB to 1.3GB.
  2. 2 A 4B Qwen3.5 finetune writes Three.js scenes and exports them as GLB assets for Godot HUGGING FACE · VIA R/LOCALLLAMA · DISCUSSION A developer published Qwen3.5-4B-GLB-3D-Coder, a 4B finetune that answers a plain request such as 'create a mana potion' with a Three.js scene it exports as a GLB file for import into Godot and other engines. Only Q4_K_M and Q8_0 GGUF files are posted. The author calls this the first functional checkpoint, with training still running and the full weights and dataset promised when it ends.
  3. 3 An OpenBSD developer packages a local LLM, image generation and web search as four containers SOLENE RAPENNE · VIA LOBSTERS · DISCUSSION Solene Rapenne released braindead-local-intelligence, which starts an OpenAI-compatible LLM server, an image generation server, SearXNG and Open WebUI as rootless podman containers behind a single token-protected address. Only one model sits in memory at a time: the right one loads when a request arrives and unloads after a few idle minutes. It targets AMD cards and was tested up to 12GB of VRAM.

2026-11-01 · SUNDAY · 15:17 PST

  1. 1 OpenAI's policy chief floats rebranding data centers as 'AI compute campuses' TECHCRUNCH Axios reports that OpenAI is preparing a public affairs push for after Tuesday's US midterm elections, and chief global affairs officer Chris Lehane listed proposals including AI 'speed limits', a US role in setting global standards, and renaming data centers 'AI compute campuses'. Lehane called the midterms a movie trailer for 2028, when he expects AI to be the election's main issue.
  2. 2 tandem.cpp keeps hot MoE experts on the GPU and triples Qwen3.8-Flash-Next decode on a 4090 GITHUB · VIA R/LOCALLLAMA · DISCUSSION tandem.cpp is a patch set for llama.cpp that pins a mixture-of-experts model's most-used experts in VRAM and lets the CPU handle the rest. On an RTX 4090 with 64GB of DDR4, the author reports Qwen3.8-Flash-Next IQ3_S decoding at 97.3 tokens a second against 29.8 for llama.cpp, and 1.4x to 2.1x on other MoE models. The figures are self-reported, and Strata's exact mode scored 103.6.
  3. 3 llama2.c runs on a 2006 iPod at 80 MHz with no floating-point unit R/LOCALLLAMA A developer wrote a Rockbox plugin that runs Karpathy's llama2.c TinyStories models on a fifth-generation iPod video, an 80 MHz ARM7TDMI with 64MB of RAM and no floating-point unit. The port rewrites llama2.c's int8 runq.c in integer math only, using lookup tables for exp and softmax and an integer square root for RMSNorm. The 15M model is 17MB and loads off the hard drive into the music buffer.
  4. 4 National Grid buys 73 acres on Teesside for what could be Britain's biggest substation THE GUARDIAN National Grid agreed last week to buy 29.5 hectares at Dorman Point on the Teesworks site for a substation that could power a neighbouring AI datacentre, a deal first reported by Sky News. Tees Valley mayor Ben Houchen said up to 3.2GW of capacity would let the region compete for investment going to the US and the Gulf. The government published a draft national policy statement on datacentres last week.
  5. 5 Silencio-2 is an 18M-parameter open TTS model that follows emotion and sound tags HUGGING FACE · VIA R/LOCALLLAMA · DISCUSSION Silencio-2 is a fine-tune of Kyutai's Pocket TTS that reads inline tags such as sigh, laugh and whisper, with CC-BY-4.0 weights and MIT code. It is 18.2M parameters for speech and 112MB on disk, and the author measures about 20x realtime on an Apple M4 CPU, calling that one run rather than a benchmark. The writeup details how an AudioSet filter silently dropped every laugh and cough from the training data.

2026-11-01 · SUNDAY · 12:16 PST

  1. 1 Frontier UI renders ChatGPT-style cards, maps and routes inside Open WebUI chats GITHUB · VIA R/LOCALLLAMA · DISCUSSION A developer published Frontier UI, a single-file MIT tool that gives any model in Open WebUI generative interface replies instead of markdown. The model writes a small JSON spec and the server finds photos from Wikipedia and Openverse, verifies places and draws real street routes on MapLibre tiles. Cards also carry budget sliders, keyless weather and market charts, and exports to Word, Excel or PDF.
  2. 2 A recipe runs Qwen3.8-27B with a DFlash2 draft at 177 tokens a second on an RX 7900 XTX GITHUB · VIA R/LOCALLLAMA · DISCUSSION A new repository publishes the patches, scripts and raw numbers for running Qwen3.8-27B as EXL3 4.00bpw with a DFlash2 speculative draft on an AMD RX 7900 XTX, through a ROCm port of exllamav3. With thinking off its median is 177 tokens a second on code and 75 on prose, at about 1,100 tokens a second of prefill and 131k context. That is roughly 70 percent of the same weights on a CUDA RTX 3090.
  3. 3 LFM3-1.7B is measured at 78 tokens a second on a Strix Halo integrated GPU R/LOCALLLAMA A user testing Liquid AI's LFM3-1.7B as a Q8_0 GGUF under llama.cpp with ROCm reports 4,100 tokens a second of prefill and about 78 tokens a second of decode on a Strix Halo integrated GPU. Tensor-splitting the model across a Radeon 7900 XTX and a 7900 XT raises that to roughly 7,100 and 151. They say it stays coherent on 32k to 64k prompts, the size they want for compression and summarization work.

2026-11-01 · SUNDAY · 09:16 PST

  1. 1 Infernix adds a WebUI launcher and auto-calibrated speculative decoding for Qwen3.8 GITHUB · VIA R/LOCALLLAMA · DISCUSSION Infernix, a single-GPU C++/CUDA engine for Qwen3.8 models that grew out of NInfer, shipped a release adding a beta WebUI launcher with model downloads and a switching API, speculative decoding that calibrates its own settings, and a bit-exact lossless mode. Posted figures put it ahead of Strata on first-token latency and behind Basalt on decode, which its author attributes to precision-cutting defaults it leaves off.
  2. 2 An EPYC rebuild lifts GLM-5.3-Flash decode from 9.7 to 41 tokens a second on the same GPUs R/LOCALLLAMA An r/LocalLLaMA user moved from a Core Ultra 7 desktop with 64GB of dual-channel DDR5 to a 24-core EPYC 7443 board with 256GB of eight-channel ECC DDR4, keeping the same consumer cards. GLM-5.3-Flash decode rose from 9.7 to 41.0 tokens a second and DeepSeek-V4.1-Flash from 9.3 to 35.2, because 30 to 60 percent of each model had been read from NVMe on every token before. Dense models gained nothing.
  3. 3 LeCun and Balestriero prove the Platonic Representation Hypothesis holds for JEPAs ARXIV · VIA R/LOCALLLAMA · DISCUSSION Randall Balestriero and Yann LeCun proved that joint-embedding predictive architectures trained separately on different modalities learn the same representation up to one rotation, given positive pairs that are two views of one scene. Such views reach the same alignment with 42 times fewer training samples than next-token prediction, and a 109M-parameter text JEPA beat every language model they tested, up to 72B.
  4. 4 Rented dual-EPYC servers hold near-linear throughput for Qwen3.8-Flash-Next across 8 streams R/LOCALLLAMA A local-model user spent about $40 on vast.ai instances to benchmark dual EPYC 7642 ROME boards with 251GB and 504GB of DDR4 and two RTX 3090s. Running an Unsloth Q8 build of Qwen3.8-Flash-Next on Strata at 124k context, throughput scaled almost linearly to at least eight concurrent streams, from 94 tokens a second at one to 456 at eight. GLM-5.3-Flash and DeepSeek-V4.1-Flash on Maya did not hold past one stream.

2026-11-01 · SUNDAY · 06:15 PST

  1. 1 AI is turning First Nations art into 'Temu slop', a National Gallery adviser says THE GUARDIAN Sally Scales, the Pitjantjatjara artist who chairs the National Gallery of Australia's First Nations advisory group, said AI is turning Indigenous art into 'Temu slop' and called it a theft of cultural knowledge and of the artist's agency. The visual arts body Nava told a parliamentary AI inquiry that scrapers strip artists' names and alter their work before it is sold.
  2. 2 Heretic 2.0 swaps abliteration for an arbitrary-rank method and becomes a general model editor GITHUB · VIA R/LOCALLLAMA · DISCUSSION Heretic, a censorship-removal tool with 37,000 GitHub stars, released version 2.0 after five months of work. It replaces directional abliteration with Arbitrary-Rank Ablation, which drops the assumption that refusals occupy a single direction in residual space, and rebuilds the tool around scorer and modifier plugins so it can also suppress slop or sycophancy. Configurations from 1.x are not compatible.
  3. 3 A two-card R9700 build finds Strata on Flash-Next trailing a 27B Q8 on llama.cpp R/LOCALLLAMA A local-model user set out to replace Qwen3.8-27B at Q8 with a longer-context setup and reported Strata on Qwen3.8-Flash-Next falling short on two Radeon R9700s. Offloading experts to RAM hung on long tasks, so only a 3-bit quant fit the 64GB of VRAM; it was faster on paper at about 60 tokens a second but scored 93.9 percent on HumanEval+ against 95.1, using nearly twice the tokens.
  4. 4 An engineer runs self-hosted GLM-5.3-Flash as the coder with GPT-6.1 Sol orchestrating AAYUSH GARG · VIA R/LOCALLLAMA · DISCUSSION An engineer deployed GLM-5.3-Flash, a 320-billion-parameter mixture of experts with 18 billion active, on four local H200s at a 512k context window, then made it the subagent that explores and writes code while GPT-6.1 Sol plans and reviews. The write-up says neither Claude Code nor Codex lets one session mix providers across subagents, so the setup runs on OpenCode.

2026-11-01 · SUNDAY · 03:13 PST

  1. 1 Five Qwen3.8-27B agents reproduce a published coding harness as eight YAML files, with all 50 runs posted GITHUB · VIA HACKER NEWS · 251 PTS · DISCUSSION A Memdoor example reimplements the GVS5H method - a planner, two ideators, a solver and a manager that talk only through files on disk - as eight YAML files with no code. On the first 10 problems of the authors' LiveCodeBench Hard list, five passes each, it averages 9.8 of 10 against their own harness at 9.6 and 8.0 for a single Fable 5 call. The author calls that parity, not a gain, and publishes all 50 runs.
  2. 2 Hugging Face opens FineDNA, the training data behind its Carbon-X genomics model HUGGING FACE · VIA R/LOCALLLAMA · DISCUSSION Hugging Face's bio team released FineDNA, the data it used to turn Qwen3-14B into Carbon-X, which it calls the strongest open language model on DNA. The Apache-2.0 release holds more than 300 billion tokens of genomes and DNA-rich text for midtraining, about 200,000 SFT conversations and about 98,000 verifiable RL prompts. The code and recipe are open too, so the pipeline can be applied to other models.
  3. 3 DeepSeek releases a prototype coding agent that opens its own work items and answers with pull requests BLOOMBERG DeepSeek has published dsh-superagent, a research prototype of a more autonomous coding agent aimed at Anthropic's Claude Code. It watches one GitHub repository and optionally Feishu, opens a work item when an authorized person asks, works in its own agent session and answers in the original thread with a pull request. DeepSeek calls it reference-only research code, not its internal version.
  4. 4 A 16GB Qwen3.8 27B quant takes 48GB on a 64GB Mac once an agent session reaches 164k tokens R/LOCALLLAMA A developer running Qwen3.8 27B as a coding agent on a 64GB M4 Max reports LM Studio's engine process sitting at 48GB once a session reaches 164k tokens, against 16GB of weights. About 11GB is KV cache and the rest a second copy of the context for the prompt cache plus MLX scratch memory, leaving roughly 150MB free. The prompt cache hits 93 percent, so a miss costs a full 20-minute prefill.
  5. 5 A Pokemon Red benchmark logs Grok 4.20 describing its own loop for hundreds of turns without escaping it R/LOCALLLAMA The author of PokeBench, which has vision models play Pokemon Red, says Grok 4.20 without reasoning left the first house on turn 36 but did not reach a starter Pokemon until turn 755. Its own notes record oscillating uselessly for 90-plus turns and walking into walls for hundreds of turns, then it walks into a wall again. The author reports Grok 4.6 beat Brock in 316 turns for about $10, while 4.20 spent $30.

2026-10-31 · SATURDAY · 18:19 PDT

  1. 1 A researcher says Anthropic flagged their account for training a competitor and restricted their model access JIAHAO SHAO ON X · VIA HACKER NEWS · 173 PTS · DISCUSSION Jiahao Shao, a computer science PhD student at HKUST, posted on X that Anthropic tagged their account for training a competitor and now blocks work touching reinforcement fine-tuning, supervised fine-tuning or training larger models. Shao denies distilling Claude, says the rollouts came from an open-source model, and reports sessions being killed or downgraded from Opus 5.5 to Opus 5.
  2. 2 CrowdGPT adds Byzantine cross-checks after commenters found volunteers could poison the model GITHUB · VIA R/LOCALLLAMA · DISCUSSION CrowdGPT, which trains a 1B-parameter model on volunteers' home GPUs rather than in a data center, shipped v2.6 after commenters found clients could fake contributions, poison the model or plant backdoors. Three clients now train on identical data and cross-check each other, capping a malicious client at 2 to 3 percent poisoned data per round, and client builds are signed to close an auto-update code execution path.
  3. 3 A language model that lives in a 512-byte boot sector dreams up fake Linux boot logs GITHUB · VIA HACKER NEWS · 52 PTS · DISCUSSION A developer published bootgpt, a 510-byte master boot record in hand-written assembly that loads an 11.5 KB int8 model from the next 23 sectors and runs it in 16-bit real mode with no operating system. The model is char embeddings and one hidden layer, quantized with power-of-two scales so inference needs only imul and one idiv, and it prints invented kernel timestamps and PCI lines.
  4. 4 Two weeks of agent logs put INT4 AWQ 14 points behind INT8 on task success R/LOCALLLAMA A developer compared about two weeks of heavy agent logs from each of two Qwen3.8 27B deployments, INT8 on four RTX 3090s and AWQ INT4 on two, keeping the same harness, sampling and loop detector. Per-task success fell from 92 to 78 percent and reasoning loops rose from 1.9 to 4.7 per 1,000 calls, with the INT4 gap widening from 1.4 times under 40k tokens of context to 3.3 times at 80k to 120k.
  5. 5 Moving the desktop to an integrated GPU frees enough VRAM for 110k context on a 16GB card R/LOCALLLAMA An r/LocalLLaMA user reported running an 11.8GB 4.2-bit Qwen3.8 27B build at about 55 tokens a second on a 16GB RTX 5070 Ti, holding 110k of context with roughly 1.5GB spare. Context above about 60k had fit only intermittently until enabling the motherboard's hybrid graphics so the 9800X3D's integrated GPU drives the displays, freeing the 600 to 800MB that Xorg alone was holding.

2026-10-31 · SATURDAY · 15:12 PDT

  1. 1 Apple's John Ternus says the company will not ship AI for AI's sake TECHCRUNCH Apple chief executive John Ternus defended the company's AI position in an interview with Wired's Steven Levy, saying he likes where Apple is at and that it will leverage AI without shipping it for its own sake. Asked whether agents could make apps unnecessary, he said creating products is a deeply human and personal thing. Ternus became chief executive in September.
  2. 2 A judge lets the NAACP's Clean Air Act case over xAI's Colossus turbines proceed TECHCRUNCH Judge Debra M. Brown denied xAI's motion to dismiss an NAACP suit alleging the company ran at least 35 combustion turbines at its Colossus data center outside Memphis without the required air permits. She rejected arguments that the turbines are mobile sources, that the plaintiffs lack standing, and that citizen suits violate Article II. A separate ruling in October had blocked the EPA from ending the case.
  3. 3 QwenPU runs Karpathy's stories260K on a vector unit compiled into Qwen3.5-4B's weights GITHUB · VIA R/LOCALLLAMA · DISCUSSION The developer behind Qwenputer, which put a working CPU inside a stock Qwen3.5-4B checkpoint, has compiled a vector unit into the same weights and run Andrej Karpathy's 260K-parameter stories model on it. The small model's weights sit in Qwen's own memory with no external tools, and the author says its matmuls, softmax and attention are bit-exact. A full writeup is still pending.
  4. 4 Artists in Albanese's own electorate organise against Australia's AI copyright plan THE GUARDIAN Creatives in the prime minister's Sydney seat of Grayndler are pushing back against a federal proposal that would let AI companies train on Australians' work by default, the Guardian reports. The seat holds more than 3,000 cultural and creative businesses, and 10 percent of its workers are in creative fields against 4.2 percent nationally. Draft laws are due by year's end, for parliament in 2027.
  5. 5 GPT-5.6 Sol completes a peaceful Factorio run in 13.5 hours of game time RYAN MADDEN · VIA HACKER NEWS · 130 PTS · 134 COMMENTS · DISCUSSION Ryan Madden ran GPT-5.6 Sol in Codex at a low thinking level against a biter-free Factorio save, driving the game through a Python library that enforces the reach and fog-of-war limits human players face. It reached a rocket launch, though Madden says late-game failures to connect production systems were papered over by ferrying supplies by hand. Earlier GPT-5.5 attempts never used belts at all.

2026-10-31 · SATURDAY · 12:15 PDT

  1. 1 A Verge editor turned a $50 Waveshare devkit into a Muse Charm clone with Claude Code THE VERGE The Verge's Sean Hollister paid $50 for a Waveshare ESP32-S3 pendant, one of the devkits Meta suggests for building a Muse Gadget, and found it did little out of the box. Successive Claude Code sessions added a conversation history page, an ElevenLabs voice, a remote camera shutter and a Tamagotchi-style pet minigame. Meta's own build shipped a single avatar and no smart home discovery.
  2. 2 Arca's head of AI details a custom harness and persistent memory behind multi-day finance agents LATENT SPACE Latent Space published an interview with Aman Singh, head of AI at wealth management firm Arca, recorded with editorial head Richard MacManus at AI Engineer New York. Singh describes an AI-native firm built on a custom agent harness and persistent memory, running agentic workflows that span days. He frames the pattern as agents prompting people rather than the reverse.
  3. 3 An open reference publishes V100 SXM2 pin maps and NVLink wiring plans for DIY carrier boards R/LOCALLLAMA A new repository collects connector pin mappings for NVIDIA's V100 SXM2 modules, two- and four-GPU NVLink connection plans, and connector-only KiCad starter schematics, licensed under CERN-OHL-W and CC BY-SA. The author credits existing community research and calls it an early release, with power, clock and control circuits still to be designed. The stated goal is an open-source carrier board.
  4. 4 llama.cpp v0.8.0 adds DFlash2 for Qwen3.8-Flash-Next, measured 17 percent faster than MTP HUGGING FACE · VIA R/LOCALLLAMA · DISCUSSION A user quantized DFlash2 draft heads for Qwen3.8-Flash-Next and benchmarked them on llama.cpp v0.8.0, the first release that supports the drafter for that model. Across code, list, prose and long-context prompts the geometric mean rose from 75.1 to 87.9 tokens a second, with prose the one regression at -3 percent. The Q4_0 draft head is about 350MB against 2.2GB for the MTP head it replaces.
  5. 5 A temperature sweep puts greedy decoding 12.7 points behind temperature 1.0 on hard coding problems R/LOCALLLAMA An r/LocalLLaMA user ran Qwen3.8 at IQ4_XS-M through the 100 hard problems in LiveCodeBench v6 at five temperatures, holding top_p, top_k and min_p fixed. Pooled accuracy rose from 70.0 percent at temperature 0 to 82.7 percent at 1.0, and the share of answers that fell into loops dropped from 9 percent to 0.3 percent. Recall scores on GPQA Diamond were unaffected.

2026-10-31 · SATURDAY · 09:14 PDT

  1. 1 An engine's default lossy offload flags cost a Q8 pack more accuracy than 2-bit quantization R/LOCALLLAMA Basalt's developer measured two lossy flags engines ship by default on small cards, biasing routing toward experts already in VRAM and skipping uncached low-ranked experts, on Qwen 3.8 Flash Next. At the shipped values a 178 GiB Q8_0 pack scored a worse KL divergence than an exact 65 GiB Q2_0. A task eval put the cost near 1.5 points with ample VRAM and 5.2 points on chained reasoning with the expert cache capped.
  2. 2 Betelgeuse runs a 68GB expert build on a 12GB RTX 3060 at 22 tokens a second R/LOCALLLAMA A developer released Betelgeuse, a llama.cpp fork that streams routed experts from NVMe into a bounded VRAM slot pool backed by a RAM victim cache. He reports 22 tokens a second of warm decode on a 68GB Qwen 3.8 Flash Next build using an RTX 3060 12GB and 16GB of DDR4, against 1.47 for stock llama.cpp and 8.11 for Strata on the same box, with output byte-exact and no experts dropped.
  3. 3 A Match Group survey finds 39 percent of British singles have used AI in their dating lives THE GUARDIAN A survey of 3,000 British singles published this month by Match Group, the owner of Tinder and Hinge, found 39 percent had used AI in their dating lives, from drafting messages to assessing potential partners. Use rises to 66 percent among gen Z and 53 percent of millennials. One user told the Guardian he relies on it for pep talks and to vet his messages, while saying he would rather date in person.
  4. 4 Executives at about 50 companies say Meta's Muse has barely touched their sales WIRED Wired asked executives at roughly 50 companies in travel, telecoms, food and self-storage how far Meta's Muse agent has reached their business, and found almost no measurable effect. T-Mobile said it has seen nothing of significance, Hilton called agent bookings insignificant, and Life Time Group reported zero agent-driven cancellations. Chipotle said Muse's debut lifted agentic orders by a single-digit percentage.
  5. 5 A llama.cpp crash on Gemma 4 traced to context checkpoints filling system RAM JOSE M · VIA R/LOCALLLAMA · DISCUSSION Jose M traced a llama.cpp crash while stress testing Gemma 4 12B to system RAM rather than VRAM, and found context checkpoints behind it. For sliding-window models llama.cpp keeps 32 checkpoints per slot by default at about 320MiB each, which overran his 16GB of RAM. He writes that four were enough for simple chat continuation.

2026-10-31 · SATURDAY · 06:13 PDT

  1. 1 Cisco Talos finds an infostealer that sends each victim's stolen data to a language model WIRED Cisco Talos has documented Volta-Autodoxer, an infostealer carrying a 240-word prompt that tells a model to act as a forensic intelligence analyst and write a target assessment from the data it harvests. Requests go out through OpenRouter, defaulting to Claude Opus 4.6 with fallbacks to Kimi K2 and Gemini 2.5 Flash if guardrails refuse. Talos says it did not track whether the malware has been used in the wild.
  2. 2 Microsoft releases Mage-VL-Cowork, a 4B agent that chooses between clicking and the shell HUGGING FACE · VIA R/LOCALLLAMA · DISCUSSION Microsoft published Mage-VL-Cowork, an Apache-2.0 vision-language model of 4 billion parameters that handles screenshot-driven GUI actions and a persistent bash shell in one policy, with no external router. Its card reports 66.0 percent on OSWorld-Verified under a 50-step budget, which Microsoft calls the best at that scale. The team says online reinforcement learning added 10.16 points over hybrid fine-tuning.
  3. 3 An AI agent picked a gene therapy and injected it into a live mouse's brain WIRED Exin Therapeutics cofounder Gabriel Ocana Santero wired an agent to a custom surgical rig, where it chose one of 19 candidate therapies, set the brain region and coordinates, and drove the needle and injector after a veterinary surgeon had performed the craniotomy. Santero says Claude Opus 5.5 refused to guide the needle, so the team used Claude Sonnet 5. A human approval step and a motor kill switch stayed in place.
  4. 4 KoboldCpp v1.124 pulls in audio.cpp, adding the YuE2 music model and 17 speech models GITHUB · VIA R/LOCALLLAMA · DISCUSSION KoboldCpp's v1.124 release integrates part of the audio.cpp project, bringing the YuE2 music generation model with three ready-made templates and 17 ported text-to-speech models, most of them supporting voice cloning or spoken instructions. The same build syncs sd.cpp for new image models, adds an MCP setup wizard to the bundled agent, and enables CUDA graphs across all architectures.
  5. 5 Unsloth says ISTA's quant scores do not reproduce, and ISTA blames the reasoning budget R/LOCALLLAMA · DISCUSSION Unsloth released Dynamic v3.1 GGUFs of DeepSeek-V4.1-Flash-1017 with benchmarks against ISTA-DASLab's GSQ-RCO builds, saying ISTA's reported 100 percent AIME25 accuracy recovery came out near 91.88 percent in its own runs, averaged over 16 attempts. ISTA replied that it altered no hyperparameters and that the gap is a benchmark constraint: Unsloth capped reasoning at 32K tokens where ISTA allows 128K.

2026-10-31 · SATURDAY · 03:15 PDT

  1. 1 A lawyer runs DeepSeek-V4.1-Flash across two DGX Sparks at 2,618 tokens a second of prefill R/LOCALLLAMA Nick Mermiges of PLI Labs ran DeepSeek-V4.1-Flash-1017 at 2.75 bits per weight under vLLM tensor parallel across two DGX Sparks, with a third EPYC box serving the Engram tables over RDMA and running a speculative drafter on two 3090s. Prefill held 2,618 tokens a second at 256K context and structured JSON output reached 322 across four streams. He says the build loses on plain prose, 66 against a rival's 80.7.
  2. 2 A 1,200-sample rerun of Cohere's Qwen trace never reproduces the Beijing bucket R/LOCALLLAMA Mark Galyan resampled Cohere's published trace 1,200 times, cut just before the upload address, across Unsloth 2-bit and 4-bit builds of Qwen3.8-Flash-Next. The model wrote some address almost every time but never Cohere's Beijing bucket, and the 4-bit file chose localhost 32.5 percent of the time. Moving five layers from system RAM onto the GPUs cut probes of Alibaba's metadata address by about two thirds.
  3. 3 Ollie, a privacy-focused AI assistant backed by Khosla Ventures, shuts down on November 6 TECHCRUNCH Co-founder and chief executive Bill Lennon said on X on Friday that Ollie will close in a week, on November 6. The subscription assistant connected to a user's email and calendar to book appointments, plan meals and pay bills, and discussed a $7.5 million seed round led by Khosla Ventures with TechCrunch in September. TechCrunch calls it one of the first mainstream apps to pass a SOC 2 audit.
  4. 4 United's chief executive says Boom's 2029 supersonic target will slip as it builds data center turbines ARS TECHNICA United Airlines chief executive Scott Kirby said on a podcast released October 28 that Boom Supersonic's official 2029 date for its first Overture airliner is not going to happen. Boom unveiled a Colorado factory on October 22 for a 42-megawatt gas turbine called Superpower, aiming to ship the first units to AI data centers in mid-2027 and 50 a year by 2029. Its Overture plant has sat mostly idle since 2024.
  5. 5 OpenAI publishes court brief excerpts arguing that fair use supports AI training OPENAI BLOG OpenAI published a post collecting excerpts from court briefs by creators, academics, accessibility advocates and legal experts on how fair use supports AI training. It lands in the copyright fight led by The New York Times, where the Justice Department told the court in September that training large language models on copyrighted work is fair use. House Judiciary Democrats filed against that position on Friday.

2026-10-31 · SATURDAY · 00:14 PDT

  1. 1 Altman meets Samsung's top executives in South Korea as the memory crunch deepens BLOOMBERG OpenAI chief executive Sam Altman met Samsung Group's top executives in South Korea on Saturday to deepen cooperation on memory chips and AI infrastructure, Bloomberg reports. The meeting comes as global shortages of memory intensify.
  2. 2 AI demand stretches circuit board lead times to 30 months, with orders booked to 2030 WCCFTECH · VIA R/LOCALLLAMA · DISCUSSION Printed circuit board makers cannot secure enough capacity for AI and conventional electronics at once, Nikkei Asia reports, with order lead times now reaching 30 months and one supplier saying orders placed today may not ship until late 2028. An executive at a US PC vendor said board supply is hard to lock in even though PC shipments may fall again next year. Board materials are also getting more expensive.
  3. 3 OpenAI has secured about $11 billion of the $30 billion it targeted for its latest round THE WALL STREET JOURNAL · VIA HACKER NEWS · 137 PTS · 116 COMMENTS · DISCUSSION OpenAI has secured roughly $11 billion in commitments for its new financing, less than half the $30 billion it first sought, after tepid interest from some large investors, the Wall Street Journal reports. The deal values the company at $1.25 trillion rather than the $1.4 trillion it had hoped for. The Financial Times separately reported that OpenAI cut the target by $10 billion.
  4. 4 QEngine decodes Qwen3.8-Flash-Next at 504 tokens a second on two RTX 5090s R/LOCALLLAMA A tester rebuilt QEngine, a source-available CUDA engine written for three RTX 3090s, to run on two RTX 5090s and compared four engines on one machine. Its INT4 build decoded code at 439 tokens a second with the key-value cache in VRAM and 504 with it in host RAM, against 293 for Strata. The poster warns the script repeats prompts, which flatters QEngine's expert cache, and calls 1.4 to 1.9 times Strata honest.
  5. 5 NVIDIA engineers give a garage door a mouth and a grumpy local voice agent for Halloween HUGGING FACE BLOG Two NVIDIA engineers published a writeup of MonsterHouse, a Halloween projection that turns a garage door into a face, listens to trick-or-treaters and answers as a grumpy pirate ship that softens when visitors say please. The whole stack runs on a single workstation using the Nemotron Voice Agent with Nemotron speech recognition, Nemotron 3.5 Bolt E4B, Magpie TTS Zeroshot and Audio2Face-3D.