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Claude comes for Gemini with its own take on Docs and Slides

Anthropic launched Claude Docs and Slides in beta and merged chats with Cowork into 'one Claude', challenging Google's Gemini-powered productivity tools.

Claude Docs and Slides launch in beta, letting users create, edit, share, and collaboratively comment on documents and presentations from any chat, with export options. Anthropic also merged regular chats and Cowork into 'one Claude', bringing Cowork, Design, and Artifacts into a single interface. The update closes ground with Google, which has expanded Gemini inside Docs, Sheets, and Slides, and rolls out to Pro and Max users first across web, desktop, and mobile.

The Verge · AIupdated · 18h agofirst · 19h agoAI industry 5 sources

Claude Cowork and chat are now one Claude

Anthropic merges Claude Cowork and chat into one Claude, adding Docs, Slides, and Design to conversations.

Anthropic announced that Claude Cowork and Claude chat are merging into a single Claude experience, rolling out to Pro and Max plans on web, desktop, and mobile over the coming weeks. New Claude Docs, Claude Slides, and Claude Design features, in beta on paid plans, let users co-create and edit documents, presentations, and designs directly in conversations and download them as PowerPoint or PDF. Team and Free plans will follow, and Enterprise admins will get at least 30 days notice before any changes.

Hacker News · securityupdated · 18h agofirst · 19h agoAI industry 5 sourcesHN 31↑ · 18 comments

DeepSeek-v4.1 Flash: Pushing the Limits of KV Cache Compression

DeepSeek-V4.1 Flash is a 552B-parameter multimodal MoE model with 1M-token context achieving 4x KV cache compression for long-horizon agent workloads.

A detailed analysis of the DeepSeek-V4.1 Flash technical report describes a 552B-parameter multimodal mixture-of-experts model supporting contexts up to 1 million tokens. Its Causal Encoder-Decoder (CED) architecture activates 8B parameters during prefill and 16B during decode, and reportedly delivers about 420 tokens/s. Joint optimization of architecture (CSA2 cross-layer compression), FP4 KV cache precision, and deployment strategy cuts runtime KV cache to roughly 1/4 and persistent KV cache to about 1/8 of DeepSeek-V4-Flash at the same sequence length, targeting storage and bandwidth bottlenecks in long-horizon agent serving. The author notes all DeepSeek-V4 Pro models were taken offline following the release.

Hacker News · AI · 10h agoModel releaseHN 41↑ · 3 comments

Retrospective by 'gpg.fail' authors

Authors of the gpg.fail GnuPG vulnerability set published a retrospective with talk recording, slides, and a repo PoC.

Sam James shares that the researchers behind the 'gpg.fail' set of GnuPG vulnerabilities have published a retrospective, including a talk recording and slides. The slides appear to mention an additional vulnerability not yet widely reviewed, and a proof-of-concept is available in their repository. This follows earlier discussion of the gpg.fail findings on oss-security.

oss-securityupdated · 8h agofirst · 4d agoResearch 9 sources1

Anthropic merges Claude chat and Cowork in one interface

Anthropic unified Claude chat, Cowork, and Artifacts into one auto-routing interface, adding Docs and Slides creation with PDF and PowerPoint export.

Anthropic merged the Claude chat and Cowork front-ends so one window routes requests automatically, ending customer confusion over which tab to use. The update adds Claude Docs and Slides with PDF and PowerPoint export, collaborative sections, and comments, and makes Claude Design, launched in April, available anywhere in Claude. It rolls out to Pro and Max plans on web, desktop, and mobile over coming weeks, with Free and Team tiers later, following a recent Cowork memory upgrade.

TechCrunch · AIupdated · 18h agofirst · 19h agoAI industry 5 sources

Anthropic merges Claude Chat, Cowork, and more into a single product

Anthropic merged Claude Chat and Cowork into one product and launched Claude Docs and Slides for creating and exporting documents and presentations.

Anthropic is folding Claude Chat and Cowork into a single product where Claude automatically determines what a task needs, eliminating tab switching. It also introduced Claude Docs and Claude Slides for creating, editing, and exporting documents and presentations as PowerPoint or PDF, with Claude Design now integrated into conversations. The rollout starts with Pro and Max plans, followed by Team and Free tiers; enterprise admins receive at least 30 days' notice.

The Decoderupdated · 18h agofirst · 19h agoAI industry 5 sources1

macOS 27 Golden Gate – Review

Ars Technica reviews macOS 27 Golden Gate, highlighting an unavoidable Apple Intelligence upgrade, new AFM 3 Core models, and dropped Intel Mac support.

macOS 27 Golden Gate delivers the first significant Apple Intelligence upgrade two years after launch, and the toggle to disable the AI features or delete downloaded models is gone. Apple Intelligence runs on a new AFM 3 Core model built in collaboration with Google, while the more capable AFM 3 Core Advanced requires an M3 chip and at least 12GB of RAM. The release drops all Intel Mac support, requiring Apple Silicon, with Sequoia security updates expected to end in fall 2027 and Tahoe's in 2028.

Hacker News · AI · 16h agoAI industry 2 sourcesHN 45↑ · 28 comments

[AINews] DeepSeek v4.1-Flash: 763B-P8B-D16B novel causal Encoder–Decoder architecture with vision marks the Return of the Whale

DeepSeek released V4.1-Flash, an open-weight 763B-parameter model with a novel causal encoder-decoder architecture, 1M context, vision input, and MIT license.

DeepSeek launched V4.1-Flash, an open-weight MIT-licensed model using a novel causal encoder-decoder architecture with 763B total parameters and asymmetric active parameters: 8B for prefill and 16B for decode. It supports 1M-token context and text+image input, priced at $0.30 per 1M input and $1.20 per 1M output tokens with a 50% off-peak discount. Artificial Analysis scored it 40 on its Intelligence Index, above DeepSeek V4 Pro 0813, and Vals ranked it the #1 open-weight model ahead of Kimi K3. Baseten shipped day-0 support and Ollama began rolling it out to paid subscribers.

Latent Space · 5d agoModel release 2 sources1

[AINews] Reality Checks on AI News (Yegge shuts down Gas Town, Databricks’ +60% Astra cost)

Latent Space AI news roundup: Steve Yegge shuts down Gas Town, Databricks reports 60% higher coding spend on GPT-6 Astra, OpenAI launches misalignment disclosure framework.

Latent Space's AI News digest for September 15-16, 2026 leads with Steve Yegge shutting down his Gas Town orchestrator despite spending thousands monthly on coding-agent subscriptions. Databricks rolled out GPT-6 Astra to roughly 3,500 engineers, reporting superior long-horizon performance over Opus 5 and Sol 5.6 but a ~60% increase in coding spend. OpenAI published a formal framework for disclosing model misalignment incidents with six case reports, while Microsoft and Google Research released safety papers on 'capability laundering' and the Fuse motive-inference benchmark. Xiaomi shared live RL training telemetry for MiMo-V2.6, estimated at $493k/day for the 1T-class Pro run.

Latent Space · 4h agoAI industry 11 sources

rMuscle: Robotic Muscle Memory for Efficient Vision-Language-Action Model Inference

rMuscle, a caching-based inference framework for vision-language-action models, achieves 1.29-1.42x speedups on RTX 4090 and Jetson Thor while preserving success rates.

rMuscle is a real-time inference framework for Vision-Language-Action (VLA) models that exploits cross-execution similarity in repetitive robot tasks via a dual-phase muscle-memory cache. The Context Cache reuses visual-token outputs to reduce computation, while the Action Cache reuses neuron activation patterns to reduce weight accesses, with online recomputation and sliding-window retrieval keeping overhead low. It achieves 1.29-1.42x speedups on RTX 4090 and Jetson Thor across LIBERO, RoboTwin, and real-world manipulation tasks while maintaining original success rates.

arXiv cs.AI / cs.LG / cs.CL · 18h agoAI tools & infra1

The sexy AI-powered dating app scams are here

Anthropic exposed a network of roughly 28 AI-driven dating apps using autonomous personas and gig workers to defraud paying users.

Anthropic threat intelligence uncovered a fraud network of around 28 dating apps after a prepaid account sent over 100,000 Claude API requests daily, with most chats run by autonomous AI personas and no human agent. Researchers Matthew Gore-Kormanik and Anthropic's Chris Cronbaugh documented apps including Dora, Romi, and Doni, which monetize conversations via coins; gig workers were hired only to pass liveness checks and select pregenerated replies. An operations manual written in Chinese was found inside the Doni app, and Anthropic published findings in its September 2026 AI misuse report.

The Verge · AI · 21h agoPhishing & fraud in the wild

12 Best Kubernetes Security Tools Compared (2026): Features & Pricing

GBHackers compares 12 Kubernetes security vendors including Sysdig, Wiz, Aqua, and Cisco Isovalent on features, pricing units, and procurement strategy.

GBHackers publishes a 2026 buying guide comparing 12 Kubernetes security vendors including Sysdig, Wiz, Aqua Security, SUSE NeuVector, Snyk, Cisco Isovalent, Palo Alto Networks, Fairwinds, Red Hat ACS, and Tigera. It argues CNCF-grade open source (Kubescape, Falco, Trivy, Calico, Cilium/Tetragon) provides free posture, runtime, and network policy coverage that resets price negotiations. Cisco's acquisition of Isovalent places the eBPF data plane under a networking giant, while the paid market focuses on multi-cluster policy, enforcement, and support. The piece emphasizes that pricing units (workload, node, cluster, developer, credits) heavily influence contract costs.

GBHackersupdated · 3h agofirst · 1d agoTools 12 sources1

12 Best Kubernetes Security Tools Compared (2026): Features & Pricing

A buying-guide comparison of twelve Kubernetes security vendors, from free OSS tools like Falco and Kubescape to paid platforms led by Sysdig and Aqua.

The article compares features and pricing mechanics for twelve Kubernetes security vendors including Sysdig, Wiz, Aqua Security, SUSE NeuVector, Snyk, Isovalent (Cisco), Palo Alto Prisma Cloud, Fairwinds, Red Hat ACS (StackRox), and Tigera. It argues CNCF-grade open source (Kubescape, Falco, Calico, NeuVector, Cilium/Tetragon) provides a free floor for posture, runtime, and network policy. Pricing hinges on node-versus-cluster-versus-developer billing units, and Cisco's Isovalent acquisition consolidates the eBPF layer inside a networking giant.

GBHackersupdated · 3h agofirst · 1d agoTools 12 sources

Apple's Siri AI Can Be Swapped Out for Claude, ChatGPT, Code Shows

Code analysis of iOS 27 and macOS Golden Gate frameworks shows Apple engineered Siri to deeply interoperate with third-party AI models like Claude and GPT-5.6.

Code sleuth 'pdfu' uncovered private frameworks in iOS 27 and macOS Golden Gate revealing a 'Model Delegation' mechanism that lets Claude act as a Siri extension like the built-in ChatGPT extension. A second 'Inference Providing' protocol in Model Manager Services can fully replace Siri's server-side model with models such as GPT-5.6, which then receives Apple's Siri planner prompt and tool definitions to perform system actions and process personal data. The EU Digital Markets Act, which requires Apple to give third parties effective access to iOS features, may have shaped this approach. The entitlement is not yet open to third parties and Claude is not yet available in the macOS 27 Golden Gate RC.

Hacker News · AI · 3d agoAI industryHN 57↑ · 14 comments

A Princeton Researcher Proposes Recurrent Looped Transformer (RLT) that Carries Decoder State across Every Token, Fixing 96 Blocks per Token with Unbounded Temporal Depth

Princeton researcher Yifan Zhang proposes Recurrent Looped Transformer, carrying full decoder state across every token for unbounded temporal depth.

Yifan Zhang's technical report defines the Recurrent Looped Transformer (RLT), pairing a causal encoder with a recurrent decoder whose final output and layerwise sliding-window attention cache carry into every subsequent token with no prompt-response boundary reset. The reference configuration ties 48 encoder and 48 decoder layers, executing 96 logical blocks per token while the state path grows to 48t blocks after t tokens at fixed per-token compute. The report details RL replay contracts that rebuild all states under current parameters and exact prefix snapshots for multi-turn serving, but explicitly reports no measured efficiency, reasoning quality, or scaling results.

MarkTechPost · 3d agoAI research1

The Rise of the Forward Deployed Engineer — and How To Do the Job Right

Palantir veteran Vinoo Ganesh traces the forward deployed engineer role and shares practices for building effective FDE teams.

Kepler CEO and former Palantir forward deployed engineer Vinoo Ganesh argues that labs, startups, and PE firms hire FDEs without a shared definition of the role. He recounts Palantir's Project Frontline rotation, which trained about 250 software engineers as FDEs, many now leading forward deployed teams at OpenAI, Anthropic, xAI, and Anduril. A 2013 failure of the Phoenix transaction store at a bank, where real-world data gaps caused roughly 2.3 million keyspaces and an out-of-memory crash, illustrates why FDEs must own the gap between design and production reality. At Kepler he places the FDE function inside product rather than sales.

Latent Space · 4d agoAI industry 4 sources1

Rethinking Heterogeneous System Disaggregation for Subquadratic Attention

SQD disaggregates LLM inference by quadratic versus subquadratic attention layers, improving energy efficiency up to 56% on heterogeneous systems versus GPU-only baselines.

SQD (SubQuadratic Disaggregation) splits decode not by operator type but by quadratic versus subquadratic attention, matching their distinct arithmetic intensity and memory footprints. For sparse attention LLMs it separates top-k selection (requiring full KV indexing) from top-k attention plus FFN; for linear and sliding-window models it separates dense attention layers from subquadratic layers plus FFN. On an adjusted 8xB200 heterogeneous proxy, tokens-per-joule improves 53% on GLM 5.2, 31% on Nemotron 3 Ultra, and 56% on Gemma 4 31B. A Rubin plus LPX analytical model shows 1.2x-1.5x tighter achievable latencies and up to 3.6x higher throughput versus attention-FFN disaggregation.

arXiv cs.AI / cs.LG / cs.CL · 5d agoAI research

A Hybrid LSTM-XGBoost Framework for Multi-Horizon Stock Return Prediction Across Diversified Equity Portfolios

Hybrid LSTM-XGBoost model predicts multi-horizon returns for 14 US equities, cutting 30-day RMSE to about one-third of a standalone LSTM baseline.

The paper combines a two-layer LSTM (64 hidden units) processing 60-day windows of five market features with an XGBoost regressor over a 78-dimensional hybrid feature vector including 14 technical indicators. It is trained on pooled data for 14 US equities across six sectors using chronological splits and per-stock MinMaxScaling to prevent look-ahead bias, and evaluated at 30, 90, 252, and 365 trading-day horizons. The hybrid achieves test RMSE of 0.0949 at 30 days, roughly one-third of the standalone LSTM, while 97.6% directional accuracy at 365 days largely tracks the base rate of positive returns.

arXiv cs.AI / cs.LG / cs.CL · 5d agoAI research

‘We Did Not Invite You.’ Citizens Rage at Town Hall Over Proposed Nuclear AI Data Center

University of Michigan and Los Alamos faced resident backlash over a proposed $1.2 billion hyperscale data center in Ypsilanti Township, Michigan.

The University of Michigan partnered with Los Alamos National Laboratory on a proposed $1.2 billion, 220,000-square-foot hyperscale data center in Ypsilanti Township. Residents at a Wednesday town hall raised concerns about electricity costs, water usage, noise, and the facility's role in nuclear weapons research. Officials noted the project is far smaller than the nearby $56 billion, 1.4-gigawatt OpenAI data center in Saline Township. Los Alamos said no plutonium or weapons production would occur on site, though the facility would support nuclear stockpile modeling.

404 Media · 5d agoAI industry

Cohere Releases North Small Translate: A 218B MoE Translation Model That Scores 83.6 on WMT26 Across 50 Languages

Cohere released North Small Translate, an open-weight 218B MoE (25B active) translation model scoring 83.6 on WMT26 across 50 languages.

Cohere and Cohere Labs released North Small Translate, a decoder-only sparse Mixture-of-Experts translation model with 218B total and 25B active parameters, 128 experts with 8 activated per token plus shared experts, and 16K-token input and output context. In Cohere's vendor-reported WMT26 evaluation, judged by GPT-5.6-Sol, it scores 83.6 averaged across 50 languages (84.36 in an agentic multi-pass mode), ahead of DeepL NextGen (81.37), Qwen 3.5 397B A17B (81.56), GLM 5.2 (76.50), and Google Translate (68.20). The model was built with RWS's Language Weaver team, post-trained specifically for translation, and reports 112 output tokens per second versus 81 for Gemma 4 31B, with long-document xCOMET-XL scores of 48.9 versus 21.3 for Google Translate. It is available free on Cohere's Chat V2 API until rate limits, with three self-hosting checkpoints including a 4-bit NVFP4 variant running on 1x B200 or 2x H100.

MarkTechPost · 6d agoModel release

ZGCM-1: A Fully Open and Extremely Efficient Foundation Model for Math and Agentic Search

ZGCM-1 is a fully open 7B foundation model with 256K context that stays competitive with frontier models on math reasoning and agentic search.

ZGCM-1 is a fully open 7B dense foundation model trained from scratch using an efficiency-focused recipe: interleaved gated sliding-window and full attention, a stable FP8 Muon optimizer, and MDP-based mid-training with context scaling across 16K, 64K, and 256K. On mathematical reasoning and agentic search suites it remains competitive with much larger frontier models such as Qwen3-235B-A22B and GLM-5.1. The recipe yields a ~4.2x improvement in 16K pre-training time-to-loss, and all weights, checkpoints, training code, data recipes, and W&B logs are open-sourced.

Hugging Face daily papers · 6d agoModel release

TART: A Modular Tool for Technique-Aware Audio-to-Tablature Guitar Transcription

TART pipeline transcribes guitar audio to tablature with fingering and technique labels, outperforming prior baselines by up to 8.5 Tab F1 points.

TART is a modular four-stage pipeline for audio-to-tablature guitar transcription, combining an audio-to-MIDI transcription model, an expressive technique classifier, an audio-conditioned T5 encoder-decoder for string-fret assignment, and an automated tablature generator. In zero-shot evaluation on GuitarSet, EGDB, and two noisy augmented benchmarks, it averages 81.35% audio-to-MIDI F50 (+6.67 over the best baseline), 71.8% string-fret Tab F1 (+8.5), and 54.08% end-to-end Tab F1. The authors state it is the first framework to generate tablature with both fingering and expressive technique annotations directly from guitar audio.

arXiv cs.AI / cs.LG / cs.CL · 6d agoAI research2