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Google Deepmind launches interdisciplinary institute to tackle the big questions around AGI

Google DeepMind launches the DeepMind Institute, an interdisciplinary hub for AGI safety, governance, and risk research.

Google DeepMind has founded the DeepMind Institute (DMI), a platform for interdisciplinary research and debate on artificial general intelligence. Directed by Shane Legg, James Manyika, and Nobel laureate Demis Hassabis, it will bring together technologists, artists, humanists, and policy experts to address AGI safety, governance, and risks such as cyberattacks and loss of control. DeepMind leadership says AGI is close, with Legg suggesting a precursor could arrive by 2028.

The Decoder · 3h agoAI industry 2 sources

Hackers Pose as Domain Controllers to Steal Active Directory Password Hashes

Attackers abuse Active Directory replication (DCSync) via the DRSUAPI protocol to steal password hashes and forge Golden Tickets for persistent domain compromise.

Security reporting citing Trellix details how threat actors impersonate domain controllers to request replication data and obtain NTLM password hashes without dumping LSASS on the domain controller. With Domain Admin or replication rights, attackers can steal the KRBTGT hash and forge long-lived Golden Tickets that survive password resets. Defenders should monitor DRSUAPI requests from non-DC systems, restrict replication permissions, and enforce MFA and tiered administrative access.

Cyber Security Newsupdated · 6d agofirst · 6d agoResearch 2 sources3· 1 read

Performance of Clinical AI System and Physicians and Frontier Language Models in primary care diagnostics

Clinical AI system Doctorina achieved 82.0% primary-care diagnostic concordance versus 57.0% for physicians across 150 synthetic consultations.

The study compared Doctorina, eight physicians, and four standalone frontier language models on 150 synthetic Polish-language primary-care consultations. Doctorina achieved 82.0% Top-1 diagnostic concordance versus 57.0% for physicians (25.0-point difference, 95% CI 17.7-32.7) and 97.3% versus 85.0% primary-or-reference-differential concordance. Normalized workup and treatment scores were 89.4 versus 66.9 and 83.7 versus 61.2. Kimi K3 ranked next on diagnosis, while Claude Opus 5 led the closely spaced management estimates among Opus, Doctorina and Kimi.

arXiv cs.AI / cs.LG / cs.CL · 8d agoAI research

Akamai Valkey Managed Database: Real-Time Memory for Enterprise AI

Akamai launched Valkey Managed Database, a low-latency in-memory data layer aimed at cutting AI inference costs and accelerating RAG.

Akamai introduced Valkey Managed Database, a managed in-memory data service based on the open-source Valkey project. The company positions it as real-time memory for enterprise AI, optimizing inference costs, accelerating retrieval-augmented generation, and powering real-time AI agents.

Akamai Blog · 29d agoAI tools & infra

Future-Proofing the Internet: Akamai Achieves End-to-End PQC

Akamai says it achieved end-to-end post-quantum cryptography across its network to future-proof internet traffic.

Akamai announced it has achieved end-to-end post-quantum cryptography (PQC) across its services. The company frames the move as future-proofing the internet against quantum decryption threats. No article text was available; details are limited to the announcement title.

Akamai Blog · 28d agoIndustry

Zero-Day Dominance: How Akamai Defends Before the Industry Discloses

Akamai published vendor marketing on how its platform defends customers against zero-day exploits before industry-wide disclosure.

Akamai published a blog post titled 'Zero-Day Dominance: How Akamai Defends Before the Industry Discloses'; no article body text was available. Based on the title, the piece promotes Akamai's capabilities for protecting customers from zero-day exploits ahead of public disclosure. No specific vulnerabilities, CVEs, incidents, or customers are identified.

Akamai Blog · 19d agoIndustry

Introducing @huggingface/kernels: 200+ WebGPU Kernels for Local AI

Hugging Face released @huggingface/kernels, a library offering 200+ WebGPU compute kernels to accelerate AI inference locally in browsers.

Hugging Face introduced the @huggingface/kernels package, bundling more than 200 optimized WebGPU compute kernels for running AI workloads locally. The release targets browser-based and on-device inference, reducing reliance on server-side compute. No article body was available beyond the title, so benchmark results and supported models are not specified.

Hugging Face Blog · 15d agoAI tools & infra

Rebuilding AUTOMATIC1111 with Gradio Workflow

Hugging Face demonstrates rebuilding the AUTOMATIC1111 Stable Diffusion web interface using its Gradio Workflow framework.

Hugging Face published a post showing how to rebuild the AUTOMATIC1111 Stable Diffusion WebUI experience with the Gradio Workflow framework. The article body was unavailable, so details beyond the title are limited, but the piece appears to be a tutorial on composing interactive AI interfaces with Gradio Workflow components.

Hugging Face Blog · 6d agoAI tools & infra

Multi-Vector (Late Interaction) Embedding Models with Sentence Transformers

Hugging Face details building and using multi-vector late-interaction embedding models with Sentence Transformers for retrieval workloads.

Hugging Face published a guide on multi-vector, late-interaction embedding models (ColBERT-style) supported through Sentence Transformers. The post covers how practitioners can build and use these models for retrieval and RAG pipelines. It is a developer tooling and technique write-up, not a security advisory.

Hugging Face Blog · 29d agoAI tools & infra1

Up to 3.2x Faster Inference with LFM2.5-DSpark

LiquidAI's LFM2.5-DSpark delivers up to 3.2x faster inference, announced via the Hugging Face blog.

LiquidAI announced LFM2.5-DSpark on the Hugging Face blog, claiming up to 3.2x faster inference. The release focuses on improved runtime performance for the LFM2.5 model family; further technical details were not available in the provided text.

Hugging Face Blog · 27d agoAI tools & infra

Introducing More Granular Controls for AI Bot Traffic

Akamai introduced more granular controls for managing AI bot traffic within its bot management platform.

Akamai announced the introduction of more granular controls for handling AI bot traffic in its bot management offering. Detailed feature specifications were not available in the provided source text, which included only the title.

Akamai Blog · 13d agoTools

Rosetta at AlexandriaX-2026: LoRA-Adapted NileChat for Context-Aware Dialectal Arabic Dialogue Translation

Rosetta ranks 4th and 5th in AlexandriaX-2026 dialectal Arabic dialogue translation using a LoRA adapter on NileChat-3B, finding limited pretraining benefit.

The Rosetta system for the AlexandriaX-2026 shared task fine-tunes a LoRA adapter on NileChat-3B for context-aware English-to-dialectal Arabic dialogue translation. The adapter was additionally pretrained on MADAR and PADIC dialect corpora for the unconstrained track. It achieved spBLEU 26.10 (4th, constrained) and 25.09 (5th, unconstrained). External dialect pretraining improved only two of thirteen dialects while slightly degrading overall performance, indicating negative transfer.

arXiv cs.AI / cs.LG / cs.CL · 7d agoAI research1

ukisai/Swift-Qwen3.8-27b — new model trending #30 on Hugging Face

UkisAI releases Swift-Qwen3.8-27B, a Qwen3.8-27B derivative using 58.3% fewer thinking tokens with <1% performance loss and ~1.95x speed-up.

UkisAI released Swift-Qwen3.8-27B, a reasoning-efficient derivative of Qwen3.8-27B that cuts thinking-token usage by 58.3% while staying within 1% of base performance, yielding a 1.95x speed-up on several tasks. The model was fine-tuned by penalizing reasoning-marker tokens that trigger overthinking, plus a transfer component from BottleCap AI's ThinkingCap-Qwen3.6-27B. Benchmarks include GPQA-Diamond 88.28% (base 88.38%), MMLU-Pro 84.95% (base 85.47%), and AIME 2026 94.00% (base 98.67%), with mean-token reductions of roughly 27-46% across tests. GGUF weights are available on Hugging Face alongside enterprise licensing options.

Hugging Face trending models · 8d agoModel release

The 12 Best Mobile Device Management (MDM) Solutions, Compared and Priced

A comparison of 12 MDM platforms ranks Microsoft Intune as best value for Microsoft 365 estates and Jamf, Kandji, and Mosyle for Apple fleets.

The buyer's guide compares 12 mobile device management (MDM) products, naming Microsoft Intune best value since it is included in Microsoft 365 E3/E5, and Jamf, Kandji, and Mosyle as Apple specialists with day-one OS support and automated compliance remediation. Eight of the twelve publish rates; per-device pricing punishes multi-device users, while Microsoft, Omnissa, and IBM offer per-user options. Free tiers from Mosyle, Miradore, and ManageEngine support genuine small deployments.

GBHackersupdated · 6d agofirst · 6d agoIndustry 4 sources

Deconstructing the Architecture of AI-Orchestrated Web Attacks

Akamai analyzes the architecture of AI-orchestrated web attacks, examining how AI-driven automation is reshaping offensive web operations.

Akamai published an analysis deconstructing the architecture of web attacks orchestrated with AI, based on the available title. The piece examines how AI-driven automation changes the structure of offensive web operations. No article text was provided, so specific findings are limited.

Akamai Blog · 23d agoResearch

LandingAI Releases Agentic Document Extraction Gen2 with DPT-3 Pro and DPT-3 Verity

LandingAI shipped Agentic Document Extraction Gen2 with DPT-3 Pro and DPT-3 Verity parsing models, adding usage-based billing, block-tree outputs, and word-level grounding.

LandingAI has generally released Agentic Document Extraction Gen2, rebuilt around two parsing models: DPT-3 Verity for deterministic transcription of digital documents with per-word bounding boxes and confidence scores, and DPT-3 Pro for layout-aware parsing of scans, handwriting, non-Latin scripts, and LaTeX math. Billing changes from a flat 3 credits per page to a page-plus-output-character model (Pro: 1 credit/page plus 0.5 credits per 1,000 output characters on priority; Verity: 0.3 plus 0.2), with an asynchronous standard tier at 0.5x price and vendor-claimed 25-80% cost reductions. Parse v2 returns a document-page-block tree with semantic IDs, normalized bounding boxes, and line- or word-level atomic grounding, replacing flat chunks; Gen1 client code will not run against Gen2 endpoints. Deployment options include US/EU cloud, VPCs on AWS, Azure, and Google Cloud, Snowflake, and air-gapped on-premises environments, with automated model routing planned for fall 2026.

MarkTechPost · 6d agoAI tools & infra

[AINews] OpenAI to reach AGI bar by end-2026

OpenAI chief scientist Jakub Pachocki says unreleased Astra model meets the 'Automated AI Research Intern' goal; Altman expects internal AGI declaration by December 2026.

OpenAI chief scientist Jakub Pachocki says the unreleased Astra model fulfills the September 2026 'Automated AI Research Intern' target. Sam Altman told TIME he expects OpenAI to declare AGI achieved internally by December 2026. The roundup also covers Zhipu's GLM-5.3-Flash (320B total parameters, 18B active, 1M context), Google's Gemini Omni 1.1 Flash video model topping the Text-to-Video Arena, and the $399 open-source Microduck biped robot from Pollen Robotics and Hugging Face.

Latent Space · 19d agoAI industry

Introducing AI Assistant for Akamai Web Security Analytics

Akamai launched an AI Assistant for Web Security Analytics, giving SOC and AppSec teams natural-language event investigation and guided response actions.

Akamai introduced an AI Assistant integrated with its Web Security Analytics offering, designed to let SOC and AppSec teams investigate security events faster. The assistant supports natural-language queries and guided action recommendations for analysts. The announcement is a vendor product launch with no incident details.

Akamai Blog · 6d agoTools

ukisai/Swift-Qwen3.8-27B-GGUF — new model trending #30 on Hugging Face

UkisAI released Swift-Qwen3.8-27B GGUF, a Qwen3.8-27B derivative cutting thinking tokens by 58.3% with under 1% performance loss and roughly 1.95x speedup.

UkisAI released Swift-Qwen3.8-27B as GGUF on Hugging Face, a reasoning-efficient derivative of Qwen3.8-27B using a Swift adapter that reduces median thinking tokens by up to 58.3% while keeping performance losses under 1% and delivering a 1.95x speed-up on several tasks. Reported benchmarks include GPQA-Diamond 88.28%, MMLU-Pro 84.95%, C-Eval 90.62%, AIME 2026 94.00% and Terminal-Bench 2.1 65.84%. The model is trending at #30 on Hugging Face, with BF16 weights and enterprise licensing also available.

Hugging Face trending models · 5d agoModel release

Supporting Thailand’s next generation of AI startups

OpenAI and Thailand's MHESI launched an eight-week accelerator for ten health, wellness, and education AI startups.

OpenAI announced a program with Thailand's Ministry of Higher Education, Science, Research and Innovation (MHESI) to support the country's next generation of AI startups. The eight-week accelerator will help ten startups in health, wellness, and education turn AI prototypes into trusted products.

OpenAI News · 19d agoAI industry

Inside AI-Powered WAF Detections: Architecture and Safety Controls

Akamai published a technical breakdown of the architecture and safety controls behind its AI-powered WAF detections.

Akamai published a technical blog post examining the architecture of its AI-powered web application firewall detections. Per the title, the piece covers the design and safety controls applied to machine-learning-based WAF detections.

Akamai Blog · 8d agoTools

Vidu S2: Real-Time Interactive, Editable, and Spatial Video Generation

Vidu S2 delivers real-time 720p interactive avatar generation plus real-time video editing with style, clothing, character, and background replacement.

Vidu S2 comprises Vidu S2-Avatar, a real-time interactive digital-character model, and Vidu S2-Editing, a real-time video editing model. S2-Avatar supports real-time 720p generation, dynamic references updatable at any moment, and stronger instruction following such as dancing, while S2-Editing performs real-time style rendering, clothing replacement, character replacement, and background replacement. The work also explores real-time spatial video generation for both models, reports outperforming all baselines, and offers a playable online demo at vidu.com.

Hugging Face daily papers · 7d agoModel release

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 · 2d agoAI industryHN 57↑ · 14 comments

Amazon launches Alexa+ in India with Hindi support

Amazon launched its generative AI Alexa+ assistant in India with Hindi support in Early Access, free for Prime customers after testing.

Amazon announced that Alexa+, its generative AI-powered conversational assistant, is now available in India in Early Access with Hindi and English support, including mid-sentence language switching and long-form context retention. The assistant handles multi-step tasks such as ordering groceries via Amazon Now and controlling smart home devices, with integrations including Swiggy, District, MakeMyTrip, EazyDiner, Amazon Music, and JioSaavn. It will be free for Prime members after the testing period and cost about $20.85 per month for non-Prime customers. Amazon is targeting India's 600 million-plus Hindi speakers, and says smart device adoption grew 20% year over year.

TechCrunch · AI · 9h agoAI industry

New Mirai-Based Linux Botnet ‘Evooo1Bot’ Turns Victims Into Proxies

A newly observed Mirai-based Linux botnet dubbed Evooo1Bot compromises edge devices and turns them into persistent proxies for threat actors.

Evooo1Bot is a newly identified Linux botnet built on the Mirai framework but enhanced with additional advanced capabilities. The malware compromises edge devices and converts them into persistent proxies, likely for relay or resale use. The botnet's evolution beyond stock Mirai highlights continued targeting of poorly secured IoT and edge systems.

Infosecurity Magazine · Aug 14, 2026Malware in the wild

Dr. Claw: An AI Scientist Workspace for Vibe Research

Researchers release Dr. Claw, an open-source auditable workspace that wraps coding agents like Claude Code for end-to-end AI-assisted research workflows.

Paper 2609.00365 presents Dr. Claw, an open-source workspace that wraps existing coding-agent executors such as Claude Code and Gemini CLI in a controllable, human-in-the-loop research workflow. It uses persistent state objects, a reusable skill library, and multi-executor coordination to make research decisions auditable and recoverable, rather than adding another autonomous agent. Holding the executor fixed, Dr. Claw scores higher on research completeness than a bare command-line agent while preserving an auditable process trail. The code is released under AGPL-3.0 on GitHub (OpenLAIR/dr-claw).

Hugging Face daily papers · 17d agoAI research1

Training and Finetuning Multi-Vector Embedding Models with Sentence Transformers

Hugging Face published a tutorial on training and finetuning multi-vector embedding models using the Sentence Transformers library.

Hugging Face's blog walks through training and finetuning multi-vector embedding models with Sentence Transformers. Multi-vector approaches store multiple vectors per document to support late-interaction retrieval. The post is a practical guide for developers building retrieval pipelines with the library.

Hugging Face Blog · 21d agoAI tools & infra1

LLaDA-UI: Bringing Block-wise Diffusion to Vision-Language GUI Agents

LLaDA-UI, a 16.7B block-wise diffusion vision-language GUI agent, outperforms Qwen2.5-VL-7B and beats Qwen3-VL-8B on four of six GUI benchmarks.

LLaDA-UI is a 16.7B-parameter MoE-based, block-wise diffusion vision-language GUI agent built on the LLaDA2.0-mini-base diffusion language backbone with a native-resolution vision encoder. It uses a two-stage pipeline: general multimodal pre-training followed by GUI-agent supervised fine-tuning on mobile, desktop, web, and grounding data. It substantially outperforms Qwen2.5-VL-7B and surpasses Qwen3-VL-8B on four of six reported GUI benchmarks, establishing block-wise diffusion as a practical paradigm for latency-sensitive multimodal agents.

Hugging Face daily papers · 8d agoAI research