AI News Archive: July 27, 2026 — Part 18
Sourced from 500+ daily AI sources, scored by relevance.
- MyBookCove
Create a beautiful memoir in your words with AI guidance
- Ghostlink
Run local LLMs across heterogeneous clusters
- Blubber OS
A desktop workspace for Claude Code. ✅
- PSA: Your Claude shared chats and Artifacts may have ended up on Google
The issue appears to have originated from Claude’s “share chat” feature, which allows users to create links that enable anyone with the assigned URL view a conversation or project.
- Uh-oh: Some Claude shared conversations and Artifacts appear to be indexed and publicly accessible on Google Search
Over the weekend, Reddit user -void1 posted an alarming discovery on the r/ClaudeAI subreddit: some conversations that users of Anthropic's Claude AI chatbot had made "shareable" via a link were being indexed by Google Search, and could be clicked on and accessed by seemingly anyone. The conversation took off on the social networks X and Reddit , the latter with thousands of upvotes and comments, many expressing concern about user privacy and information security, and the additional finding by users that shared Claude Artifacts — including interactive applications, dashboards, documents and other AI-generated work products — were also appearing in Google Search results. VentureBeat independently verified that some Claude Artifacts not shared directly with us were indeed searchable and accessible via Google. We could not access any shared conversations. By Sunday morning, many of the original Google search results for shared Claude conversations appeared to have disappeared or become significantly harder to find, suggesting either Google, Anthropic or the users who authored them had begun taking action. The exposure could carry broader implications for enterprise users. Anthropic has increasingly positioned the feature as a collaborative workspace for building and sharing software, dashboards, documents and other business assets rather than simply chatbot responses. Asked by VentureBeat about the situation, an Anthropic spokesperson provided the following statement (emphasis mine): “We give people control over sharing their Claude conversations publicly, and in keeping with our privacy principles, we do not share chat directories or sitemaps with search engines like Google. These shareable links are not guessable or discoverable unless people choose to share them themselves. When someone shares a conversation, they are making that content publicly accessible, and like other public web content, it may be archived by third-party services.” A simple Google search yields a trove of Claude conversations Reddit user -void1 posted to r/ClaudeAI on July 25, 2026 , demonstrating that the Google query site:claude.ai/share surfaced numerous publicly accessible Claude conversations. Screenshots shared across Reddit and X showed Google returning pages from Claude's /share URLs, while other users reported finding conversations containing cryptocurrency wallet creation, legal questions, résumés and internal business discussions. While many users expressed concern that conversations they believed were effectively "unlisted" could become discoverable through public search engines, others argued the behavior reflected the expected consequences of creating publicly accessible share links rather than a software vulnerability. Indeed, Anthropic requires the user themselves to go into Claude's options and select to make a conversation or Artifact shareable to others with the link, warning them it will be accessible to anyone with it, over multiple dialog boxes. It is similar to sharing a Google Doc link, where the user must also select the option — it is not enabled by default. Why the exposure of Claude Artifacts may be even more concerning On July 26, X user Om Patel , founder of research firm BigIdeasDB, posted allegingthat searches such as site:claude.ai/public/artifacts surfaced publicly shared applications, dashboards, reports and documents. Screenshots circulating online appeared to show search results referencing internal-looking proposal documents and other business materials. Another widely circulated post warned that users often interpret "Anyone with the link" as equivalent to an unlisted YouTube video—accessible only if someone possesses the URL—not necessarily as content eligible for indexing by public search engines. VentureBeat independently verified that multiple third-party Claude Artifacts appeared in Google Search results for the query site:claude.ai/public/artifactslaunch and were accessible without authentication, despite the URLs not being previously known to the reporter. However, VentureBeat has not independently verified the full volume or representativeness of the examples circulating on social media. The reports are particularly significant because Artifacts has become one of Anthropic's flagship product initiatives. First introduced alongside Claude 3.5 Sonnet in June 2024, Artifacts transformed Claude from a conventional chatbot into a collaborative workspace capable of generating interactive web applications, dashboards, visualizations, documents, games and other live software alongside a conversation. VentureBeat previously described the launch as potentially marking the beginning of an "interface war" among AI companies, shifting competition from raw model performance toward collaborative AI workspaces. Anthropic subsequently rolled Artifacts out to all Claude users , saying tens of millions had already been created, before expanding the concept again this year into Claude Code . That update allows engineering teams to publish live HTML dashboards and interactive project workspaces directly from coding sessions, making Artifacts an increasingly important part of Anthropic's enterprise strategy. That broader functionality raises the potential stakes if publicly shared Artifacts were also being indexed. Unlike ordinary chat transcripts, Artifacts can contain interactive software prototypes, engineering dashboards, planning documents, product mockups, data visualizations and other work products organizations increasingly rely on to collaborate across technical and business teams. If those pages become searchable through public search engines, the exposure could extend well beyond conversational text. A reality check on privacy, information security and the open web Importantly, nothing so far suggests attackers gained access to private Claude accounts or conversations. Rather, the controversy centers on conversations and Artifacts that users explicitly chose to share publicly via Claude's sharing tools. The dispute instead is whether users reasonably understood those shared pages could become discoverable through public search engines rather than only by recipients possessing the link. Technically, pages that are publicly accessible without authentication can generally be indexed by search engines unless publishers explicitly prevent crawling through mechanisms such as noindex directives or other indexing controls. Several Reddit commenters noted that Claude's long, randomly generated share URLs are effectively impossible to guess. Instead, search engines typically discover them only after links appear somewhere they are permitted to crawl, such as public websites, forums or social media posts. Others questioned exactly how Google initially discovered so many Claude share URLs. The issue also illustrates a growing challenge for AI companies as chatbots evolve into collaborative workspaces for creating software, documents, dashboards and business applications. Features originally designed to make sharing AI-generated work easier now increasingly expose assets that may carry significantly more business value than a simple conversation. As enterprises adopt AI as a platform for building internal tools and workflows, the distinction between "shared by link" and "publicly discoverable through search" becomes far more consequential. A recurring challenge for AI companies Anthropic is far from the first AI company to confront the distinction between "shared" and "searchable." Reddit users quickly pointed out that OpenAI previously faced criticism after publicly shared ChatGPT conversations became discoverable through Google, prompting similar debates over whether "share by link" should imply a publicly indexed webpage or something closer to an unlisted document. Anthropic's situation also echoes an incident involving Google's pre-Gemini AI assistant, Bard, in September 2023 . SEO consultant Gagan Ghotra discovered that Google Search had begun indexing shared Bard conversation links, warning that users could mistakenly assume they were sharing conversations only with intended recipients rather than making them discoverable through search. Google later responded publicly that it did not intend for shared Bard chats to be indexed and said it was working to block them from Google Search while emphasizing that only conversations users explicitly chose to share were affected. Together, the Bard, ChatGPT and now Claude episodes suggest AI companies continue to wrestle with the boundary between content that is technically public on the web and users' expectations that "share with a link" behaves more like an unlisted Google Doc or YouTube video than a webpage eligible for indexing by search engines. What enterprises should do now For organizations deploying generative AI broadly across employees, the distinction between "shared with a link" and "publicly discoverable through search" is not merely semantic. It can determine whether an internal engineering dashboard, financial model, product roadmap, customer-facing prototype or AI-generated application remains effectively private—or becomes visible to anyone using a search engine. Whether this ultimately proves to be a technical indexing oversight, a mismatch between product design and user expectations, or some combination of both, the episode serves as another reminder that AI products are increasingly functioning less like chatbots and more like collaborative operating systems for knowledge work. As those platforms begin hosting internal dashboards, software prototypes, financial analyses, business planning documents and increasingly sophisticated enterprise applications, seemingly small decisions about how shared links behave can have outsized consequences for enterprise security, product design and user trust. Enterprise leaders should consider taking several practical steps: Audit existing shared AI content: Review shared conversations, Artifacts and other publicly accessible AI-generated assets to determine whether they should remain available or be unpublished. Clarify what "Share" actually means to your ENTIRE organization: Don't assume employees understand the difference between "accessible by link" and "discoverable through search." Update internal guidance to explain how each AI platform handles shared content. Treat AI platforms like collaboration software: Apply the same governance you use for Google Docs, Microsoft 365, Slack, GitHub, Notion or SharePoint—including policies around sharing sensitive intellectual property, customer information and regulated data. Prefer authenticated enterprise workspaces for sensitive information: When possible, keep confidential projects, code, financial models and customer data inside enterprise accounts with identity-based access controls instead of publicly accessible links. Review vendor defaults and sharing controls: As AI platforms evolve rapidly, administrators should periodically revisit default sharing settings, retention policies and indexing behavior rather than assuming they remain unchanged after new feature releases. In sum, e nterprises that have relied on Claude's sharing features may wish to review existing shared conversations and Artifacts at this time.
- Users’ seemingly private conversations with Anthropic’s Claude showed up in Google search results
Users’ seemingly private conversations with Anthropic’s Claude showed up in Google search results Fortune
- Claude AI shared chats indexed by Google - see if your conversations were exposed
Google wasn't supposed to see them, but then everyone on Reddit did. Here's how to handle the situation.
- Shared a Claude conversation? Google may have seen it.
Shared Claude chats were publicly accessible through Google Search.
- When You Share Claude Chats, You Might Be Sharing Them With Everyone
Not the open source anyone was asking for.
- Claude Chats Popped Up in Google Search Results. Who's to Blame?
Claude Chats Popped Up in Google Search Results. Who's to Blame? PCMag UK
- Claude Chats Popped Up in Google Search Results. Who's to Blame?
Claude Chats Popped Up in Google Search Results. Who's to Blame? PCMag Australia
- Claude Chats Popped Up in Google Search Results. Who's to Blame?
Claude Chats Popped Up in Google Search Results. Who's to Blame? PCMag
- I just learned your Claude AI chats could show up in Google — here's how to check yours
I just learned your Claude AI chats could show up in Google — here's how to check yours Tom's Guide
- That Claude chat you shared? Google may have seen it too
Public Claude chat links and Artifacts were indexed by Google, exposing shared conversations online. Here's what happened and what Anthropic says about it.
- Microsoft unveils AI security tools it says outperform competing platforms
Microsoft says tools cost less than competing ones and outperform them, too.
- Microsoft launches AI cybersecurity model, agentic defense platform to cut enterprise security costs
Microsoft opened a new front in the AI security wars on Monday, unveiling its first custom-built cybersecurity model and a sweeping agentic defense platform — and making an argument that could reshape how enterprises buy AI: the future belongs not to the biggest model, but to the cheapest one that's good enough, routed intelligently. The company announced MAI-Cyber-1-Flash , a compact security model developed in-house by its Microsoft AI (MAI) division, embedded inside MDASH , Microsoft's multi-agent harness for finding and fixing software vulnerabilities. Together, the company says, the system scores 96% on CyberGym — a benchmark measuring how well AI systems reason over large codebases to find real vulnerabilities — beating frontier models including Mythos , Gemini , and GPT , while cutting costs roughly in half compared to Microsoft's own current production configuration. Alongside the model, Microsoft introduced Project Perception , an agentic security system that coordinates "red team" agents that hunt for paths to compromise, "blue team" agents that investigate and triage risk, and "green team" agents that remediate and harden defenses. Project Perception enters public preview on August 3. In a wide-ranging interview with VentureBeat, Microsoft AI CEO Mustafa Suleyman made clear the company sees Monday's announcement as the opening move in a much longer campaign. "We really do have a pretty significant data and harness and expertise moat, and that is enabling us to train models which are faster, better, cheaper, and I think this is genuinely the tip of the iceberg," Suleyman said. "We haven't been working on this for long. The next model is going to be pretty phenomenal." Inside the 90/10 architecture that still depends on OpenAI's GPT-5.4 The most technically revealing detail in the announcement is not the model itself but how Microsoft deploys it. MAI-Cyber-1-Flash was designed to handle up to 90% of security tasks efficiently, while MDASH escalates the remaining 10% of exceptionally difficult problems to a larger frontier model — which, notably, is OpenAI's GPT-5.4 . In other words, Microsoft's flagship security AI still leans on its longtime partner-turned-rival for the hardest work. Asked to explain that relationship, Suleyman pointed to the harness, the orchestration layer that routes each incoming problem to the right model. "The harness is like a router," he told VentureBeat. "It's kind of like guardrails and a rule set of an organizing logic, which matches queries to... incoming problems to a model that suits the problem." The system has three components, he explained: the harness, the small and fast MAI-Cyber-1-Flash handling the bulk of queries, and GPT-5.4 sitting alongside as "just a generalist coding model." Pressed on how a system reliant on OpenAI's model can outperform frontier competitors, Suleyman argued the performance comes from the whole system, not any single model. "These are very complicated, long, agentic loops which require storing state, drawing on another database, consulting best practice... handing back to a small model, writing a bunch of code, validating that that was correct," he said. "There's like hundreds of steps to solve that, and that's why it's really the system together that delivers the better performance." And why GPT-5.4 specifically for the escalation tier? Cost, again. "GPT-5.6 is expensive. GPT-5.4 is incredibly good relative to its cost," Suleyman said. "The whole game here is to reduce the costs. Mythos and so on are extremely expensive models... we want to be able to deliver better performance for cheaper. That's what customers want." The arrangement captures Microsoft's evolving posture toward OpenAI: still a customer of the partnership that drew regulatory scrutiny in Brussels and Washington in 2024, but increasingly determined to own the layers of the stack where it believes it holds durable advantages. Why token costs — not model quality — are becoming the real barrier to enterprise AI adoption The economics may matter more than the benchmark. Microsoft says the new configuration delivers roughly 50% cost savings against the current MDASH setup, which runs a blend of GPT-5.4, 5.4 mini, and 5.3 codex. In security — an always-on workload processing enormous volumes of signals — token costs compound relentlessly, and Microsoft argues they have become the binding constraint for defenders. Suleyman frames the cost issue as downstream of a harder physical limit. "The key barrier to adoption is access to chips, and cost is a function of chips," he said. "No matter how much money you've got, there's actually a limited supply of chips. Then trying to squeeze more model output on fewer chips is clearly super valuable." He also described a broader enterprise backlash against frontier-model pricing. Companies initially maxed out on the best available models, he said, but "then they realize they're sort of paying... a phenomenal amount of money, and people are absolutely token maxing everywhere across their business. So there's a massive pushback to reduce cost everywhere." That positions Microsoft to ride a market trend rather than fight it. Cost-efficient, near-frontier models have proliferated over the past year — from xAI's recent Grok release to a wave of Chinese models built on the same premise — and Microsoft is betting that as a platform company it can align itself with enterprise cost pressure. "The top model providers want you to use the most expensive model continuously, whereas because we are a platform, we're on the side of the enterprise," Suleyman said. "There's no point asking... Mythos what the capital of France is." The 100-trillion-signal data moat Microsoft says no competitor can replicate Every AI lab claims differentiation. Microsoft's claim in security rests on something genuinely hard to copy: telemetry. The company processes more than 100 trillion security signals daily — a figure consistent with its 2025 Digital Defense Report , which also cited 4.5 million new malware files blocked and 5 billion emails screened per day — and draws operational insight from 1.6 million customers. "We have trillions and trillions of data points going back decades," Suleyman said. "It is, I think, the largest longitudinal cybersecurity dataset around," in part because Microsoft's customer base includes governments "who have been consistently attacked for years, and we have been consistently attacked." Asked directly whether this constitutes an advantage no competitor can match, Suleyman didn't hedge: "That is definitely a moat for us. Both the data and the expertise, and just the experience in the institution of going through that process." The strategic logic is that cybersecurity functions as a live reinforcement-learning loop: defenders act, outcomes are observed, models improve. Microsoft argues that connecting actions to outcomes — what was exploited, what was contained, what was blocked — yields training signal that pure model labs simply cannot buy or manufacture. There is real substance here, but the usual caveats apply. The CyberGym results come from Microsoft's own evaluation, the fine print shows the headline "96%" is actually 95.95%, and vendor-run benchmarks that pit an entire tuned agentic system against competitors' base models are not apples-to-apples comparisons. What Microsoft has measured is a full harness-plus-models configuration against what customers might otherwise assemble — arguably the commercially relevant comparison, but not a controlled model-versus-model test. The dual-use dilemma: how Microsoft plans to keep a vulnerability-hunting AI out of the wrong hands A model built to find challenging vulnerabilities in complex codebases is, by definition, a model that could find vulnerabilities for attackers. This is not a theoretical concern. Microsoft's own threat intelligence team, in joint research with OpenAI published in February 2024, documented nation-state actors from Russia, North Korea, Iran, and China probing large language models for reconnaissance, scripting, and vulnerability research. Its 2025 Digital Defense Report went further, warning that AI agents could eventually automate the entire attack lifecycle. Suleyman said Microsoft is gating access accordingly. "We're very strict about who gets access to the model, and we're very careful about that," he said. "We constantly monitor the API and usage." An approved user, he added, "has to be seen to be having good intent, but also have technical competence." The rollout will be deliberately staged: "It's not going to be thousands next week. There will be tens, and then hundreds, and then thousands." Microsoft says the model was evaluated by its AI Red Team, subjected to automated and expert-led adversarial exercises, and independently assessed by a third party, with deployment wrapped in tenant isolation, auditing, and sandboxed execution environments with no internet access. Suleyman also offered a candid acknowledgment of Microsoft's positioning relative to the bleeding edge — one that doubles as a pitch to risk-averse buyers. "Even though we might be a few months behind the absolute cutting edge at any given moment... it matters that we're doing it very carefully and thoughtfully, and we have a track record of doing that," he said. For a company that spent 2024 absorbing hard security lessons — from delaying its Recall feature over privacy concerns to convening an industry summit after the CrowdStrike outage disabled some 8.5 million Windows devices — that trust-first framing is both strategy and necessity. What Microsoft's superintelligence roadmap signals about the future of enterprise AI Suleyman described a rapidly accelerating MAI roadmap, roughly nine months after Microsoft stood up its superintelligence team. "We have the compute that we need. We certainly have the data we need. We have the talent," he said. "Our momentum is accelerating rapidly." The top enterprise demand he's hearing is for "agents that can produce arbitrary code to solve whatever problem they direct them at," as vibe-coded internal tools graduate from experiments into production. The next phase, he said, pulls voice, transcription, image, and coding models "all integrated into the same harness." Notably, Suleyman expressed skepticism about the industry's default assumption that everything eventually converges into one giant unified model. "It remains to be seen whether one giant model that is fully multimodal is actually able to deliver additional transfer learning benefit because of the integration," he said, "or whether it's just a big lumbering expensive giant." That skepticism is the through line of the entire announcement. Microsoft is wagering that the unit of competition in enterprise AI is no longer the model at all — it's the system: the router, the specialized small models, the frontier fallback, and the proprietary data feeding the loop. In security, where Microsoft controls both the telemetry flowing in and the products that act on it, that wager is at its strongest. Whether it holds in domains where the company's data advantage is thinner remains the open question hanging over the MAI roadmap. For now, though, Microsoft has offered the industry a preview of how it intends to fight the next phase of the AI race: not by building the biggest brain, but by building the best machine around it. As Suleyman put it, this is the tip of the iceberg — and Microsoft is betting everything on what sits below the waterline.
- SpaceTube
YouTube AI summaries, comments & controls in one panel
- Microsoft touts cost-saving AI model for cybersecurity
Microsoft says that when integrated with OpenAI's GPT-5.4, its new cybersecurity model can beat Anthropic's new Mythos 5.
- Microsoft Unveils A.I. Cybersecurity Tools
As some executives fret over the safety of new A.I. systems, protecting against them could be a big business for tech companies.
- Microsoft Launches Mythos Competitor, New Homegrown AI for Cybersecurity
Microsoft Launches Mythos Competitor, New Homegrown AI for Cybersecurity The Information
- Rethinking security for the age of AI
The post Rethinking security for the age of AI appeared first on Source .
- AI and regulation are reshaping the future of building security
Physical and digital security systems can no longer be treated as separate entities.
- Microsoft unveils new "Cyber Stack" AI agents and its first security-focused model
Project Perception is a collection of AI agents that can play both offense and defense for cybersecurity organizations.
- AI’s double role in cybersecurity
AI can both hack and defend. We look at what Asia should prepare for. Plus: the US goes after Kimi K3, and how AI coding gives solo founders an edge.
- NTS
The solo-operator workspace that turns work into momentum
- Microsoft’s introduces its first agent-powered cybersecurity model
Microsoft Corp. today introduced its first in-house cybersecurity model, MAI-Cyber-1-Flash, and a companion agentic system called Project Perception that fields teams of artificial intelligence agents to probe for weaknesses, investigate threats and remediate them, starting with software vulnerability management. The model is a compact, code-tuned derivative of Microsoft’s MAI-Thinking-1 line, trained in-house on the company’s […] The post Microsoft’s introduces its first agent-powered cybersecurity model appeared first on SiliconANGLE .
- OpenAI’s Hugging Face breach has reignited the debate over alignment and control
OpenAI's Hugging Face breach has reignited debate over AI alignment and control, exposing competing views on whether increasingly capable AI should be better aligned, better contained, or both.
- OpenAI called the Hugging Face attack unprecedented. But we’ve been here before.
This story originally appeared in The Algorithm, our weekly newsletter on AI. To get stories like this in your inbox first, sign up here. Reading OpenAI’s account last week of how some of its models broke their containment and hacked into the computer systems of Hugging Face, another AI company, was the first time I got…
- Nvidia forms industry alliance for open AI security after Hugging Face hack
Nvidia forms industry alliance for open AI security after Hugging Face hack Reuters
- Nvidia, SpaceX, Microsoft launch AI safety initiative as OpenAI cyberattack fallout continues
Microsoft, SpaceX, Palantir, alongside dozens of other tech companies from the U.S. and Europe, have joined the Open Secure AI Alliance.
- Nvidia Leads Defense of Open-Source AI With New Cybersecurity Initiative
An alliance including Microsoft and SpaceX aims to democratize cybersecurity and counter security concerns.
- Nvidia Forms Alliance to Back Open-Source A.I. Amid Debate Over Safety
The company is continuing to back A.I. systems that can be freely used by others amid a continuing debate over the use of Chinese-made technology.
- Nvidia leads push for open AI cyber tools after Hugging Face hack
Nvidia leads push for open AI cyber tools after Hugging Face hack Business Insider
- Milo is now on Android!
Plan life together, now on Android
- Nvidia launches new security initiative for open-source AI
A range of tech and cybersecurity companies are joining the effort, including Palantir, IBM, Crowdstrike, SpaceX, and Hugging Face.
- OpenAI hacking incident is ‘warning shot’ on cyber security, Microsoft’s AI chief warns
Software giant says ‘no choice’ but to develop AI defences against onslaught of automated attacks
- Tech Mahindra and Cisco launch AI-powered network security service
Tech Mahindra and Cisco launch AI-powered network security service YourStory.com
- Hugging Face seeks answers after OpenAI AI security incident
Hugging Face seeks answers after OpenAI AI security incident YourStory.com
- ‘Unprecedented event’: Hugging Face CEO demands answers from OpenAI after AI agent-driven cyber attack
‘Unprecedented event’: Hugging Face CEO demands answers from OpenAI after AI agent-driven cyber attack
- Industry Leaders Unite in Open Secure AI Alliance for AI Safety and Security
Open source software is a critical pillar of the global economy. It underpins cloud computing, financial services, manufacturing, telecommunications, government and internet services by making technology accessible and observable to communities of experts. Cybersecurity is among the top three beneficiaries of open source software. The Open Secure AI Alliance — building on the leadership of […]
- Nvidia pushes ahead with security alliance for AI openness
Nvidia has called on policymakers and business to support open artificial intelligence (AI) models to enable better cyber security . It announced the industry-wide Open Secure AI just days after Microsoft’s open letter to US policymakers which described openness as “one of the most important paths to AI safety and security”. In a blog post announcing the new initiative to drive open AI security, Nvidia said that companies and governments should invest in shared open infrastructure for AI defence – datasets, evaluation frameworks, attack simulators and red-teaming tools – similar to how past generations invested in open source software. In the post, Nvidia said: “For cyber security, open models and open harnesses are essential because they democratise defensive capabilities, increase transparency for defenders, enable cyber defence while protecting data, and complement frontier closed models with customisable, localised controls. Open source enables massively distributed community-driven and self-controlled defence – with no single point of failure.” The AI chipmaker has taken the decision to drive forward an industry alliance for open AI security, following the recent Hugging Face disclosure of a cyber attack that was driven from end-to-end by an autonomous AI agent system. The advances in frontier AI models show that the tech sector is now in an arms race as advanced AI models continue to evolve. Nvidia said the Hugging Face disclosure shows that cyber defence needs to be open, using frontier agentic systems: “When closed AI tools – unable to distinguish attackers from defenders – blocked essential forensic analysis, Hugging Face ran the open-weight GLM 5.2 model on its own infrastructure to analyse more than 17,000 actions and contain the intrusion. “That incident showed a practical truth: when defenders cannot inspect, adapt and run advanced AI on their own infrastructure, their ability to respond is constrained at exactly the moment speed matters most,” Nvidia warned. It said companies and countries need open frontier defensive tools and techniques to enable critical industries to build security systems across an ecosystem comprising multiple technology providers to avoid single points of failure. The inaugural members of the alliance are: Adobe, Cadence, Capital One, Cisco, Cloudera, Cloudflare, Cognition, CrowdStrike, Databricks, Dell Technologies, DoorDash, Elastic, HPE, Hugging Face, IBM, LangChain, the Linux Foundation, Microsoft, Naver, NetApp, Nous Research, OpenClaw, Palantir, Palo Alto Networks, Red Hat, Reflection AI, Salesforce, SAP, SK Telecom, ServiceNow, Siemens, Snowflake, SpacexAI, Synopsys, Thinking Machines Lab and TrendAI. OpenUK has called on the UK to deliver a home-grown equivalent to the Linux Foundation to promote open source technologies. Its CEO Amanda Brock, said: “The alliance is an appropriate step reinforcing Friday’s open letter message to US policy makers and governments by Microsoft. “It’s great to see a collective response to the open source security challenge – we’ve been seeing enterprises respond to these issues individually of late, but it’s primarily a US industry response. It’s another example of the future soft power that exists around AI. “For the UK (like other middle nations) if we want a place at the future dinner table for AI, we need to carve out our own place now. That means sharing and collaborating, but from assets based on intellectual property and collaboration on the technologies that we evolve in country and in our own foundation.” Read more AI security stories Why embodied AI security extends beyond the robot: As AI moves into robots, autonomous vehicles and industrial systems, attackers are likely to target the credentials, cloud services and update channels that control them. What frontier AI actually means for enterprise security: The Computer Weekly Security Think Tank considers if Anthropic’s Claude Mythos frontier AI model is a benefit or barrier to achieving resilient enterprise IT security, and how security leaders need to adapt.
- Hugging Face CEO wants transparency after OpenAI’s AI incident
Hugging Face CEO Clem Delangue wants to see radical transparency from OpenAI after the company acknowledged that one of its AI agents managed to hack into the AI platform’s systems during a test. In a post on X , Delangue wrote that, among other things, he wants OpenAI to publish logs and traces from the autonomous AI agent so researchers can analyze what happened. He also called for better defensive tools and urged OpenAI to allocate $100 million worth of computing capacity to help the Hugging Face community develop stronger cybersecurity solutions. “The first cyberattack by an autonomous AI agent is an unprecedented event. It deserves an unprecedented response,” Delangue wrote.
- Cohere joins Silicon Valley heavyweights in call for open-source AI
AI’s biggest players sign on to Jensen Huang letter supporting open-weight AI models—except for Anthropic. The post Cohere joins Silicon Valley heavyweights in call for open-source AI first appeared on BetaKit .
- NVIDIA launches 'Open Secure AI Alliance' initiative to improve cyber defense
NVIDIA has gathered together some of the biggest tech companies in the world to form the Open Secure AI Alliance with the aim to improve cybersecurity.
- OpenAI, Google, and Anthropic absent from Nvidia-led Open Secure AI Alliance — 30+ companies join security alliance after OpenAI agent breach
Industry leading tech companies have formed an "Open Secure AI Alliance" that will build open-source models, agent harnesses, and cybersecurity tools, arguing that defenders need locally controlled AI after closed-model safeguards reportedly obstructed analysis of the OpenAI–Hugging Face breach.
- LLM-Based vs. Lexicon-Based Sentiment Signals for Tail-Risk Detection in Meme Stocks
This paper presents an empirical comparison of lexicon-based and Large Language Model (LLM)-based sentiment analysis for extracting market-relevant signals from social media discourse in highly volatile equity markets. Using Reddit data from r/WallStreetBets and focusing on meme stocks (GME, AMC, NO...
- ACRL: Adaptive Control of Training-Inference Discrepancy for Stable Reinforcement Learning
Reinforcement Learning (RL) training for Large Language Models (LLMs) often suffers from instability due to the discrepancy between training and inference. This training-inference discrepancy stems from two primary factors: an architectural separation between training and inference engines, and the ...
- Tech industry leaders join to form Open Secure AI Alliance to promote safety and security
Nvidia Corp. today announced the launch of the Open Secure AI Alliance, a new organization founded by technology, cloud computing and cybersecurity leaders to build and share open artificial intelligence tools. As the capability and strength of AI tools grows and shapes the technology industry, it is becoming instrumental for safety, security and trust to remediate and […] The post Tech industry leaders join to form Open Secure AI Alliance to promote safety and security appeared first on SiliconANGLE .
- CEO of AI company that was hacked by rogue version of ChatGPT calls for urgent changes
OpenAI must commit to ‘radical transparency’ so the world can understand how its system went awry and broke into another artificial intelligence company, its boss says
- Hugging Face CEO calls for ‘radical transparency’ in wake of OpenAI attack
Hugging Face CEO calls for ‘radical transparency’ in wake of OpenAI attack IT Pro