Every published Top AI Stories item tagged with Information & Technology, newest first.
For Global Accessibility Awareness Day on Thursday, Meta announced an expansion of its Be My Eyes partnership that lets blind and low-vision users start hands-free video calls with trusted friends, family, or trained support representatives by saying *"Hey Meta, Be My Eyes with [name]"* on Ray-Ban Meta and Oakley Meta Vanguard glasses. Connected support partners include Tesco, Sony, Amtrak, Hilton, Zain, and Clearblue — covering retail, telecom, consumer electronics, healthcare, travel, and hospitality. Meta also added a customizable one-touch action button for frequent accessibility features, voice-only call controls coming to WhatsApp and Messenger, and a new Wearables Device Access Toolkit for third-party assistive-tech apps. Be My Eyes now reports more than one million blind users and more than ten million sighted volunteers worldwide.
Ahead of the Worldwide Developers Conference on June 8, Apple has registered the subdomain genai.apple.com with its DNS provider — not yet live, but a strong signal the company is staging a developer-facing generative AI surface. Coverage from 9to5Mac and MacRumors over the weekend points to *"Apple Intelligence 2.0"* features including a standalone Siri app, chatbot-style interface, large-language-model-based world knowledge, on-screen awareness, multi-action requests, and a new image-editing extend tool built on Apple Foundation Models. The on-device push is positioned as Apple's answer to Gemini Spark and OpenAI's agent layer; the question is whether the keynote actually ships features developers can call this fall, or repeats last year's *"in a future update"* framing.
Bloomberg reported Friday that Anthropic could close its new financing round as soon as this week, raising more than $30 billion at a post-money valuation above $900 billion. Sequoia Capital, Dragoneer, Altimeter, and Greenoaks Capital Partners are each expected to put in roughly $2 billion as co-leads, with Founders Fund and General Catalyst also participating. The round would vault the Claude maker past OpenAI's $852 billion March mark and follows Anthropic's projection that quarterly revenue will roughly double to $10.9 billion in the second quarter, with annualized run-rate revenue topping $50 billion by the end of June.
An Irish Times analysis published Sunday argues that OpenAI is essentially free to go public — with reports pointing at a September IPO — but Sam Altman is heading into the roadshow with a reputation bruised by a New Yorker profile and by trial testimony in which former colleagues described chaos, shifting strategy, and mistrust inside the company. Internal forecasts reportedly assume an astonishing cash burn of up to $665 billion before the company turns profitable in 2030, while SpaceX is heading for a $1.75 trillion IPO in June and Anthropic is closing a $900 billion round this week. Competition for late-stage AI capital is the real constraint on Altman's window, more than the dismissed Musk suit on its own.
A Gallup poll released this month found that 70 percent of Americans oppose construction of an AI data center in their local community, including 48 percent who say they are *"strongly opposed."* Half of opponents cite excessive use of resources — 18 percent each name water and energy use specifically — while another 16 percent cite pollution and noise. Two-thirds of supporters cite economic benefits, mostly local job creation. The first national survey of public sentiment on the issue lands as Senator Bernie Sanders has introduced moratorium legislation, Maine's legislature has passed and then watched a governor's veto kill a construction ban, and protests have escalated from Tremonton, Utah, to Monterey Park, California — a sign that the *"AI is good for jobs"* pitch is not yet outweighing local concern about water, grid, and noise.
On May 20, the Federal Trade Commission sent warning letters to twelve so-called *"nudify"* websites accused of letting users strip clothing from photos to create non-consensual sexual images, citing violations of the Take It Down Act that took effect May 19. A separate set of reminder letters went to fifteen of the largest US platforms — Alphabet, Amazon, Apple, Automattic, Bumble, Discord, Match Group, Meta, Microsoft, Pinterest, Reddit, SmugMug, Snapchat, TikTok, and X. The law requires covered platforms to remove non-consensual intimate images and known identical copies within 48 hours of a valid request, with civil penalties up to $53,088 per violation; FTC Chairman Andrew Ferguson framed enforcement as a priority for the agency's first synthetic-media docket.
At a press event in Taipei this week, NVIDIA CEO Jensen Huang told reporters the company has *"largely conceded"* China's AI accelerator market to Huawei, with NVIDIA's share now near zero after the US H200 export-clearance stalemate dragged into a second month. Huawei expects roughly $12 billion in 2026 revenue from its Ascend line — up from $7.5 billion in 2025 — on orders already placed by Alibaba, ByteDance, and Tencent, all of which deployed DeepSeek V4 services within hours of the model's Ascend-optimized release in April. Huang said he still expects Beijing to eventually allow H200 imports, but for now the homegrown stack is shipping while NVIDIA's clearance letters sit in customs.
NVIDIA Labs has quietly posted Nemotron Diffusion to Hugging Face — a 14-billion-parameter language model that switches between autoregressive decoding, parallel diffusion decoding, and a *"self-speculation"* mode that drafts with diffusion and verifies with autoregression, all without changing model weights. The accompanying technical report claims a 2.2-times throughput lift over the comparable Qwen 3 8-billion-parameter baseline at matched accuracy, scaling to 850 tokens per second on a GB200 (a 3.3-times lift). Base, instruct, and vision-language variants are all open-weight; the architecture is positioned as a path from memory-bound to compute-bound inference as GPUs keep outrunning memory bandwidth.
The Verge reports that Microsoft will stop issuing Claude Code licenses to its own employees effective June 30, redirecting users to GitHub Copilot CLI. The original internal pilot — meant to expose project managers and designers to AI coding for the first time — reportedly burned through Microsoft's 2026 AI budget in months, with one employee reporting Claude consumed their monthly token allocation in just over a week. Hacker News commenters framed the move as procurement economics, not contractual or security friction, and noted developers picked Claude over Copilot when offered the choice — undermining Microsoft's own product strategy.
Anthropic published the first results from Project Glasswing, a partnership with roughly 50 organizations using its unreleased Claude Mythos Preview model to scan critical infrastructure software for vulnerabilities. In a single month, partners found more than 10,000 high- or critical-severity bugs — Cloudflare alone surfaced 2,000, and the UK's AI Security Institute confirmed Mythos as the first model to solve both of its cyber-range simulations end-to-end. Alongside the results, Anthropic launched Claude Security in public beta for Enterprise customers and opened a Cyber Verification Program for legitimate security research. Mythos-class models remain unreleased pending stronger misuse safeguards.
Daniel Stenberg, the longtime curl maintainer, published a first-party assessment of Anthropic's Claude Mythos Preview after Project Glasswing scanned 178,000 lines of curl source code. The model surfaced 5 suspected vulnerabilities — reducing on review to **1 confirmed low-severity CVE plus roughly 20 bugs that were not vulnerabilities** — and Stenberg concluded the bigger narrative around Mythos so far "was primarily marketing." His benchmark is direct: AISLE, Zeropath, and OpenAI's Codex Security have together driven 200 to 300 bug fixes for curl over the past 8 to 10 months, and he sees "no evidence that this setup finds issues to any particular higher or more advanced degree" than those tools. He does grant that all modern AI code analyzers — Mythos included — are substantially better than traditional static analyzers at finding security flaws.