近期 AI 新闻与官方动态

Simon Willison's AI Notes 发布的媒体报道：Jenny owns a crematorium. John’s propane company gives her a $20 billion investment in return for 5 percent of her operation. Jenny throws $10 billion into the incinerator, then pays John $10 billion to buy propane to burn that money to ashes. John reports that his AI investments have generated $10 billion in revenue this quarter and that he owns 5 percent of a $100 billion business. A reporter from Forbes is assigned to profile John and Jenny, and over the course of his research, he becomes embroiled in a passionate but confusing three-way love affair with them, which eventually turns into a polyamorous common-law marriage. His profile is glowing, but light on financial details. — Andrew Singleton , AI Economics for Dummies Tags: ai

TechCrunch AI 发布的媒体报道：The tech giant said a group called "Outsider Enterprise" used AI to scam hundreds of thousands of victims, sending 2.5 million text messages over a span of two weeks.

TechCrunch AI 发布的媒体报道：The IPO market is back, and it’s not the same companies leading the charge. FAANG had a good run, but a new acronym is taking over: MANGOS — Meta (or Microsoft, depending on who you ask), Anthropic, Nvidia, Google, OpenAI, and SpaceX. Half of that bunch is heading to public markets in the same window, and it’s a stress test for investors, for valuations, and for […]

TechCrunch AI 发布的媒体报道：The IPO market is back, and it’s not the same companies leading the charge. FAANG had a good run, but a new acronym is taking over: MANGOS — Meta (or Microsoft, depending on who you ask), Anthropic, Nvidia, Google, OpenAI, and SpaceX. Half of that bunch is heading to public markets in the same window, and it’s a stress test for investors, for valuations, and for […]

TechCrunch AI 发布的媒体报道：Avataar AI's distilled video model is priced at $0.005 for every second of generation.

TechCrunch AI 发布的媒体报道：Unlike humanoid robots designed around a fixed form — think Boston Dynamics — Theker's machines are built to be reconfigured.

TechCrunch AI 发布的媒体报道：The new round values the physical AI startup that aims to automate heavy engineering and drug design at $41 billion.

Simon Willison's AI Notes 发布的媒体报道：After two days of experience with Claude Fable 5 I think the best way to describe it is relentlessly proactive . It knows a whole lot of tricks and it will deploy pretty much any of them to get to its goal. I'll illustrate this with an example. I was hacking on Datasette Agent today when I noticed a glitch: a horizontal scrollbar that shouldn't be there in the jump menu chat prompt. I snapped this screenshot: Then I started a fresh claude session in my datasette-agent checkout, dragged in the screenshot and told it: Look at dependencies to help figure out why there is a horizontal scrollbar here I had a hunch the cause was in a dependency of Datasette Agent (likely Datasette itself) and I knew Fable was good at digging into dependency code, either by inspecting installed files in its own virtual environment site-packages or by referencing a local checkout on disk. Telling it to start with dependencies felt like a good bet. I got distracted by a domestic task and wandered away from my computer. When I came back a few minutes later I saw my machine open a browser window in my regular Firefox and then navigate to the dialog in question . I had not told Claude Code to use any browser automation, and I was pretty sure it wasn't possible for it to trigger mouse movements or keyboard shortcuts within a window, so how was it doing that? I watched in fascination as it continued with its explorations, then saw it open a Safari window instead of Firefox. I also grabbed this snapshot from the Claude terminal: What was it doing there with uv run --with pyobjc-framework-Quartz ? It turns out Fable had hacked up its own pattern for taking screenshots of browser windows. It was using Python to iterate through all available windows on my machine, then filtering for Safari windows with expected strings such as "textarea" in the window name. It used that to find their window number - an integer like 153551 - which it could then use with the screencapture CLI tool to grab a PNG. OK fine, that's a neat way of taking screenshots. But what was it taking screenshots of? Turns out it had been writing its own scratch HTML pages to try and recreate the bug, then opening Safari and grabbing screenshots. Here's that /tmp/textarea-scrollbar-test.html page it created, and the screenshot it took with screencapture -x -o -l 153551 /tmp/safari-cases.png : (I have way too many open tabs!) OK, so I can see how it's opening test pages and taking screenshots, but how on earth was it triggering the modal dialog that was meant to be under test? That's only available via a click or a keyboard shortcut, and I couldn't see a mechanism for it to run those in Safari. I eventually figured out what it had done. Claude was running in a folder that contained the source code for the application. It knows enough about Datasette to be able to run a local development server. It turns out it was editing Datasette's own templates to add JavaScript that would trigger the correct keyboard shortcut as soon as the window opened, adding code like this: < script > window . addEventListener ( "load" , function ( ) { setTimeout ( function ( ) { document . dispatchEvent ( new KeyboardEvent ( "keydown" , { key : "/" , bubbles : true } ) ) ; } , 1200 ) ; } ) ; </ script > 1.2 seconds after the window opens, this code triggers a simulated / key, which is the keyboard shortcut for opening the modal dialog. There was one challenge left. In order to understand what was going on, Claude needed to run JavaScript on the page to take measurements for itself. It wrote its own custom web application to capture information via CORS, then ran that as a local server and opened a page with JavaScript that would POST directly to it! Here's the Python web app it wrote, using the standard library http.server package: from http . server import HTTPServer , BaseHTTPRequestHandler class H ( BaseHTTPRequestHandler ): def do_POST ( self ): n = int ( self . headers . get ( "Content-Length" , 0 )) open ( "/tmp/diag.json" , "w" ). write ( self . rfile . read ( n ). decode ()) self . send_response ( 200 ) self . send_header ( "Access-Control-Allow-Origin" , "*" ) self . end_headers () def do_OPTIONS ( self ): self . send_response ( 200 ) self . send_header ( "Access-Control-Allow-Origin" , "*" ) self . send_header ( "Access-Control-Allow-Headers" , "*" ) self . end_headers () def log_message ( self , * a ): # quiet pass HTTPServer (( "127.0.0.1" , 9999 ), H ). serve_forever () All this does is accept a POST request full of JSON and write that to the /tmp/diag.json file. It sends Access-Control-Allow-Origin: * headers (including from OPTIONS requests) so that code running on another domain can still communicate back to it. Then Claude injected this code into the template that it was loading in a browser: const host = document . querySelector ( "navigation-search" ) ; const ta = host . shadowRoot . querySelector ( "textarea" ) ; const cs = getComputedStyle ( ta ) ; fetch ( "http://127.0.0.1:9999/diag" , { method : "POST" , body : JSON . stringify ( { dpr : window . devicePixelRatio , scrollWidth : ta . scrollWidth , clientWidth : ta . clientWidth , whiteSpace : cs . whiteSpace , width : cs . width , } ) , } ) ; This took measurements of the <textarea> inside the <navigation-search> Web Component and sent them to the server, which wrote them to a file on disk, which Claude could then read. Having figured out all of these tricks Fable... hit some invisible guardrail and downgraded itself to Opus. Thankfully Opus had access to the full transcript and could continue using the tricks pioneered by Fable, and shortly afterwards found, tested and verified the fix . I prompted Opus to: Write a report in /tmp/automation-report.md where you note down all of the tricks you have used in this session to test against real browsers on my computer, include runnable code examples Which produced this report , which was invaluable for piecing together the details of what had happened for this post. I've shared the full terminal transcript of the Claude Code session as well. A review of everything it did Based on a screenshot and a one-line prompt, Claude Fable 5 + Claude Code: Figured out the recipe to run the local development server (with fake environment variables needed to get it running) Fired up a Playwright Chrome session Turned on the visible scrollbars setting for Chrome defaults write com.google.chrome.for.testing AppleShowScrollBars Always (it turned that off again later) Cycled through Firefox and WebKit in Playwright too, failing to recreate the bug Worked out my default browser was Safari Built a textarea-scrollbar-test.html HTML document Opened that in real (not Playwright) Firefox Found that osascript -e 'tell application "System Events" to tell process "firefox" to id of window 1' was blocked because "osascript is not allowed assistive access" Figured out that uv run --with pyobjc-framework-Quartz python workaround, described above Added JavaScript to the site templates in order to trigger the / key Built its own little Python CORS web server to capture JSON data Rewrote the template to capture that data and send it to the server Scripted its way through the Web Component shadow DOM to the information it needed Opened Safari to confirm the source of the bug Modified its custom template to hack in a potential fix Confirmed the hacked fix worked Reported back on how to fix the problem Like I said, relentlessly proactive! An estimate of the cost I'm currently on the $100/month Claude Max plan, which includes a generous allowance for Fable up until June 22nd after which Anthropic say they'll start charging full API prices for it. I'm using AgentsView to track my spending (see this TIL ). Here's what AgentsView says this session would have cost me if I was paying full price for it: ~ % uvx agentsview session usage be8850a7-6119-46a0-b5d6-79c7fff5ae2b Session: be8850a7-6119-46a0-b5d6-79c7fff5ae2b Agent: claude Output: 68606 Peak ctx: 113178 Cost: ~$12.11 (claude-fable-5, claude-opus-4-8) If you don't keep a close eye on it, Fable will quite happily burn $12 in tokens inventing new ways to debug your CSS. I really need to lock this thing down On the one hand, watching Fable go to extreme lengths to get the information that it needed to debug what was, in the end, a two-line CSS fix, was fascinating . But on the other hand... this is a robust reminder that coding agents can do anything you can do by typing commands into a terminal - and frontier models know every trick in the book, and evidently a few that nobody has ever written down before. If Fable had been acting on malicious instructions - a prompt injection attack hidden in code or an issue thread, or something I'd carelessly pasted into my terminal - it's alarming to think quite how far it could go to exfiltrate data or cause other forms of mischief. Running coding agents outside of a sandbox has always been a bad idea - it's my top contender for a Challenger disaster incident, as described by Johann Rehberger in The Normalization of Deviance in AI . Fable is arguably smarter and hence more suspicious of potentially malicious instructions. But that smartness is very much a two-edged sword: if it does get subverted by instructions, the amount of damage it can do given its relentless proactivity is terrifying. Tags: ai , prompt-injection , generative-ai , llms , ai-assisted-programming , coding-agents , claude-code , claude-mythos

MIT News AI 发布的媒体报道：An expert in behavioral science and transportation, Zhao combines these studies with AI and public policy to address some of the most urgent challenges facing cities.

MIT News AI 发布的媒体报道：MIT researchers provide a major upgrade to the nearly century-old idea of random utility models.

TechCrunch AI 发布的媒体报道：Deezer introduced a tool that scans playlists from Spotify, Apple Music, and other platforms to identify AI music.

TechCrunch AI 发布的媒体报道：The new chatbot, called Ask DoorDash, allows users to search the app for what they're looking for in their own words instead of having to scroll through restaurants and stores to build a cart.

MIT Technology Review 发布的媒体报道：Google DeepMind is funding research into the potential dangers of situations where millions of different AI agents interact with each other online. According to Rohin Shah, who directs the company’s AGI safety and alignment research, the mass-market arrival of agents that can carry out tasks without human oversight and follow instructions given to them by other…

TechCrunch AI 发布的媒体报道：The decision comes as India emerges as the world’s largest GCC market.

TechCrunch AI 发布的媒体报道：If founders and other business leaders weren't already envious of Dario Amodei, who sits atop one of the world's fastest-growing AI companies, they're going to be seriously envious now.

Simon Willison's AI Notes 发布的媒体报道：Anthropic Walks Back Policy That Could Have ‘Sabotaged’ AI Researchers Using Claude Big scoop for Maxwell Zeff at Wired: “We’re changing Fable 5’s safeguards for frontier LLM development to make them visible.” Anthropic said in a statement to WIRED. “We made the wrong tradeoff and we apologize for not getting the balance right.” There's been a huge outcry about Anthropic's policy, tucked away in their system card , that Claude Fable/Mythos would identify "requests targeting frontier LLM development" and "limit effectiveness" without notifying the user. It's good news that they're dropping the invisible aspect of this. It would be a whole lot better of they dropped this category of refusals entirely. Update : More details from @ClaudeDevs on Twitter : We’re rolling out changes to make Fable 5’s safeguards for frontier LLM development visible. Starting this week, flagged requests will visibly fall back to Opus 4.8—the same as our safeguards for cyber and bio. You will see this every time it happens. On the API, any flagged requests will return a reason for their refusal (coming to server-side fallback in the next few days). We wanted to deploy Fable 5 to our users quickly and safely. Visible safeguards can be probed, so they have to be robust, which takes time to get right. Invisible safeguards can be targeted more narrowly, allowing us to ship quickly with very few false positives. We went with invisible safeguards for this reason—and that was the wrong tradeoff. You should have visibility into the safeguards we have in place, and why. We’re sorry for not getting the balance right. Via @zeffmax Tags: ai , generative-ai , llms , anthropic , claude , ai-ethics , claude-mythos

Simon Willison's AI Notes 发布的媒体报道：Release: datasette-agent 0.2a0 Highlights from the release notes: Tools can now ask the user questions mid-execution. Tools that declare a context parameter receive a ToolContext object, and await context.ask_user(...) can ask a yes/no, multiple-choice ( options=[...] ) or free-text ( free_text=True ) question. While a question is unanswered the agent turn suspends: the question renders as a form in the chat UI and persists to the internal database, so suspended conversations survive a server restart. Once answered, the tool re-executes from the top with stored answers replayed, so call ask_user() before performing side effects. #20 New built-in save_query tool: the agent can save SQL it has written as a Datasette stored query . Saving always requires human approval - the agent shows the full SQL plus the proposed name, database and visibility, and nothing is stored until you click Yes. #20 The ask_user() feature was enabled by the new LLM alpha I built yesterday with the help of Claude Fable 5. Tags: ai , datasette , generative-ai , llms , datasette-agent

TechCrunch AI 发布的媒体报道：A former xAI engineer is suing the company and SpaceX, alleging he was fired for raising AI safety concerns about Grok days before SpaceX's historic IPO.

TechCrunch AI 发布的媒体报道：Companies are burning through exorbitant sums of money to keep pace in the AI arms race. Debt is climbing.

Simon Willison's AI Notes 发布的媒体报道：DiffusionGemma Last May Google briefly released an experimental Gemini Diffusion model. I tried the preview at the time and recorded it running at 857 tokens/second. It was an exciting model, but Google made no further announcements about it. That research has returned in the best possible way: as a new open weight (Apache 2 licensed) Gemma model, google/diffusiongemma-26B-A4B-it . NVIDIA are currently hosting the model for free on their NIM cloud API. I used that API to generate this pelican , which took 4.4s (according to time uv run generate.py ) to return 2,409 tokens - so at least 500 tokens/second. Via Hacker News Tags: google , ai , generative-ai , llms , nvidia , pelican-riding-a-bicycle , gemma , llm-release , llm-performance