近期 AI 新闻与官方动态

Simon Willison's AI Notes 发布的媒体报道：Dropped this morning by the Vatican: Magnifica Humanitas of His Holiness Pope Leo XIV on Safeguarding the Human Person in the Time of Artificial Intelligence . This is a very interesting document. It's some of the clearest writing I've seen on the ethics of integrating AI into modern society. Pope Leo XIV chose the name Leo in honor of Pope Leo XIII, who is known for his 1891 Rerum novarum encyclical on "Rights and Duties of Capital and Labor". This story on Vatican News further clarifies the significance of that decision: Meeting with the College of Cardinals for their first formal encounter after his election, Pope Leo XIV explained part of the reason for the choice of his papal name. "There are different reasons for this," he said, before going on to explain that he chose the name Leo "mainly because Pope Leo XIII, in his historic encyclical Rerum novarum addressed the social question in the context of the first great industrial revolution." "In our own day," he continued, "the Church offers to everyone the treasury of her social teaching in response to another industrial revolution and to developments in the field of artificial intelligence that pose new challenges for the defence of human dignity, justice, and labour." And now we get Pope Leo XIV's own encyclical on the AI revolution. There's a lot in here, but the writing style is very approachable, including to non-Catholics. A few of my highlights (I listened to most of the encyclical on a walk with our dog, my first time trying the ElevenReader iPhone app . It worked very well: I pasted in a URL to the document and it read it to me in a very high quality voice, highlighting each paragraph as it went.) Here are some of my highlights. In each case below emphasis is mine. Here's a useful description of the interpretability problem for LLMs in section 98: First, any statement regarding AI risks becoming quickly outdated, given the remarkable pace at which these systems are developing. Second, all of us, including those who design them, possess only a limited understanding of their actual functioning. Indeed, current AI systems are more “cultivated” than “built,” for developers do not directly design every detail, but instead create a framework within which the intelligence “grows.” As a result, fundamental scientific aspects — such as the internal representations and computational processes of these systems — remain, at present, unknown. I liked section 83's description of the relationship between development and dignity: For individuals as well as for nations, development is both a duty and a right. Minimum conditions are required for enabling every person and people to flourish in accord with their dignity, without being kept in a state of dependence or excluded from access to necessary goods. Development is truly human when it places people at the center instead of the accumulation of wealth, and when it concerns peoples as well as individuals. Justice demands the recognition of the rights of society and the rights of peoples, and includes a responsibility toward future generations. Development is not truly human if it increases consumption for some while shifting costs and burdens onto others, or relegates entire regions to subordinate roles, preventing them from realizing their full potential . Baked in cultural biases and sycophancy get a mention in section 100: In personal use, three aspects in particular deserve careful consideration: the ease with which results are obtained, the impression of objectivity and the simulation of human communication. The speed and simplicity with which information, complex analyses, media content and practical assistance can be accessed undoubtedly makes life easier. Yet they can also encourage excessive reliance and the search for ready-made answers, and weaken personal creativity and judgment. The apparent objectivity of the responses and suggestions these systems provide can lead us to overlook the fact that they reflect the cultural assumptions of those who designed and trained them, with all their strengths and limitations . The artificial imitation of positive human communication — words of advice, empathy, friendship and even love — can be engaging and at times genuinely helpful. However, for less discerning users, it can also be misleading, creating the illusion of a relationship with a real personal subject . When words are simulated, they do not build genuine relationships, but only their appearance. The artificial imitation of care or support can become particularly risky when it enters contexts where real relationships and emotional bonds are lacking. 101 touches on the environmental impact: Current AI systems require enormous amounts of energy and water, significantly influencing carbon dioxide emissions, and place heavy demands on natural resources. As their complexity increases, especially in the case of large language models, the need for computing power and storage capacity grows too, which requires an extensive network of machines, cables, data centers and energy-intensive infrastructure . For this reason, it is essential to develop more sustainable technological solutions that reduce environmental impact and help protect our common home. 102 covers the risks of algorithmic systems making decisions that impact people's lives without "compassion, mercy, forgiveness": The use of AI is never a purely technical matter: when it enters processes that affect people’s lives, it touches on rights, opportunities, status and freedom . Important and sensitive decisions — concerning employment, credit, access to public services or even a person’s reputation — risk being fully delegated to automated systems that do not know “compassion, mercy, forgiveness, and above all, the hope that people are able to change,” and can therefore give rise to new forms of exclusion. 105 emphasizes the need for human accountability in how these systems are applied: For AI to respect human dignity and truly serve the common good, responsibility must be clearly defined at every stage: from those who design and develop these systems to those who use them and rely on them for concrete decisions . In many cases, however, the internal processes leading to a result remain opaque, making it harder to assign responsibility and correct errors. This is where accountability becomes crucial: the possibility of identifying who must “account” for decisions, justify them, monitor them, and, when necessary, challenge them and remedy any harm caused . And 108 touches on the way AI amplifies the power of those with resources: In fact, as with every major technological shift, AI tends to amplify the power of those who already possess economic resources, expertise and access to data . In light of the common good and the universal destination of goods, this raises serious concerns, since small but highly influential groups can shape information and consumption patterns, influence democratic processes and steer economic dynamics to their own advantage, undermining social justice and solidarity among peoples. For this reason, it is essential that the use of AI, especially when it touches on public goods and fundamental rights, be guided by clear criteria and effective oversight, grounded in participation and subsidiarity. That same section explicitly calls out data as something that should be thought of more as a public good: [...] Moreover, ownership of data cannot be left solely in private hands but must be appropriately regulated. Data is the product of many contributors and should not be treated as something to be sold off or entrusted to a select few . It is necessary to think creatively in order to manage data as a common or shared good, in a spirit of participation, as Saint John Paul II already suggested regarding collective goods. Given that Palantir is named after a Lord of the Rings reference, I can't help but wonder if the J.R.R. Tolkien quote from The Return of the King (section 213) was the Pope throwing a little shade at Peter Thiel. The twentieth-century Catholic author J.R.R. Tolkien, in the words of a protagonist in one of his novels, described our responsibility in this way: “It is not our part to master all the tides of the world, but to do what is in us for the succour of those years wherein we are set, uprooting the evil in the fields that we know, so that those who live after may have clean earth to till.” The civilization of love will not arise from a single or spectacular gesture, but from the sum total of small and steadfast acts of fidelity that serve as a bulwark against dehumanization. For this reason, it is worthwhile pausing to reflect on some aspects of how we, each in our own way, can cooperate in building the civilization of love. Another 2026 prediction down On 6th January this year I joined the Oxide and Friends 2026 predictions podcast episode to talk about predictions for 2026, 2029 and 2032. I wrote mine up here , with hindsight they weren't nearly ambitious enough - it's already undeniable that LLMs write good code, we've made huge advances in sandboxing and New Zealand kākāpō have indeed had a truly excellent breeding season . There's one segment from the episode that I didn't bother to include in my write-up, but that I can't resist providing as a lightly-edited transcript here: Bryan Cantrill: 37:13 I think that AI has created some real public perception problems for itself. And I think that you are gonna have one of the frontier model companies, this year, have a white paper explaining how the proliferation of AI will mean prosperity for everybody. They will be trying to make some economic argument - because this is gonna be a 2026 election issue, how we think of these things and how they are regulated and it's a big mess. There's more heat than light in this debate. Simon Willison: 38:05 I'd like to tag something on to that one: I think that only works if they can sort of wash that through existing trusted experts. Sam Altman and Dario are constantly publishing essays about this stuff and nobody believes a word they say. Get Barack Obama's signature on one of these position papers and maybe you've got something people might start to trust a little bit. Adam Leventhal: 38:27 Otherwise, it's just like "leaded gas is good for you", says Exxon. Bryan Cantrill: 38:31 I mean, yeah. God. Obama... let's go with that, that's a great one because if it's like Bill Clinton everyone's gonna kind of roll their eyes, so it's gotta be someone who's got real credibility saying that this is gonna be broad-based... I'd say if they get that person to do it, it's gonna be revealed that that's also a bit crooked. Simon Willison: 38:57 How about the Pope? Bryan Cantrill: 39:01 The Pope is very into this stuff! That's a great prediction. We've hit pay dirt. The Pope weighing in on LLMs and their economic impact on the world. Simon, I'm giving you full credit if the Pope weighs in believing that this is gonna be economic devastation. My prediction here looks a whole lot less insightful given the Leo XIV/Leo XIII relationship, which I was unaware of when we recorded the episode! Tags: predictions , ai , kakapo , generative-ai , llms , bryan-cantrill , ai-ethics

TechCrunch AI 发布的媒体报道：The nine-year-old startup is replacing hundreds of employees with thousands of AI agents.

TechCrunch AI 发布的媒体报道：Pope Leo XIV's first encyclical uses AI as a lens to diagnose older problems: concentrated power, eroding democracy, and a tech elite that shapes the world to its own advantage.

TechCrunch AI 发布的媒体报道：We're in the transition period -- all of us.

Simon Willison's AI Notes 发布的媒体报道：The most frustrating failure mode right now is that people submit issues that are not in their own voice. They contain an observed problem somewhere, but it has been thrown into a clanker and the clanker reworded it and made a huge mess of it. Typically, it was prompted so badly that the conclusions produced are more often than not inaccurate but always full of confidence. The result is complete guesswork on root causes, fake-minimal repros, suggested implementation strategies, analogies to adjacent but often the wrong code, and long lists of error classes that might or might not matter. [...] So at least personally, I increasingly want issue reports to be condensed to what the human actually observed: I ran this command. I expected this to happen. This happened instead. Here is the exact error or log. — Armin Ronacher , on slop issues filed against Pi Tags: armin-ronacher , open-source , ai , generative-ai , llms , slop , ai-ethics , github-issues , coding-agents , pi

TechCrunch AI 发布的媒体报道：Like other AI wearables, Amazon's Bee offers an odd combination of convenience and privacy anxiety.

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TechCrunch AI 发布的媒体报道：People used AI on a spectrogram image of cockpit recordings to reconstruct them, forcing the NTSB to temporarily block access to its docket system.

Simon Willison's AI Notes 发布的媒体报道：The memory shortage is causing a repricing of consumer electronics David Oks provides the clearest explanation I've seen yet of why consumer products that use memory are likely to get significantly more expensive over the next few years. The short version is that memory manufacturers - of which there are just three remaining large companies - have a fixed capacity in terms of how many wafers they can process at any one time. This fixed wafer capacity is then split between DDR - used in desktops and servers, LPDDR - used in mobile phones and low-energy devices, and HBM - used with GPUs. Until recently, HBM got just 2% of that wafer allocation. The enormous growth in AI data centers has pushed that up to an expected 20% by the end of 2026, and "a single gigabyte of HBM consumes more than three times the wafer capacity that a gigabyte of DDR or LPDDR does". Memory companies have learned from the extinction of their rivals that you should always under-provision rather than over-provision your fabricator capacity. The profit margins and demand for HBM (high-bandwidth memory) will constrain the production of consumer-device RAM for several years. This is already being felt in the sub-$100 smartphone market, which is particularly important to markets like Africa and South Asia. (The original title of the piece was "AI is killing the cheap smartphone" but I'm using the Hacker News rephrased title, which I think does more justice to the content.) Via Hacker News Tags: memory , ai , ai-ethics

TechCrunch AI 发布的媒体报道：Some AI startups are stretching traditional revenue metrics when talking about progress publicly. And their investors are fully aware.

Google AI Blog 发布的官方公司发布：A recap of the 2026 I/O Dialogues, where leaders discuss the future of AI, quantum computing, robotics and creativity.

TechCrunch AI 发布的媒体报道：After Google Search's AI update, the word "disregard" now effectively breaks the search interface.

TechCrunch AI 发布的媒体报道：Google demoed prototype Android XR glasses that overlay Gemini-powered translation, navigation, and other information directly into your field of view.

MIT Technology Review 发布的媒体报道：This is today’s edition of The Download, our weekday newsletter that provides a daily dose of what’s going on in the world of technology. Anthropic’s Code with Claude showed off coding’s future—whether you like it or not At Anthropic’s developer event in London this week, Code with Claude, attendees were asked if they’d shipped code…

MIT Technology Review 发布的媒体报道：During Tuesday’s Google I/O keynote, Demis Hassabis, the CEO of Google DeepMind, proclaimed that we are currently “standing in the foothills of the singularity.” It was a striking statement—the singularity is the theoretical future moment when AI rapidly exceeds human intelligence and dramatically transforms the world. But what struck me as I listened in the…

MIT Technology Review 发布的媒体报道：Listen to the session or watch below AI companies want to build systems that understand the external world and overcome the limitations of LLMs. Recent developments have brought world models to the forefront of the AI discussion. Watch a conversation with editor in chief Mat Honan, senior AI editor Will Douglas Heaven, and AI reporter…

Simon Willison's AI Notes 发布的媒体报道：We just announced the first release of Datasette Agent , a new extensible AI assistant for Datasette. I've been working on my LLM Python library for just over three years now, and Datasette Agent represents the moment that LLM and Datasette finally come together. I'm really excited about it! Datasette Agent provides a conversational interface for asking questions of the data you have stored in Datasette. Add the datasette-agent-charts plugin and it can generate charts of your data as well. The demo The announcement post (on the new Datasette project blog) includes this demo video : I recorded the video against the new agent.datasette.io live demo instance, which runs Datasette Agent against example databases including the classic global-power-plants by WRI , and a copy of the Datasette backup of my blog. The live demo runs on Gemini 3.1 Flash-Lite - it's cheap, fast and has no trouble writing SQLite queries. A question I asked in the demo was: when did Simon most recently see a pelican? Which ran this SQL query : SELECT title, commentary, created FROM blog_beat WHERE beat_type = ' sighting ' AND (title LIKE ' %pelican% ' OR commentary LIKE ' %pelican% ' ) ORDER BY created DESC LIMIT 5 And replied: The most recent sighting of a pelican by Simon was recorded on May 20, 2026 . The observation included a California Brown Pelican, along with a Common Loon, Canada Goose, Striped Shore Crab, and a California Sea Lion. Here's that sighting on my blog , and the Markdown export of the full conversation transcript. The plugins My favorite feature of Datasette Agent is that, like the rest of Datasette, it's extensible using plugins. We've shipped three plugins so far: datasette-agent-charts , shown in the video, adds charts to Datasette Agent, powered by Observable Plot . datasette-agent-openai-imagegen adds an image generation tool to Datasette Agent using ChatGPT Images 2.0 . datasette-agent-sprites provides tools for executing code in a Fly Sprites persistent sandbox. Building plugins is really fun . I have a bunch more prototypes that aren't quite alpha-quality yet. Claude Code and OpenAI Codex are both proving excellent at writing plugins - just point them at a checkout of the datasette-agent repo for reference and tell them what you want to build! Running it against local models I've also been having fun running the new plugin against local models. Here's a uv one-liner to run the plugin against gemma-4-26b-a4b in LM Studio on a Mac: uvx --prerelease=allow \ --with datasette-agent --with llm-lmstudio \ datasette --internal internal.db --root \ -s plugins.datasette-llm.default_model lmstudio/google/gemma-4-26b-a4b \ data.db Datasette Agent needs reliable tool calls and the ability for a model to produce SQL queries that run against SQLite. The open weight models released in the past six months are increasingly able to handle that. What's next Datasette Agent opens up so many opportunities for the LLM and Datasette ecosystem in general. It's already informed the major LLM 0.32a0 refactor which I'm nearly ready to roll into a stable release, maybe with some additional "LLM agent" abstractions extracte from Datasette Agent itself. I've been exploring my own take on the Claude Artifacts, which is shaping up nicely as a plugin. I'm excited to use Datasette Agent to build my own Claw - a personal AI assistant built around data imported from different parts of my digital life, which is a neat excuse to revisit my older Dogsheep family of tools. We'll also be rolling out Datasette Agent for users of Datasette Cloud . Join our #datasette-agent Discord channel if you'd like to talk about the project. Tags: projects , sqlite , ai , datasette , generative-ai , llms , llm , uv , datasette-agent

TechCrunch AI 发布的媒体报道：Spotify is partnering with Universal Music Group to let Premium subscribers create AI-generated song covers and remixes, with participating artists receiving a share of the revenue.

TechCrunch AI 发布的媒体报道：Google is about to look really different, and if you're not a fan of the AI overview feature, then you're not going to like what's coming.

MIT Technology Review 发布的媒体报道：Storytelling is core to humanity’s DNA, stemming from our impulse to express ideals, warnings, hopes, and experiences. Technology has always been woven through the medium and the distribution: from early humans’ innovation of natural pigments and charcoals for cave paintings to literal representation by the camera. The landscape of storytelling continues to shift under our…