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最新 AI 资讯
Anthropic’s Job Interview Asks If AI Safety is Worth Letting Its Stock Go to Zero: Report
The question was a part of Anthropic’s culture interview, which all candidates go through with an employee selected to conduct it.
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OpenAI is Getting Nervous About Reinforcement Learning
The company’s latest training pause highlights growing concerns that models can develop unexpected capabilities faster than labs can evaluate and control them.
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Think360.ai Certified as a Best Firm for AI Professionals
Think360.ai has been certified by AIM as a Best Firm for AI Professionals, recognising its culture of learning, collaboration and hands-on AI work.
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65 Languages, 156,000 Speakers: How IISc Is Teaching AI to Listen to India
IISc’s SPIRE Lab, in collaboration with ARTPARK and with support from Google, has released SraVaani 1.0, an open-source speech recognition model.
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Sam Altman Admits He Was Wrong on AI Adoption Timelines
Altman observed that people and companies tend to continue using the products and workflows they are familiar with even as new technology becomes available.
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Shopify CEO Builds Open-Source Git Server Over a Weekend
Tobias Lütke said he was inspired by Cursor’s “Git at Scale” post, which came just as he was frustrated with Shopify’s internal Git system.
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Hugging Face Explores Sale at Valuation of $13 Bn: Report
The reported valuation would be nearly 3x Hugging Face’s last known valuation of $4.5 billion in 2023.
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NVIDIA in Talks to Invest in Perplexity at $30 Bn Plus Valuation: Report
The talks come as Perplexity’s annualised revenue crosses $750 million, fuelled by rapid growth in its AI search and agent products.
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A Mysterious AI Model Called Ox Alpha Is Winning Over Developers
Early tests have put the model ahead of several leading AI systems on software engineering tasks.
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Linkdaze’s smart calendar is built to run a household, not just track a schedule
With back-to-school season approaching (or already here in some places), keeping track of everyone’s schedules can get pretty chaotic. Between work, school, appointments, sports, chores, and everything else going on, a regular paper calendar just doesn’t cut it. That’s whereLinkdaze’ssmart digital calendar comes in — a touchscreen tablet built specifically to organize a household rather than a single person. One of Linkdaze’s biggest strengths is its calendar compatibility. The system can synchronize calendars from popular services, including Google, iCloud, Outlook, Yahoo, and Cozi, which is a dedicated family-organizing app. This is particularly useful for families where different members use different platforms. Instead of asking everyone to switch to a single calendar app, Linkdaze brings multiple schedules together and uses color coding to make individual family members easy to identify. Launched last December, Linkdaze is available in 15.6-inch and 10.1-inch models, giving you some flexibility depending on how much wall space you have. Beyond calendars and appointments, you can use it for chores and rewards, meal planning, shopping lists, and other family organization. It can even double as a digital photo frame for displaying family photos. The most interesting feature, however, is Linkdaze’s AI meal planner with “Snap-to-Sync.” Instead of manually entering everything into a meal-planning app, you can take a photo of a paper recipe or your kid’s school lunch menu. Linkdaze will turn that information into a digital meal plan and generate a shopping list from it. While not an entirely new idea, it’s a useful feature that helps Linkdaze stand out from a basic digital calendar. Another big plus is that Linkdaze doesn’t require a monthly subscription for its main features. It’s an interesting choice in a category where recurring revenue has become the default. Skylight, a competing smart-calendar brand, offers additional features through its $79 per year subscription. For a hardware company entering a crowded smart-display market, that decision is either going to differentiate its product or look like a lost revenue stream. Linkdaze is also less expensive up front, with the 10.1-inch model priced at $119.99 compared with Skylight’s 10-inch model starting at $149.99 (if you pay for the subscription.) Overall, this device could make a practical gift for busy parents who are trying to keep everyone’s schedules in one place. It could also be a great fit for college apartments, where roommates can use it to coordinate chores, study schedules, shared meals, and other household responsibilities. It’s also very helpful for those of us juggling interviews, deadlines, meetings, and story assignments. This post was first published on August 20, 2026.
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Who’s behind the new ‘stealth model’ Ox Alpha?
A mysterious new AI model called Ox Alpha has driven certain corners of the internet into a frenzy of speculation about who actually built it. The free model wasreleased on OpenRouteron Thursday, where it was described as “a reasoning model designed for coding, sustained agentic work, and production workload.” On X, Stripe CEO Patrick Collison (whose companyis acquiring OpenRouter)described Ox Alphaas “very impressive.” So who’s actually behind Ox Alpha? The OpenRouter listing described it as a “stealth model” and said it was “developed and operated by a third-party provider who has chosen to remain anonymous during this preview.” Unsurprisingly, much of the speculation has revolved around China. AI analyst Andrew Curranposted on Fridaythat the initial speculation focused on the GLM models developed by Chinese companyZ.ai, but “this morning people seem less sure of anything.” Similarly,an article on Wccftechfirst suggested that the evidence pointed to GLM, but an update suggested that Ox Alpha could be an unreleased version of Microsoft’s MAI. And on Reddit, there’s at leastone postdeclaring that Ox Alpha “can’t be the Chinese,” whileanother expressed “high confidence”that it is, in fact, Chinese.
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Is it legal to train AI models on copyrighted books? It’s complicated
You probably know by now that the AI models powering ChatGPT, Gemini, Claude, and other chatbots are trained on seemingly infinite databases of published works, containing hundreds of millions of books, online articles, academic papers, and basically anything you can find on the internet. Most published authors have, without their knowledge or consent, contributed to the development of the same AI tools that threaten to undermine their livelihoods. That seems illegal, right? The reality isn’t that simple. “I think one of the issues with this entire area of law and this entire area of technology is there’s a lot going on,” Cathy Gellis, an attorney with expertise in intellectual property, copyright, and technology, told TechCrunch. “It’s very complex and there are a lot of raw feelings about what is happening, both for and against.” Last year, in one of the first rulings of its kind, Judge William Alsup ordered Anthropic to pay a mammoth$1.5 billion copyright settlementto a group of writers whose works were used to train the company’s AI models. At face value, this seemed like a moral victory favoring authors, but Judge Alsup actually ruled that Anthropic’s AI training was lawful. What Alsup penalized Anthropic for was pirating these books from illegal online shadow libraries. “Like any reader aspiring to be a writer, Anthropic’s LLMs trained upon works not to race ahead and replicate or supplant them — but to turn a hard corner and create something different,” the judge wrote, comparing the way an LLM ingests trillions of words to a writer’s study of literature. Gellis thinks the ruling is more advantageous for AI companies. What’s a $1.5 billion fine to a company projecting about$200 billionin annual revenue by 2028? “I think it is generally good news for AI training that he looked at what was going on and really sort of thought it analogous to reading a copyrighted work as opposed to copying a copyrighted work,” Gellis said. “Copyright law hinges on copying, but it doesn’t hinge on using the work or experiencing the work, consuming the work, reading the work.” Copyright lawhasn’t been updatedsince 1976, which means that judges have to figure out how to interpret guidelines from 50 years ago when confronting legal questions that have the potential to shape the future of the AI industry. “Everybody is very worried right now because the law is all over the place, and it’s because of this question,” Jason Henderson, Senior Attorney and Founder of the IP & Media Practice at JWL International, told TechCrunch. “They know that the AI model has been trained on so much stuff, and the law has not really caught up to that question.” These questions often hinge on fair use law — namely, whether use of a copyrighted work is “transformative” enough to be considered legally permissible. Fair use is a carve out of copyright law that allows for the use of copyrighted materials without explicit permission, protecting the ability to comment and iterate on copyrighted works through criticism, parody, education, and other means. Judges consider specific factors when deciding if something is fair use, including the purpose and nature of the work, the amount used, and its impact on the market. “Copyright is always about protecting and growing the market,” Henderson noted. “The courts are kind of all over the place in their reasoning [in AI cases]. What’s tending to win is if what you’re doing is you’re training on somebody’s property because your purpose is to directly compete, then the courts will frown on it… If what you’re doing is not going to compete, then the courts are tending to find ways that it will be okay.” Henderson is referencing a case in which the media and technology company Thomson Reuters sued the research firm Ross Intelligence for copying its content in order to build a competing, AI-based legal platform. “Ross’s use is not transformative because it does not have a ‘further purpose or different character’ than Thomson Reuters’s,” Judge Stephanos Bibaswrotelast year. In that case, Judge Bibas decided that it was not fair use to train on Reuters’ content to make a new platform that would directly compete with it. While authors could potentially argue that chatbots are competing with them by using their works to generate new, synthetic books, that argument has not yet prevailed in court. When it comes to the relationship between AI and copyright, Gellis finds it helpful to narrow down what we’re actually talking about – the way we think about copyright in terms of AI training is quite different from how we think about copyrighting AI-generated content. In one case,Thaler v. Perlmutter,the court ruled that if a work is 100% AI-generated, it’s not copyrightable, which opens a whole new can of worms – how can we definitively prove whether or not a work was generated using AI, and if so, how do we know what percentage of it was created or assisted with AI? “If you write your novel in [Microsoft] Word and run spell check, we kind of feel comfortable with the idea of saying that Word does not own your novel,” Gellis said. “[AI] is forcing us to look at a whole bunch of decisions that we kind of ignored for a while.” Most AI companies are still lodged in pending litigation over these issues, which means that we won’t have a definitive solution to these problems any time soon. “What you are seeing is that the initial opening volleys are being influential, and that influence itself could be undone if other courts decide different things, and it’ll take later states of litigation to figure out which one will prevail,” Gellis said. “But in the meantime, all these decisions are shaping everything that’s happening. It would be kind of foolish for the AI companies to ignore them.”
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