Amazon CEO Andy Jassy says the company may eventually sell its Trainium AI chips directly to outside customers, not just through AWS, which would put Amazon in more direct competition with Nvidia. "There's so much demand for our chips that it's quite possible we'll sell racks of them to third parties in the future," Jassy wrote in his annual shareholder letter Thursday. He also revealed the company's chip business is already running at more than $20 billion annually, with demand so strong that current and even future generations are largely spoken for. Quartz reports: Access to Amazon's chips is currently limited to Amazon Web Services, with customers paying for cloud-based usage rather than owning any physical hardware. Selling to AWS and external customers alike, as standalone chipmakers do, would put annual revenue at around $50 billion, up from the $20 billion the company estimates for the year, Jassy said. The $20 billion figure spans three product lines: Trainium, the AI accelerator chip; Graviton, a general-purpose processor; and Nitro, a chip that helps run Amazon's EC2 server instances. All three are growing at triple-digit rates year over year, Jassy claimed in his letter. Jassy said demand for Trainium has outpaced supply at each generation. Trainium2 is essentially unavailable, with its entire allocated capacity spoken for. Trainium3 started reaching customers in early 2026, and reservations have filled nearly all available supply. Even Trainium4 -- which is not expected to reach wide release for another year and a half -- has substantial pre-orders committed. Jassy argued that a full-scale Trainium rollout could shave tens of billions off annual capital costs while meaningfully widening profit margin.

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An anonymous reader quotes a report from the Guardian: [Five skilled workers aged 50 and older spoke] to the Guardian about how, after struggling to find work in their fields, they have turned to an emerging and growing category of work: using their expertise to train artificial intelligence models. Known as data annotation, the work involves labeling and evaluating the information used to train AI models like Open AI's ChatGPT or Google's Gemini. A doctor, for example, might review how an AI model answers medical questions to flag incorrect or unsafe responses and suggest better ones, helping the system learn how to generate more accurate and reliable responses. The ultimate goal of training is to level up AI models until they're capable of doing a job as well as a human could -- meaning they could someday replace some of these human workers. The companies behind AI training, such as Mercor, GlobalLogic, TEKsystems, micro1 and Alignerr, operate large contractor networks staffed by people like Ciriello. Their clients include tech giants like OpenAI, Google and Meta, academic researchers and industries including healthcare and finance. For experienced professionals, AI training contracts can be a side hustle -- or a temporary fallback following a layoff -- where top experts can, in some cases, earn over $180 an hour. But that's on the high end. For some older workers [...], it represents another thing entirely: a last refuge in a brutal job market that is harder to stay in, or re-enter, the older they get. For many of them, whether or not they're training their AI replacements in their professions is besides the point. They need the work now. [...] "There's just a lot of desperation out there," Johnson said. As opportunities narrow, many turn to what Joanna Lahey, a professor at Texas A&M University who studies age discrimination and labor outcomes, calls "bridge jobs" -- lower-paying, less demanding roles that help workers stay financially afloat as they approach retirement. Historically, that meant taking temp assignments, retail and fast-food work and gig roles like Uber and food delivery. Now, for skilled workers -- engineers, lawyers, nurses or designers, for example -- using their expertise for AI data training is becoming the new bridge job. "[AI] training work may be better in some ways than those earlier alternatives," Lahey told the Guardian. AI training can offer flexibility, quick income and intellectual engagement. But it's often a clear step down. Professionals in fields such as software development, medicine or finance typically earn six-figure salaries that come with benefits and paid leave, according to the US Bureau of Labor Statistics. According to online job postings, AI training gigs start at $20 an hour, with pay increasing to between $30 and $40 an hour. In some cases, AI trainers with coveted subject matter expertise can earn over $100 an hour. AI training is contract-based, though, meaning the pay and hours are unstable, and it often doesn't come with benefits.

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Après des mois à recruter dans toute la Silicon Valley pour former le Superintelligence Labs, Meta vient de dévoiler Muse Spark, un premier modèle propriétaire présenté comme supérieur à Claude Opus 4.6 et Google Gemini 3.1 Pro dans plusieurs tests. Mais l'entreprise a-t-elle encore une chance dans la course à l'IA générative ?