Itch.io adding Generative AI disclosure filtering to few more places on the site
Itch.io is expanding its filters for games and other content disclosed as using generative AI. The filters will appear in more places across the site. (bsky.app)
On the Cheeky Pint podcast, OpenAI CEO Sam Altman argued that it is wasteful for individuals to keep large amounts of DRAM in personal computers when the memory is used only occasionally. With memory supply constrained, he said, computing resources would be allocated more efficiently if they were concentrated in cloud data centers, where utilization could be higher. He challenged the assumption that open-source AI models running locally would reduce demand for centralized computing, suggesting instead that widespread local inference ties up scarce memory.
The criticism is that this efficiency argument also serves OpenAI’s commercial interests. The company depends on centralized, closed-source services, and shifting computing from personal devices to its data centers could make people more reliant on paid cloud AI for everyday tasks. The piece links that model to OpenAI’s reported plan to spend $750 billion on infrastructure through 2030, arguing that data-center demand is helping drive up prices for DRAM and other components, including those used in phones. It contrasts the promise of convenient, universally available cloud computing with the costs of concentration: consumers may pay more for hardware now, then increasingly pay providers to perform tasks they could otherwise handle locally. Its central concern is that Altman presents resource centralization as a global efficiency measure, while the arrangement would also expand OpenAI’s control and revenue.
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Itch.io is expanding its filters for games and other content disclosed as using generative AI. The filters will appear in more places across the site. (bsky.app)
Sam Altman argues that people should use less RAM so memory can be redirected to AI data centers. Critics say OpenAI’s efforts to secure a large share of global RAM supplies could also drive up prices and question whether efficiency justifies restricting personal use. (techdirt.com)
LLMs often give outdated or incorrect product prices, even when they use web search. The tutorial shows how to build a Python agent that grounds answers in live data and lets code insert verified prices. (blog.apify.com)
Revolut moved about 2,000 engineers to self-hosted GLM coding models, running them on 56 Nvidia B200 GPUs at roughly $0.30 per million tokens. AI operations lead David Abitbol says engineering lead time improved 70% as lower costs let teams use AI more broadly, while Claude Code and Codex became exceptions. (twitter.com)
A 1995 Pentium Pro running a modern Stockfish port is estimated to play at 3300 Elo, far above Kasparov’s peak rating. The experiment shows how advances in chess algorithms could have beaten Kasparov without Deep Blue’s custom supercomputer hardware. (nicholas.carlini.com)
Gartner says open-weight models can handle about 90% of routine enterprise agent tasks at a fraction of the cost of closed models, while frontier models remain useful for complex reasoning. It expects companies to rely more on specialized open models, making the software harnesses that route tasks between models a key source of value. (theregister.com)
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