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This isn’t a generic IP dispute. Apple’s hardware chief at OpenAI is Tang Tan. Former Apple VP. 24 years at the company. He now runs OpenAI’s device ambitions. Apple alleges he was coaching Apple employees interviewing at OpenAI to bring actual hardware parts – batteries, logic boards, SIPs – to their interviews for “show and tell” sessions. He also reportedly circulated an internal Apple offboarding document marked “Need to Know” to incoming OpenAI hires, teaching them how to leave Apple without triggering security checks. Then there’s Chang Liu. Former Apple electrical engineer. He kept his Apple-issued laptop after joining OpenAI. Found a bug that still gave him access to Apple’s cloud storage. His reaction: “LOL, I found out I can access the [network storage], so funny.” He then ...

Whenever a new model gets released, I see alot of posts that this model now performs 80% in this benchmark and 90% on that benchmark. Now what does that mean and what if an AI model achieves 100% on all the benchmarks? Does that mean AI model cannot get any better now? submitted by /u/pokaboom1 [link] [comments]

The BABEL codec: the first complete, certified decode of everything happening inside a production language model (GPT-2 small). It reads the model's internal state into English AND writes English back into the model. 94.7% of behavior reconstructed — and that holds at every layer depth and text regime tested, not just one spot. Everything is open: paper, the full lexicon, the grammar tables, the decoder/encoder weights, reproduction scripts, and a demo that shows you the model's thoughts on any sentence you type. https://github.com/wpferrell/babel-codec-gpt2 submitted by /u/Revolutionary-Lab882 [link] [comments]

Asked Gemini a basic World Cup stat question (how many times has Spain finished top 4). Instead of an answer, it dumped its entire scratchpad: internal card-rendering logic with real component names (Bento/BentoCard/chameleon), a checklist it runs to decide what UI to render, and entity IDs it pulls from Google's Knowledge Graph. Just hadn't seen this specific schema documented anywhere. Raw output here: https://pastebin.com/8HWikGWj Curious if anyone's seen the "Bento" naming before or knows more about how this rendering pipeline works. submitted by /u/Pablomorado [link] [comments]

submitted by /u/iSyN707 [link] [comments]

Meta recently launched a new AI agent for businesses that’s designed to handle customer chats, book appointments, and close sales. Mark Zuckerberg even dropped a pretty wild prediction during the launch stating that eventually these agents will be able to "run your entire business." On one hand, you have to appreciate how far the infra has come. The fact that a platform as massive as Meta is rolling out native autonomous tools proves that AI agents are no longer just an experimental toy for tech hobbyists. They are genuinely capable of saving massive amounts of time on frontline customer service and scheduling. But there’s a massive elephant in the room that we need to talk about: data ownership. Handing over your entire operational data pipeline, your customer interactions, and your...

The main conclusions from analysis were: The Pareto frontier for coding tasks (i.e. best quality for a given cost) includes models from OpenAI, Anthropic, and open source. This means today, only a mix of tools can provide frontier performance. Open models, and GLM 5.2 in particular, are now able to handle even the highest level of task difficulty. The token price of a model is a poor indicator of actual costs incurred on end-to-end tasks. Larger models can be far more token efficient and have lower overall costs. The harness a model is called from dramatically impacts cost and quality. In many cases, simple harnesses like Pi performed best on our workloads. submitted by /u/petburiraja [link] [comments]

submitted by /u/Odd-Onion-6776 [link] [comments]

How does this line make you feel? Does it resonate, or does it already feel outdated in the AI era? I'd love your honest first impression. submitted by /u/Radiant_Horse4536 [link] [comments]