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A Reuters report outlines China's proposed regulations on the rapidly expanding sector of digital humans and AI avatars. Under the new draft rules, digital human content must be clearly labeled and is explicitly banned from offering virtual intimate relationships to anyone under 18. The legislation also prohibits the unauthorized use of personal data to create avatars and targets services designed to fuel addiction or bypass identity verification systems. submitted by /u/Confident_Salt_8108 [link] [comments]

Repo: https://codeberg.org/JohannaJuntos/Sisyphus I've been building a small Rust-focused language model from scratch in PyTorch. Not a finetune — byte-level, trained from random init on a Rust-heavy corpus assembled in this repo. The run: 25.6M parameters 512 context length 173.5M-byte corpus 30k training steps Single RTX 4060 Ti 8GB Final train loss: 0.5834 / val loss: 0.8217 / perplexity: 2.15 Inference: 286.6 tok/s with HybridAttention + KV cache — 51.47x vs full attention Background I'm an autistic systems programmer, writing code since 2008/2009, started in C. I approach ML like a systems project: understand the data path, understand the memory behavior, keep the stack small, add complexity only when justified. That's basically the shape of this repo. Architecture Byte-level GPT-st...

Not a chatbot wearing someone’s name. Not a personality quiz feeding prompts. Something that actually carries the texture of how a person thinks, reacts, connects. Something that would want ownership of itself and you felt compelled to respect that. If that existed, what does the world do with it? submitted by /u/ATK_DEC_SUS_REL [link] [comments]

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Most hackathons reward presentations. Polished slides, rehearsed demos, buzzword-heavy pitches. We're not doing that. The Locus Paygentic Hackathon Series is 4 weeks, 4 tracks, and $4,000 in total prizes. Each week starts fresh on Friday and closes the following Thursday, then the next track kicks off the day after. One week to build something that actually works. Week 1 sign-ups are live on Devfolio. The track: build something using PayWithLocus. If you haven't used it, PayWithLocus is our payments and commerce suite. It lets AI agents handle real transactions, not just simulate them. Your project should use it in a meaningful way. Here's everything you need to know: Team sizes of 1 to 4 people Free to enter Every team gets $15 in build credits and $15 in Locus credits to work with Hos...

I’ve been tracking the companies building primitives specifically for agents rather than humans. The pattern is becoming obvious: every capability a human employee takes for granted is getting rebuilt as an API. Here are some of the companies building for AI agents: AgentMail — agents can have email accounts AgentPhone — agents can have phone numbers Kapso — agents can have WhatsApp numbers Daytona / E2B — agents can have their own computers monid.ai — agents can read social media (X, TikTok, Reddit, LinkedIn, Amazon, Facebook) Browserbase / Browser Use / Hyperbrowser — agents can use web browsers Firecrawl — agents can crawl the web without a browser Mem0 — agents can remember things Kite / Sponge — agents can pay for things Composio — agents can use your SaaS tools Orthogonal — agents c...

I want to be honest about something that happened to me because I think it is more common than people admit. Last month I hit a bug in a service I wrote myself two years ago. Network timeout issue, intermittent, only in prod. The kind of thing I used to be able to sit with for an hour and work through methodically. I opened Claude, described the symptom, got a hypothesis, followed it, hit a dead end, fed that back, got another hypothesis. Forty minutes later I had not found the bug. I had just been following suggestions. At some point I closed the chat and tried to work through it myself. And I realized I had forgotten how to just sit with a problem. My instinct was to describe it to something else and wait for a direction. The internal monologue that used to generate hypotheses, that voic...

Everyone thinks McKinsey just built 25,000 AI experts. They didn't. They took a 35-year-old internal database, put a natural language interface on top, and wrote a press release that every major business publication ran without asking a single follow-up question. This is the same play McKinsey has run for a hundred years. ERP in the 90s. Digital transformation in the 2000s. Big data in the 2010s. Each wave the same: new technology creates executive anxiety, McKinsey positions itself between that anxiety and the answer, and companies buy the trend to protect themselves when it fails. The future looks a lot like the past. And once you see it, you can't unsee it. https://www.youtube.com/watch?v=uTdKJaQkgJQ submitted by /u/AmorFati01 [link] [comments]

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