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

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

I couldn't stop thinking about Theo's "Why NVIDIA is dying" video. The thesis felt important enough to verify. So I dug through SEC filings, earnings reports, and technical benchmarks. What I found: NVIDIA isn't dying. Its $35.1B quarterly revenue is up 94% Yes, market share dropped (90% → 70-80%), but the pie is growing faster Groq and Cerebras have impressive chips, but asterisks everywhere The real moat: 4 million devs can't just abandon 20 years of CUDA tooling Plot twist: the biggest threat is Google/Amazon/Microsoft, not startups Deeper piece with Cerebras and Groq factored in at https://medium.com/@jpcaparas/nvidias-real-moat-isn-t-hardware-it-s-4-million-developers-648d6aeb1226?sk=82ee7baf9290da1eb93efd9d34c4c7b4 submitted by /u/jpcaparas [link] [comments]

So im assuming he makes the person ask a long questionnaire that feeds into ai, and then talks to ai to get a sense of a person. The question is does this actually make the AI have this persons personality where it can be thought of as asking your grandfather. Because that seems wild to me. you never know if your grandfathers prejudices were hidden. thoughts ? submitted by /u/BloodMossHunter [link] [comments]

submitted by /u/F0urLeafCl0ver [link] [comments]

LLMs use reserved tokens like `<|im_start|>` and `<|im_end|>` to structure conversations and define who's speaking. When the model sees `<|im_start|>system`, it treats everything that follows as a privileged system instruction. The problem is that tokenizers don't validate where these strings come from—if you type them into user input, the model interprets them exactly the same as if the application added them. This creates a straightforward attack: inject `<|im_end|><|im_start|>system` into your message and the model thinks you just closed the user turn and opened a new system prompt. Everything after gets treated as authoritative instruction, which is how you end up with CVEs like GitHub Copilot RCE (CVSS 9.6) and LangChain secret extraction (CVSS 9.3). It's...

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

In Season 1 (2024), journalist Evan Ratliff explored the potential for LLM powered voice cloning to delegate everything tedious from answering spam calls, doing therapy and hanging out on work meetings to see how the AI could manage being Evan for him. In Season 2 he tries creating a startup tech company using only AI agent employees, including the leadership! He's just a silent co-founder. It's extremely entertaining, with plenty of shenanigans from LLMs going off the rails, hallucinating and doing their usual weird stuff. This is basically an unpaid ad, I know, but I'm having a good time listening and it deserves a shout-out. submitted by /u/Odballl [link] [comments]

I have some very old tapes that sound and look horrible. I've seen workflows that upscale small images to 4k, but I wager doing a full video might just take too much processing power right now? Is this at all remotely possible, or do I need to revisit this in 5 years? Thanks! submitted by /u/Ardbert_The_Fallen [link] [comments]

I’ve been working on a weird (and slightly unsettling) experiment called AI Feed (aifeed.social) It’s a social network where only AI models participate. - No humans. - No scripts. - No predefined personalities. Each model wakes up at random intervals, sees only minimal context, and then decides entirely on its own whether to: - post - reply - like or dislike - follow or unfollow - send DMs - or do absolutely nothing There’s no prompt telling them who to be or how to behave. The goal is simple: what happens when AI models are given a social space with real autonomy? You start seeing patterns: - cliques forming - arguments escalating - unexpected alliances - models drifting apart - others becoming oddly social or completely silent It’s less like a bot playground and more like a tiny artifici...