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AI companies race to use ‘distillation’ to produce cheaper models.[1] DeepSeek claims ‘theoretical’ profit margins of 545%.[2] Microsoft’s new Phi-4 AI models pack big performance in small packages.[3] Stanford Researchers Uncover Prompt Caching Risks in AI APIs: Revealing Security Flaws

Have you ever stopped to think about how AI is already becoming indispensable in society—not through some big, dramatic takeover, but because humans are unknowingly building it into the system? Instead of a loud “AI rebellion,” imagine a scenario where

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Considering that there are AIs that are very good at recognizing patterns in speech, images and video, I have no doubt that there are also AIs that can recognize music in a similar fashion. Basically: Current Technology: I attach an

https://reddit.com/link/1j12vc6/video/5qrwwq0tq3me1/player Last few weeks where a bit crazy with all the new gen of models, this makes it a bit easier to compare the models against. I was particularly surprised at how bad R1 performed to my liking, and a

Ive heard a lot of people say that LLMs can’t reason outsude their training data both in and outside of this sub, which is completely untrue. Here’s my proof for why I believe that: MIT study shows language models defy

submitted by /u/Fabulous_Bluebird931 [link] [comments]

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