day 14 of 365 days of ai today was really stressful. school took most of my day and my supervisor kept me busy, so i explained more of today's video with motion visuals instead of my face. the stories still deserve your attention 🙏 an ai model scored 99.9% on a major benchmark, but there's a catch 0:00 intro
0:28 @OpenAI's gpt-6 astra scores 99.9% on arc-agi-3 with a special setup, but 62.7% on @arcprize's standard test 
1:11 @Replit reportedly moves most of its ai spending from @AnthropicAI to openai, after a reported 30%+ discount 
1:41 @GenReasoning finds ai agents can recognize a problem and still not report it
2:21 wrap up judging ai takes more than intelligence. look at how it's tested, what it costs and how it behaves. which of these stories caught your attention the most? 👀 
let me know in the comments.

institutions want to use public blockchains, but there’s one problem. they can’t make all their data public. think about a bank that wants to use blockchain. it needs to prove certain information is true without exposing customers’ private details. this is where @primus_labs comes in. → zkTLS helps prove that information from websites and APIs is authentic without revealing all the data behind it. → FHE allows data to be processed while it remains encrypted. in simple terms, one helps prove the information is genuine, while the other allows you to work with data without decrypting it first. the goal isn’t to hide everything. it’s to make information verifiable while keeping sensitive details private. that’s what makes privacy and public blockchains work together