- What's brewing in AI
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- 🧙🏼 Google's new AI learning tool
🧙🏼 Google's new AI learning tool
Also: No LLM scores over 2% on this benchmark
Howdy, wizards.
Here’s what’s brewing in AI today.
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Google has launched a new AI tool for the purpose of, you guessed it, learn about anything. Supposedly, the answers it gives are more pedagogical and grounded in educational research.
From what I’ve seen – the responses are more visual and interactive than what you’re used to with ChatGPT-style chatbots, akin to a school textbooks (think coloured boxes of info like glossary, common misconceptions, etc.).
Why it matters Finding the optimal user interface for AI is a work in progress at all the major labs. Learn About resembles, imo, what Perplexity has recently been doing for things like Finance, Sports and election-related queries. What seems to be happening here is that Google is experimenting to find the optimal user interface for AI to deal with educational queries in an isolated environment, before potentially integrating them into their broader suite of tools.
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A non-profit AI advocacy group in the US (ARI) has launched a petition asking Trump to make Musk his special adviser on AI, aiming for 10,000 signatures.
The petition claims no one is more fit for the role to protect US lead on the technology and ensuring safety – with Musk’s focus on safety highlighted through his experience of both co-founding and later being a leading critic of OpenAI, as well as calling for a moratorium on AI development early on.
Critics argue the Musk – being the founder of xAI, a company currently eyeing a $40 billion valuation – might rather be motivated by his own interests. The petition addresses this point claiming it’s possible to deal with this conflict of interest through “proper mechanisms”.
Why it matters Having tech industry input is probably crucial for a useful AI policy, but having billionaires like Musk (with a vested interest) lead regulation efforts creates inherent conflicts of interest.
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EpochAI has released FrontierMath, a new math benchmark created in collaboration with over 60 mathematicians, where even the best of LLMs don’t score above 2%. The goal is to have a better scale for evaluating large language models on advanced mathematical reasoning; it includes the type of problems that would take expert mathematicians several hours to solve.
Why it matters Current LLM benchmarks are becoming saturated, with the new frontier models reaching their limits – which is why we need better benchmarks in order to tell how much progress is being made.
THAT’S ALL FOLKS!
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