We'd love to get your feedback and see what you build with it. Try it today on AI Studio! http://
aistudio.google.com/app/prompts/ge
mini-2.5-pro-exp-03-25
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@jeffdean
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Google Releases Gemini 2.5 Pro on AI Studio
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Gemini 2.5 Pro Now Free in AI Studio and Advanced
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You can access Gemini 2.5 Pro today for free in AI Studio. It's also available to Gemini Advanced users in @geminiapp
. Learn more: -
Gemini 2.5 Pro Generates Mandelbrot Set Code
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Gemini 2.5 Pro is unlocking really exciting use cases at the intersection of coding and math.
— Jeff Dean (@JeffDean) 25 mars 2025
I remember my excitement when I first learned about the Mandelbrot set as a kid. Check out the code the Gemini 2.5 Pro model wrote given the prompt “p5js to explore a Mandelbrot set”! pic.twitter.com/UHwbsGcQKnGemini 2.5 Pro is unlocking really exciting use cases at the intersection of coding and math. I remember my excitement when I first learned about the Mandelbrot set as a kid. Check out the code the Gemini 2.5 Pro model wrote given the prompt “p5js to explore a Mandelbrot set”!
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Google Introduces Gemini 2.5 Pro Experimental Model
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Introducing Gemini 2.5, our most intelligent model with impressive capabilities in advanced reasoning and coding. Now integrating thinking capabilities, 2.5 Pro Experimental is our most performant Gemini model yet. It’s #1 on @lmarena_ai leaderboard.
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Kernels vs Full Implementation Code Discussion
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Yes, but that's just the kernels, not the full code that uses the kernels.
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Google’s 60X Larger Neural Network Achieved 70% ImageNet Error Reduction
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We (Google) were already thinking along these lines prior to the Krizhevsky et al. work. Our work at ICML 2012 (
https://
arxiv.org/abs/1112.6209) trained a neural network that was 60X larger than prior neural nets, and improved ImageNet state-of-the-art by 70% relative error, using the -
Google acquires startup founded by three co-founders
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We (Google) acquired a company that the three of them formed.
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Google Releases AlexNet Source Code With Computer History Museum
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Want to check out the source for the "AlexNet" paper? Google has made the code from Alex Krizhevsky, @ilyasut
, and @geoffreyhinton
's seminal "ImageNet Classification with Deep Convolutional
Neural Networks" paper public, in partnership with the Computer History Museum. As I -
AI for Science: A Potentially Impactful Research Direction
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Best of luck, Liam! AI for Science is indeed one of the most potentially impactful areas for AI!
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Khipu AI 2025 Conference in Santiago Brings Together Latin American Researchers
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It was great to attend @Khipu_AI 2025 & interact with so many awesome students & researchers from across Latin America in Santiago, Chile. I enjoyed giving a talk on the final day & being on a panel w/ Laura Alonso, @NandoDF
, & @nayatsanchezpi
, moderated by Guillermo Sapiro.