Ty Chen @tychen_tw

x.com/i/article/2044…

First trial, zero shot, the story is actually pretty decent! Presenting "Cyber Horse" g.co/gemini/share/2…

Josh Woodward @joshwoodward

a year ago

Introducing Storybook in @GeminiApp today! Now you can create personalized, illustrated storybooks with read-aloud narration in 2 simple steps. It's free and available globally right now. Here's how to make yours + a famous story from our house about "Teddy" …

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Say hello to the @geminicli, a local CLI to help you build and maintain software with 1,000 free Gemini 2.5 Pro requests per day : )

I wrote a new blog on TPUs -- it's been fun seeing how different they are from GPUs and also drawing things on excalidraw again✏️ henryhmko.github.io/posts/tpu/tpu.…

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With gemini 2.5 pro pricing and results, Google has fixed the biggest unknown/weakest link in their lineup and we can now confirm that @GoogleDeepMind completely owns the pareto frontier down to 1220 elo (at least until o4-mini and gpt5?)

swyx @swyx

2 years ago

updated price-elo pareto frontier with deepseek v3/r1 and gemini 2 flash thinking 2 results notes: - o1-mini and o3-mini are going to have to DRASTICALLY cut prices (like, at least 25x) to keep up. it is not a surprise that o3-mini is going to be in free chatgpt much sooner

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🐍💥Python 3.13.0 has been released! 🎉 This is the first version with 🧵experimental GIL-free mode, an experimental JIT compiler🔧, a slick new REPL 🖌️ and many new cool features! And it's faster, smarter, and more colorful than ever! 🚀 Get it here: python.org/downloads/rele…

Blogpost link: yitay.net/blog/training-… Happy to hear feedback. I may get back to blogging more in general so ideas would also be welcome! 😄

For one day only, General Catalyst invited 20 of San Francisco’s top AI entrepreneurs to showcase what’s possible with AI. Live product and raw code only. No pitches. No bullshit. Here’s what we saw at the @cerebral_valley co-working demo session at @generalcatalyst (🧵):

Google Gemini Pro 1.5 : Transforming Contact Directories Data into JSON I gave Google Gemini Pro 1.5 with 1M context the telephone directory of the 'University of Agricultural Sciences, Bangalore,' which was 66 pages long, and asked it to return JSON data for multiple departments. Here’s how it performed: Accurate Data Parsing: Impressively, it parsed data and created JSON, handling details from multiple departments across random pages, each with multiple contact details, accurately. 100% Correct Responses: Upon testing, all responses were 100% correct, showcasing its exceptional ability to process and convert data reliably. (Note: you need to be clear with your prompts make it very clear what you exactly want) Intuitive Key Creation: It surprised me by automatically identifying and creating keys like designation and location, despite such details not being explicitly separated in the provided data. It's really amazing how it manages to parse data and create structured JSON, proving Google Gemini's capabilities in handling complex data conversions Prompt used : Could you provide me with the all contact details with all possible fields for the each of the department given below, returning the results in JSON format in one file? Cost of Cultivation Scheme, GKVK, Bengaluru Seed Technology Research, NSP, GKVK, Bengaluru Agricultural Research Station, Chintamani, Chikkaballapur Note: This data is open and freely available on the internet for anyone to use. More detais on 🧵 @JeffDean 1/3

Get ready for another fun leap day full of software glitches! As done in past years, I'm live-blogging them here. We've got one already! codeofmatt.com/list-of-2024-l…

Google presents Genie Generative Interactive Environments introduce Genie, the first generative interactive environment trained in an unsupervised manner from unlabelled Internet videos. The model can be prompted to generate an endless variety of action-controllable virtual worlds described through text, synthetic images, photographs, and even sketches. At 11B parameters, Genie can be considered a foundation world model. It is comprised of a spatiotemporal video tokenizer, an autoregressive dynamics model, and a simple and scalable latent action model. Genie enables users to act in the generated environments on a frame-by-frame basis despite training without any ground-truth action labels or other domain-specific requirements typically found in the world model literature. Further the resulting learned latent action space facilitates training agents to imitate behaviors from unseen videos, opening the path for training generalist agents of the future.

I tried feeding a 7s video of my bookshelf into Gemini Pro 1.5 to get back a JSON array of books... and it worked! simonwillison.net/2024/Feb/21/ge…

Gemini 1.5 Pro - A highly capable multimodal model with a 10M token context length Today we are releasing the first demonstrations of the capabilities of the Gemini 1.5 series, with the Gemini 1.5 Pro model. One of the key differentiators of this model is its incredibly long context capabilities, supporting millions of tokens of multimodal input. The multimodal capabilities of the model means you can interact in sophisticated ways with entire books, very long document collections, codebases of hundreds of thousands of lines across hundreds of files, full movies, entire podcast series, and more. Gemini 1.5 was built by an amazing team of people from @GoogleDeepMind, @GoogleResearch, and elsewhere at @Google. @OriolVinyals (my co-technical lead for the project) and I are incredibly proud of the whole team, and we’re so excited to be sharing this work and what long context and in-context learning can mean for you today! There’s lots of material about this, some of which are linked to below. Main blog post: blog.google/technology/ai/… Technical report: “Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context” goo.gle/GeminiV1-5 Videos of interactions with the model that highlight its long context abilities: Understanding the three.js codebase: youtube.com/watch?v=SSnsmq… Analyzing a 45 minute Buster Keaton movie: youtube.com/watch?v=wa0MT8… Apollo 11 transcript interaction: youtube.com/watch?v=LHKL_2… Starting today, we’re offering a limited preview of 1.5 Pro to developers and enterprise customers via AI Studio and Vertex AI. Read more about this on these blogs: Google for Developers blog: developers.googleblog.com/2024/02/gemini… Google Cloud blog: cloud.google.com/blog/products/… We’ll also introduce 1.5 Pro with a standard 128,000 token context window when the model is ready for a wider release. Coming soon, we plan to introduce pricing tiers that start at the standard 128,000 context window and scale up to 1 million tokens, as we improve the model. Early testers can try the 1 million token context window at no cost during the testing period. We’re excited to see what developer’s creativity unlocks with a very long context window. Let me walk you through the capabilities of the model and what I’m excited about!

@SantaClaraPower Elmhurst Ave is also impacted

shoulditestprivatemethods.com

🎉🎉 We just launched Tico on @ProductHunt eaelier today and start getting upvotes🤩🤩 Please check our page and leave your feedback if you have any 😃 producthunt.com/posts/tico

Presenting the "sleep sort", our favorite O(wtf) sorting algorithm. (C'mon, it's the weekend..) 😂

Aaaaand the Cowboys just ran back the opening kickoff...

Ring that 🔔!!! Touchdown @L_Bell26!!!

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