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🔥Breaking News from Arena Google's Bard has just made a stunning leap, surpassing GPT-4 to the SECOND SPOT on the leaderboard! Big congrats to Google for the remarkable achievement! The race is heating up like never before! Super excited to see what's next for Bard + Gemini

In December, we launched Gemini 1.0 Pro. Today, we're introducing Gemini 1.5 Pro! 🚀  This next-gen model uses a Mixture-of-Experts (MoE) approach for more efficient training & higher-quality responses. Gemini 1.5 Pro, our mid-sized model, will soon come standard with a

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

Gemini 1.5 has arrived. Pro 1.5 with 1M tokens available as an experimental feature via AI Studio and Vertex AI in private preview. Then there’s this: In our research, we tested Gemini 1.5 on up to 2M tokens for audio, 2.8M tokens for video, and 🤯10M 🤯 tokens for text. From

Multineedle in haystack test We also created a generalized version of the needle in a haystack test, where the model must retrieve 100 different needles hidden in the context window. For this, we see that Gemini 1.5 Pro’s performance is above that of GPT-4 Turbo at small

I was leading long context in Gemini for a while now, and today I’m proud to share what the team has achieved: over 1M context in a large-scale foundation model. Big shoutout to Denis Teplyashin and Machel Reid - without you this would not have happened! youtube.com/watch?v=wa0MT8…

So excited to see Gemini 1.5 released to the world! It was a blast working with such an amazing team.

Short interview on the making of long context in Gemini 1.5 Pro: blog.google/technology/ai/…

Google's Gemini 1.5 Pro watches and critiques a video made by OpenAI SORA.

Been testing Gemini 1.5 pro and i'm really impressed so far Recall has been outstanding, and its really good at following instructions even with > 200k tokens. oh and agents just got a lot better. the only missing piece is really latency + cost

Gemini 1.5 Pro launched last week and already we're seeing the community produce some amazing interactions with long context. Below 👇 are some highlights and cool posts from folks who have gotten early access. A few thoughts from discussions / reactions from the community so

Gemini 1.5 pro is STILL under hyped I uploaded an entire codebase directly from github, AND all of the issues (Vercel ai sdk,) Not only was it able to understand the entire codebase, it identified the most urgent issue, and IMPLEMENTED a fix. This changes everything

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…

Utilizing Gemini 1.5 Pro with an entire codebase and achieving 80% accuracy for a multi-file update on the first attempt is a striking demonstration of the model's long context capability.

I love seeing people uncovering new and exciting applications for extra long context. It feels like opening up a whole new dimension of possibilities and I can't wait to see what else unfolds!

We removed the waitlist for Gemini 1.5 Pro with 1M context, try it for free in the UI: aistudio.google.com

Our experimental version of Gemini 1.5 Pro in AI Studio debuted at #1 on the LMSys leaderboard. 1300 ELO, nice round number 🔥 With the Gemini team, we are focused on both improving our models by iterating and finessing our recipe (deep learning FTW!), and also on massive bets