Oriol Vinyals @OriolVinyalsML
VP of Research & Deep Learning Lead, Google DeepMind. Gemini co-lead. Past: AlphaStar, AlphaFold, AlphaCode, WaveNet, seq2seq, distillation, TF. scholar.google.com/citations?user… London, England Joined October 2015-
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New @Google developer launch today: - Gemini 1.5 Pro is now available in 180+ countries via the Gemini API in public preview - Supports audio (speech) understanding capability, and a new File API to make it easy to handle files - New embedding model! developers.googleblog.com/2024/04/gemini…
We are rolling out Gemini 1.5 Pro API so that you can keep building amazing stuff on top of the model like we've seen in the past few weeks. Also, if you just want to play with Gemini 1.5, we removed the waitlist: aistudio.google.com Last, but not least, we pushed the model…
We are rolling out Gemini 1.5 Pro API so that you can keep building amazing stuff on top of the model like we've seen in the past few weeks. Also, if you just want to play with Gemini 1.5, we removed the waitlist: aistudio.google.com Last, but not least, we pushed the model… https://t.co/EQ8VtKFiom
A new Large Language Model a day keeps the GPUs away.
The future of fixing bugs? Just record them. I filmed 3 separate bugs in an app and gave the videos to Gemini 1.5 Pro with my entire codebase. It correctly identified & fixed each one. AI is improving insanely fast.
It certainly has been a fun year @Google: enjoy playing with our open source models Gemma, built from the same research and technology used to create the Gemini models. 💙♊️🚀 Blog: blog.google/technology/dev… Tech report: storage.googleapis.com/deepmind-media…
Amazing job from my friends @OpenAI on Sora! Also, sorry if I spoil this video for you, but I can't unsee the cats' 3 front legs 😆
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…
Soumith Chintala @soumithchintala
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35K Followers 429 Following Staff research scientist at DeepMind. AI and neuro. Former physicist, current human. https://t.co/jVR7w1pUOQNew @Google developer launch today: - Gemini 1.5 Pro is now available in 180+ countries via the Gemini API in public preview - Supports audio (speech) understanding capability, and a new File API to make it easy to handle files - New embedding model! developers.googleblog.com/2024/04/gemini…
We're starting to roll out API support for Gemini 1.5 Pro for developers. We're excited to see what you build with the 1M token context window! We'll be onboarding people to the API slowly at first, and then we'll ramp it up. In the meantime, developers can try out Gemini 1.5…
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…
Found more bugs for #Gemma: 1. Must add <bos> 2. There’s a typo for <end_of_turn>model 3. sqrt(3072)=55.4256 but bfloat16 is 55.5 4. Layernorm (w+1) must be in float32 5. Keras mixed_bfloat16 RoPE is wrong 6. RoPE is sensitive to y*(1/x) vs y/x 7. (Fixed) RoPE should be float32…
@OriolVinyalsML Llegint l'AIMA m'he trobat amb aquesta referència. No sabia que havies estat campió de Starcraft!! Segueixo la teva feina pel Twitter i m'ha fet gràcia, res més. És el meu joc favorit i un amic de la carrera va arribar a estar molt ben rankejat 😉
The future of fixing bugs? Just record them. I filmed 3 separate bugs in an app and gave the videos to Gemini 1.5 Pro with my entire codebase. It correctly identified & fixed each one. AI is improving insanely fast.
if your girlfriend isn’t using your product when you’re not around are you really building the future anon?
Twitter: * Googlers are phoning it in * Google is too big to ship * Google leadership has lost control of the steering wheel Dec. ‘23 — Gemini 1.0 release Feb. ‘24 — Gemini 1.5 release Feb. ‘24 — Gemma release Narrative violation.
Just as I began diving into Gemini 1.5, googlers nerd-swiped me with Gemma. 🤷♂️
Introducing Gemma - a family of lightweight, state-of-the-art open models for their class, built from the same research & technology used to create the Gemini models. Blog post: blog.google/technology/dev… Tech report: goo.gle/GemmaReport This thread explores some of the…
Gemini 1.5 Pro's 1,000,000+ token context length is incredible. I got early access and spent my Saturday night running tests. Here are 6 impressive capabilities I found:
@DimitrisPapail Neat test! I tried this image in AI Studio with Gemini Pro and it gave me this answer which I thought was pretty nice. I've been having fun trying tests on drawings like this, you can try at aistudio.google.com #Google #GeminiAI
Dijous es va anunciar Gemini 1.5! Molt content d'haver contribuït a fer-ho possible. El meu experiment preferit, "trobar l'agulla en el paller", consisteix en amagar una paraula secreta enmig de moltes dades i testejar si Gemini 1.5 la sap trobar. 🧵 x.com/oriolvinyalsml…
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…
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…
Gratitude It’s really great to get to work with such an awesome set of colleagues on a project like Gemini. @OriolVinyalsML and I just want to say a heartfelt thank you to everyone on the team for the hard work on Gemini so far, and I’m so proud of what we’ve built together! 🙏
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…
Have you ever done a dense grid search over neural network hyperparameters? Like a *really dense* grid search? It looks like this (!!). Blueish colors correspond to hyperparameters for which training converges, redish colors to hyperparameters for which training diverges.