Ben Lee

Google @DeepMind. Not an Australian rock star.

[Ben Lee @benlee]

This captures so many of my interests in one place.

[Louie Zong (on bluesky now) @everydaylouie]

THE FUNK GUITAR DOJO 🐕🎸

[Ben Lee @benlee]

@MikeIsaac hackers soundtrack

[Ben Lee @benlee]

if you walk without rhythm, you won't attract the worm

[SharkClipping @SharkClipping]

The American woodcock does this "dance" to locate worms hidden in the soil

[Ben Lee @benlee]

@coreauto 4. Poasting

[Ben Lee @benlee]

@andon_backlink Nightcall by Kavinsky, great pick.

[Ben Lee @benlee]

@DZhang50 @gallabytes @tszzl @zacharynado

[Ben Lee @benlee]

@MikeIsaac damn, pretty rude to call out that it's been 30 years, imho

[Ben Lee @benlee]

@benleemusic on tour always. One of my favorite t-shirts that I've lost!

[Ben Lee @benlee]

@alexolegimas Mm ppjo Mommy j9ni

[Ben Lee @benlee]

@eigenhector

[Jeff Dean @JeffDean]

Check out our experimental Gemini-powered AI Mode for your most difficult queries. Powered by our advanced Gemini reasoning capabilities and Google Search (what a great combo!). See 🧵 below for how to try it out!

[Ben Lee @benlee]

@harryh [derogatory] or [non-derogatory]

[マクドナルド @McDonaldsJapan]

運命に導かれた3つのバーガーが
マクドナルドに集結。

エヴァンゲリオンバーガー
1/6(月)発売

[Ben Lee @benlee]

@dsivakumar Could you DM me the query? Interested in these use-cases

[Ben Lee @benlee]

@_arohan_ I've greatly enjoyed working with you since 2016, good luck on your next adventure! 🫡

[Ben Lee @benlee]

I love teenage engineering as much as the next nerd, but who is this for? https://t.co/5x42dnUQgd

[Ben Lee @benlee]

@_arohan_ Shogun on FX

[Ben Lee @benlee]

@_arohan_ @eigenhector Dreams are messages from the deep

[Ben Lee @benlee]

@partlyhuman Damn that is a spicy meatball. Makes the used OM-84 seem like a bargain

[Ben Lee @benlee]

@partlyhuman ermahgerd

[Ben Lee @benlee]

Excited that this is shared! I've been extremely fortunate to work on this with an amazing team.

[Jeff Dean @JeffDean]

I’m very excited to share our work on Gemini today! Gemini is a family of multimodal models that demonstrate really strong capabilities across the image, audio, video, and text domains. Our most-capable model, Gemini Ultra, advances the state of the art in 30 of 32 benchmarks, including 10 of 12 popular text and reasoning benchmarks, 9 of 9 image understanding benchmarks, 6 of 6 video understanding benchmarks, and 5 of 5 speech recognition and speech translation benchmarks. Gemini Ultra is the first model to achieve human-expert performance on MMLU across 57 subjects with a score above 90%. It also achieves a new state-of-the-art score of 62.4% on the new MMMU multimodal reasoning benchmark, outperforming the previous best model by more than 5 percentage points.

Gemini was built by an awesome team of people from @GoogleDeepMind, @GoogleResearch, and elsewhere at @Google, and is one of the largest science and engineering efforts we’ve ever undertaken. As one of the two overall technical leads of the Gemini effort, along with my colleague @OriolVinyalsML, I am incredibly proud of the whole team, and we’re so excited to be sharing our work with you today!

There’s quite a lot of different material about Gemini available, starting with:

Main blog post: https://t.co/NzSycJl7aE

60-page technical report authored by th Gemini Team: https://t.co/CEdMRyYSLo

In this thread, I’ll walk you through some of the highlights.