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Ruibo Liu
@RuiboLiu
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RS @GoogleDeepMind. AI Research with Humans in Mind.
Joined October 2015
Very exiting opportunity! Apply now👇
My team at @GoogleDeepMind is hiring a Research Scientist/Engineer for automated AI research with hands-on experience & strong track record. LLM/AutoML/RL is a plus. Send CV: crazydonkey@google.com (yes, it's real :) ) Subject: "DeepMind Job Application". Let's build together!🚀
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my mum tried DeepSeek and told me she loved it because it could generate beautiful literature-level Chinese. she has zero idea about which model is leading those AGI/HLE benchmarks, but she knows what model can best serve her needs in an easily accessible and affordable way. maybe we should rethink what a good AI product should be like. I bet after several years, all the models will converge on those benchmarks. at the end of the day, every developer needs to answer "what special value can your model bring to users?" the majority of your users are people like my mum—they might choose gemini-2.0-thinking not because of its benchmark scores but because its explicit thoughts make her feel "wow, I'm talking to a human-like agent rather than a cold-blooded machine." AI probably has no moat, but personality has.
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Many years ago we watched movies in cinemas but now I spent more time watching short videos on TikTok created by everyone’s phone. Nowadays we rely on AI from big companies—what if everyone has their own “phone”? Coding will not be the blocker very soon. And then I think the app ecosystem will be very different.
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Very well said and I learned a lot as well. Kindness is even harder than smartness, sometimes.
This is the most gut-wrenching blog I've read, because it's so real and so close to heart. The author is no longer with us. I'm in tears. AI is not supposed to be 200B weights of stress and pain. It used to be a place of coffee-infused eureka moments, of exciting late-night arxiv safaris, of wicked smart ideas that put smile on our faces. But all the incoming capital and attention seem to be forcing everyone to race to the bottom. Jensen always tells us not to use phrases like "beat this, crush that". I absolutely love this perspective. We are here to lift up an entire ecosystem, not to send anyone to oblivion. I like to think of my work as expanding the pie. We need to bake the pie first, together, the bigger the better, before dividing it. It gives me comfort knowing that our team's works moved the needle for robotics, even just by a tiny bit. AI is not a zero sum game. In fact, it is perhaps the most positive-sum game that humanity ever plays. And we as a community should act this way. Take care of each other. Send love to "competitors" - because in the grand schemes of things, we are all coauthors of an accelerated future. I never had the privilege to know Felix irl, but I loved his research taste and set up Google Scholar alert for every one of his new papers. His works in agents and VLMs had a big influence on mine. He would've been a great friend. I want to get to know him, but I couldn't any more. RIP Felix. May the next world have no wars to fight.
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My biggest takeaway of 2024 is that several new scaling methods are starting to shine. For example, data scaling (crazy overtraining in Llama 3), test-time scaling (o1, o3), etc. Parameter scaling—training ever larger LMs—seems to have diminishing gains and low ROI. If you could make the big decisions, what type of scaling would you put more compute on in 2025? And happy new year everyone! Wish you the best of luck in the Year of the Snake 🐍!
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RT @iamandrewdai: Try our new #1 ranked Lmsys model: Gemini Flash Thinking! Thinking, Flash and Slow!
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🍓Try it out! 🍓
We’ve been *thinking* about how to improve model reasoning and explainability Introducing Gemini 2.0 Flash Thinking, an experimental model trained to think out loud, leading to stronger reasoning performance. Excited to get this first model into the hands of developers to try out!
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