Russ Salakhutdinov @rsalakhu
UPMC Professor of Computer Science at Carnegie Mellon University, ex-Director of AI research at @Apple, co-founder Perceptual Machines (acquired by Apple) cs.cmu.edu/~rsalakhu/ Pittsburgh, PA Joined January 2015-
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[1/5] Introducing Stylus 🖌️ - an #AI tool that automatically finds and adds the best adapters (LoRAs, Textual Inversions, Hypernetworks) to #StableDiffusion based on your prompt. 🗞️ Paper: arxiv.org/abs/2404.18928 🌎 Project Page: stylus-diffusion.github.io
It’s here! Meet Llama 3, our latest generation of models that is setting a new standard for state-of-the art performance and efficiency for openly available LLMs. Key highlights • 8B and 70B parameter openly available pre-trained and fine-tuned models. • Trained on more…
Yes Paul (@pliang279), that bubbly is yours! 🥳🎉Congratulations on your very successful dissertation defense! (on the "Foundations of Multisensory Artificial Intelligence" in the @mldcmu ,@SCSatCMU, @CarnegieMellon ).
Honored to receive the 2024 Jane Street Graduate Research Fellowship! Thank you @JaneStreetGroup for the award and for organizing an amazing workshop! The best part of this was getting to meet PhD students working on algebraic geometry, cosmology, quantum algorithms, and more!
I’ll be sharing more on Llama 3 very soon. It’s so cool to see what the community is already building with Llama 2 though. One of my favorites: @team_qanda & @upstageai used it to build a math-specific LLM to make personalized learning more accessible! ai.meta.com/blog/llama-2-m…
NLPositionality: Characterizing Design Biases of Datasets and Models – Machine Learning Blog | ML@CMU | Carnegie Mellon University blog.ml.cmu.edu/2024/03/01/nlp…
Beyond the Mud: Datasets, Benchmarks, and Methods for Computer Vision in Off-Road Racing – Machine Learning Blog | ML@CMU | Carnegie Mellon University blog.ml.cmu.edu/2024/03/22/bey…
Very proud to be part of this Amazing MURI Team with Christos Papadimitriou @Columbia, Erik Demaine, @KonstDaskalakis, @aleks_madry @MIT, @zicokolter , @rsalakhu, Katia Sycara @CMU, Kamalika Chaudhuri @UCSD, and our own @FeiziSoheil @umdcs.
Very proud to be part of this Amazing MURI Team with Christos Papadimitriou @Columbia, Erik Demaine, @KonstDaskalakis, @aleks_madry @MIT, @zicokolter , @rsalakhu, Katia Sycara @CMU, Kamalika Chaudhuri @UCSD, and our own @FeiziSoheil @umdcs.
1/ Given high-dim time series data (e.g., video, text), we'd like to know "what happens in the future?" and "what happened between A and B?" Turns out temporal contrastive learning provably answers these questions! Paper+Code: arxiv.org/abs/2403.04082 Backstory and details below
You can do solid technical work or have long arguments about mumbo jumbo -- it is hard to do both. But one of them is much easier to do than the other.
You can do solid technical work or have long arguments about mumbo jumbo -- it is hard to do both. But one of them is much easier to do than the other.
Exciting personal update: I defended my PhD last week on Deep Learning on Graphs. Huge thanks to my committee Profs Tom Mitchell, @jure, and my advisors @rsalakhu and Christos Faloutsos. I have joined @inflectionAI to extend the benefits of intelligence to a wider audience!
Congratulations to my former CMU PhD student Zhilin Yang on his new LLM startup Moonshot AI, raising over $1B in VC funding. Zhilin has done some fundamental work in NLP and large language models during his time at CMU including TransformerXL and XLNet. techcrunch.com/2024/02/21/moo…
I could not agree more with @PhilBeaudoin's response to @ylecun post. Quoting Philippe via Facebook: "I find it fascinating that ML researchers talk about their intuition with such a high degree of confidence even after having been wrong so frequently in the past. I’m used to…
I could not agree more with @PhilBeaudoin's response to @ylecun post. Quoting Philippe via Facebook: "I find it fascinating that ML researchers talk about their intuition with such a high degree of confidence even after having been wrong so frequently in the past. I’m used to…
If only Sora were developed by Meta :)
Completely agree with Kevin: “It’s fine for creative tasks, but not (yet) autonomous agents” – the key word here is YET. We are still far from having fully autonomous & reliable agents, but here are some early examples (albeit brittle) of agents navigating the web and…
Completely agree with Kevin: “It’s fine for creative tasks, but not (yet) autonomous agents” – the key word here is YET. We are still far from having fully autonomous & reliable agents, but here are some early examples (albeit brittle) of agents navigating the web and…
Check out a few demos and code of the multimodal GPT-4V + SoM agent from our VisualWebArena that you can run on any web task. Code+Paper: jykoh.com/vwa
Check out a few demos and code of the multimodal GPT-4V + SoM agent from our VisualWebArena that you can run on any web task. Code+Paper: jykoh.com/vwa
We've added a demo of the multimodal GPT-4V + SoM agent from VisualWebArena to our GitHub repo, and you can now run this agent on any web task you like! Here is the agent helping us to find a good Thai restaurant in Pittsburgh (more examples in the 🧵):
@ylecun It doesn't count as a new invite, if the slide deck doesn't change. <zing/>
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43K Followers 378 Following Professor of #computerscience @Stanford; Co-founder at https://t.co/hhm1j5wP0f #machinelearning #graphs.I'll be talking about VisualWebArena tomorrow at 12pm ET (about 14 hours from now). I'm looking forward to discussing multimodal agents!
Be sure to check out our Geo-Regional Asia Group next week on Tuesday, March 12th as they host @kohjingyu for a presentation on "VisualWebArena: Evaluating Multimodal Agents on Realistic Visual Web Tasks" Learn more: cohere.com/events/c4ai-Ji…
With amazing collaborators @vivek_myers @rsalakhu and @svlevine!
1/ Given high-dim time series data (e.g., video, text), we'd like to know "what happens in the future?" and "what happened between A and B?" Turns out temporal contrastive learning provably answers these questions! Paper+Code: arxiv.org/abs/2403.04082 Backstory and details below
Exciting personal update: I defended my PhD last week on Deep Learning on Graphs. Huge thanks to my committee Profs Tom Mitchell, @jure, and my advisors @rsalakhu and Christos Faloutsos. I have joined @inflectionAI to extend the benefits of intelligence to a wider audience!
Proud to announce: Mistral Large - 81.2% MMLU - outperforms Claude 2, Gemini 1.0 Pro, GPT-3.5 - multilingual with seq_len = 32K - json mode and function calling Also excited to launch Le Chat (Try it now at chat.mistral.ai) 🔗 mistral.ai/news/mistral-l…
Today, we are releasing Mistral Large, our latest model. Mistral Large is vastly superior to Mistral Medium, handles 32k tokens of context, and is natively fluent in English, French, Spanish, German, and Italian. We have also updated Mistral Small on our API to a model that is…
@ylecun @rsalakhu @PhilBeaudoin I think this means we kinda agree, right? There were (almost) no datasets to showcase the benefit, hence almost no empirical evidence for the benefit.
You know what's my favourite part with our Gemma release? That we do not misuse the term "open source" like other labs have. It was explicit in the comms briefing that we should call them "open models" and not "open source models". Much respect to the team.
One reason LLMs have progressed so rapidly is that we had (and still have) an information theory overhang. There's lots of deep structure that can, in principle, be learned by compressing existing data. One just needs to free up bottlenecks like engineering effort and compute.
Congrats @gingsmith , @justinesherry , Aaditya Ramdas and Nathan Beckmann!! cs.cmu.edu/news/2024/sloa…
Here's what I see as a likely AGI trajectory over the next decade. I claim that later parts of the path present the biggest alignment risks/challenges. The alignment world has been focusing a lot on the lower left corner lately, which I'm worried is somewhat of a Maginot line.
@willdepue Cool to see @rsalakhu’s pioneering work cited!
Zuck on the Apple Vision Pro He's still got fire in him, love to see it
@ylecun It doesn't count as a new invite, if the slide deck doesn't change. <zing/>
@rsalakhu @geoffreyhinton 1. What’s Geoff’s take on technical AI safety/alignment research? What would his version of a research program to approach that entail? 2. Given the impressive careers his students had, what’s his mentoring style and what should students look for in an academic supervisor?
@kohjingyu @dan_fried @rsalakhu @gneubig @shuyanzhxyc @rclo8103 Congrats on the nice work. I look forward to evaluate SeeAct on it.
How do we better design classifiers that know when they don't know? There are two different kinds of uncertainty measures in the literature -- aleatoric, or due to inherent noise in the data from overlapping classes, and epistemic, or uncertainty due to atypical inputs.
Extremely proud of Mistral-Medium and Mixtral 8x7B performance on the @lmsysorg Leaderboard! You can try both the models at console.mistral.ai