And by the way most of the content was produced by amazing CIFAR students and postdocts like @ilyasut @karpathy @goodfellow_ian @sedielem @notmisha @jaschasd
, Ben Marlin, @ziyuwang
, and many more exceptional researchers that went on to build the AI of Tesla, DeepMind, OpenAI,
@nandodf
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CIFAR Students and Postdocs Built AI at Tesla DeepMind OpenAI
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Quantum Computing Hopfield Networks Energy Based Models Foundations
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And if you want a vintage lecture describing some of these ideas, their connection to physics, computation, quantum computers, Hopfield networks, maximum likelihood, stochastic optimization, score matching, energy based models etc etc please see old lectures:
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Veritasium Video Praised for Clear Explanation of Complex Concepts
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This was so good. My 12 year old daughter and I thoroughly enjoyed spending time together watching this video and debating some of the points. You did such a brilliant job at explaining very complex ideas with beautifully clear animations. Thank you for this gift @veritasium
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Microsoft AI Hiring Data Engineers for Multimodal Datasets
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If you’re a good data engineer, or an engineer who loves looking at data creating datasets for games, video, images, audio, text … please send me a message here or on LinkedIn. We still have plenty of data jobs at @MicrosoftAI – but hurry 😅 https://t.co/F5vrE3EbiJ
— Nando de Freitas (@NandoDF) 13 mai 2025If you’re a good data engineer, or an engineer who loves looking at data creating datasets for games, video, images, audio, text … please send me a message here or on LinkedIn. We still have plenty of data jobs at @MicrosoftAI – but hurry
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Diffusion Policies and Multimodal Image-Based Action Representations
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It would be the same math/algorithms. The paper I shared uses a diffusion policy. Images are actions. Eg if you generate a spectrogram image, you can decode it immediately to speech. Speech acts can do a lot! We tend to imagine 1D embeddings for all modalities, but 2D
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Policy Gradient for Diffusion Model Fine-tuning
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It turns out we can easily apply the material we’ve covered to get the policy gradient for fine tuning a diffusion model, see eg https://
arxiv.org/pdf/2305.13301 It becomes a multi step RL problem with the reward only happening at the end. It’s not very efficient I think, but I’d love to -
Elite Research Institution Welcomes Ambitious AI Scientists
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Could not agree more. This is indeed the one of the best places in the world for advancing ambitious scientific research with large scale models. Apply.
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Ethical Responsibility of AI Privilege Access Disparities
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And speaking of un necessarily strong comments, I’m sorry to put you on the spot Jonas. In truth, the issue is broader and requires addressing. We are the privileged both financially and in terms of access to AI. With that there should be a moral onus on all of us to help the
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AI Competition Arrogance: Focus on Helping Underprivileged Communities
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Why don’t you compete with ChatGPT? Last time I checked Gemini app was an order of magnitude behind. More seriously, this arrogance and comparative disparaging is toxic and not needed in our community. Do the best work you can to help those with less privilege. That’s it.
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Reconnecting on Distributional Reinforcement Learning Research
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Thanks for adding, Marc. I miss our walks along the canal discussing distributional RL