Siddharth Sharma
@siddrrsh
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CS @ Stanford. Building @mlfoundry. Prev @AWS, @Lux_Capital, @UniofOxford
Joined July 2020
Introducing ambientGPT: an open-source and multimodal MacOS foundation model GUI. Run GPT-4o and open-source models with full ambient knowledge of your screen. Foundation models have long been confined to the browser. With ambientGPT, your screen context is directly inferred as
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Re Llama3V: Firstly, we want to apologize to the original authors of MiniCPM. @AkshGarg03 and I posted Llama3V with @mustafaaljadery. Mustafa wrote the code for the project. Aksh and I were both excited about multimodal models and liked the architectural extensions on top of.
Shocked! Llama3-V project from a Stanford team plagiarized a lot from MiniCPM-Llama3-V 2.5!.its code is a reformatting of MiniCPM-Llama3-V 2.5, and the model's behavior is highly similar to a noised version of MiniCPM-Llama3-V 2.5 checkpoint. Evidence:
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RT @SakanaAILabs: Sakana AI is proud to sponsor the LLM Merging Competition: Building LLMs Efficiently through Merging at #NeurIPS2024 🤗. I….
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Great comeback from Sinner. The French crowd can’t stop this guy 💪.
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Will be an awesome event!.
Updates w.r.t. the upcoming Compound AI Systems Workshop (June 13th in San Francisco):. Accepted Posters. We are excited to announce the accepted posters for the Compound AI Systems workshop. Due to space constraints, we were only able to accept 28 featured posters. Sincere.
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When he's in the zone, Carlos Alcaraz is the best player in the world. The defense-to-offense and style of attacking tennis is just brutal.
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Congrats Omar!.
I'm excited to share that I will be joining MIT EECS as an assistant professor in Fall 2025!. I'll be recruiting PhD students from the December 2024 application pool. Indicate interest if you'd like to work with me on NLP, IR, or ML Systems! Stay tuned for more about my new lab.
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ML research is the most "empirical" science to ever exist. we test things and when they work or look promising, we double click . so a lot of major results are child nodes of a tree of trial and error.
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We’d like to thank the folks at Meta for their work in ensuring open-source is here to stay. We also wanted to shout out the authors of LLaVA-UHD as our methods are directly inspired by their intuition when it comes to image splitting and prepending the latents to the text.
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RT @MajmudarAdam: I've spent the past ~3 weeks going through the entire history of deep learning and reimplementing all the core breakthrou….
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RT @AnthropicAI: This week, we showed how altering internal "features" in our AI, Claude, could change its behavior. We found a feature th….
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Choosing the right problem is the hardest part usually.
If you like solving problems, the good news is that you'll never run out. Either you fail to solve a problem, and need to keep trying, or you succeed, in which case you've created new problems that need solving.
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Great to see a community developing around this! @ollama, @GroqInc, and @vllm_project integrations on the way 🫡.
Introducing ambientGPT: an open-source and multimodal MacOS foundation model GUI. Run GPT-4o and open-source models with full ambient knowledge of your screen. Foundation models have long been confined to the browser. With ambientGPT, your screen context is directly inferred as
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ambientGPT is open-source and we plan to integrate vllm and ollama to provide more extensive inference hosting abilities with our multimodal GUI. We also aim to release ambientGPT on the apple app store soon.
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Unlike OpenAI’s desktop app where you must provide a screenshot or upload a file, the context from your screen is automatically parsed. We also provide the ability to run secure local models like Gemma and Phi-3 multimodal from our interface. Due to the local model sizes, at
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I love GPU pods.
1/ @SohamGovande, @jameszhou02, @jzhou891 and I spent the weekend building PodPlex: A platform for distributed training & serverless inference at scale. I'm very glad to say that we left $10,000 GPU credits richer and 36 hours of sleep poorer. more details in 🧵
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Excellent writing on decentralized/distributed training. Exciting times ahead!.
1/ As promised, here's my thesis on the future of decentralized training of foundation models. Covers:. 1) why decentralized makes sense from scaling, margins, and marketplace lenses.2) challenges .3) exciting enabling research shifts. In long form at:
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