Jakub Bober @JakubBoberML
AI Engineer, MEng Math&CS ICL graduate Joined October 2021-
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Building RAG is easy, but designing it is hard 💡 This article by @MichalOleszak in @TDataScience offers a comprehensive overview of the big and small design choices you need to build high-performing RAG systems, across 5 main pillars: 1️⃣ Indexing: Embedding external data into…
i loved my time at openai. it was transformative for me personally, and hopefully the world a little bit. most of all i loved working with such talented people. will have more to say about what’s next later. 🫡
It's only been 11 hours since OpenAI Dev Day Here are 12 of the craziest things people have already built already Including AI Sports narrator and website roaster. 🧵 Thread below
I had an amazing time at OpenAI's inaugural Dev Day yesterday and caught a glimpse of how their new products will push instruction, knowledge, and actions into the hands of more users and developers. Here’s a quick recap of what I saw at the event:
This work would not be possible without my collaborators @paaarsaaa, @Sotiris_No, Kyros Kutulakos and @DaveLindell. Find out more on: 🖥️anaghmalik.com/TransientNeRF 📃arxiv.org/abs/2307.09555 📹youtu.be/m1sc4-h7ma8
The key 🔑 takeaway message is that point clouds are a preprocessed and lossy representation; recovering the 3d representation that is consistent with the raw measurements (given the proper forward model) works much better!
By integrating the scans over time, we recover a conventional image similar to other NeRF methods such as DS-NeRF or Urban-NeRF. Our method allows recovering relatively high quality models of appearance and geometry!
To synthesize a novel lidar view we query a neural representation at points along a ray. The outputs are used alongside our rendering equation, which models lidar image formation, including the laser pulse shape and falloff effects. We supervise on histograms from lidar scans.
Delighted to share the first project of my PhD, "Transient Neural Radiance Fields for Lidar View Synthesis and 3D Reconstruction". We show unprecedented capabilities of synthesizing novel lidar scans from as few as 2 input views! 🖥️anaghmalik.com/TransientNeRF
Announcing ICLR 2023 outstanding paper award: blog.iclr.cc/2023/03/21/ann…. Congratulations to the authors!
10x engineer is a myth. 100x AI-powered engineer is more real than ever. As OpenAI winds down Codex, Microsoft announces GitHub Copilot X. I think it's almost as exciting as GPT-4 itself: - Copilot Chat: any piece of text database will be "chattable", and codebase is no…
whoa, this is bigger than ChatGPT to me. google almost solved music generation, i'd say. google-research.github.io/seanet/musiclm…
DetectGPT: Zero-Shot Machine-Generated Text Detection using Probability Curvature Detects samples from pre-trained LLMs using the local curvature of the model's log probability function. proj: ericmitchell.ai/detectgpt/ abs: arxiv.org/abs/2301.11305
After a hiatus, a new series of blogs posts. Do differential geometry and algebraic topology sound too exotic for ML? In recent works, we show that tools from these fields bring a new perspective on graph neural networks First post in the series: towardsdatascience.com/graph-neural-n…
Zain Khan, MD @ZainKhanMed
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Ivan Kapelyukh 🇺�... @IvanKapelyukh
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Zain Khan, MD @ZainKhanMed
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Beyond Group @BeyondGroupUK
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Arthur Allshire @arthurallshire
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Ivan Kapelyukh 🇺�... @IvanKapelyukh
322 Followers 579 Following PhD student at Imperial College London, working on robot learning and computer vision. Former intern at RAI (previously Boston Dynamics AI Institute). 🇬🇧 🇺🇦
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