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Tanishq Mathew Abraham, PhD
@iScienceLuvr
PhD at 19 | Founder and CEO at | Part-time at | Notebooks GM | Biomed. engineer @ 14 | TEDx talk➡bit.ly/3tpAuan
Science & Technologytanishq.aiJoined December 2011

Tanishq Mathew Abraham, PhD’s Tweets

This is currently the most important network in deep learning! From helping to power search for billions of users to better understanding proteins, it does it all! Here are 10 of the best resources to help you learn about the attention mechanism & Transformer network
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Are you wondering how large language models like ChatGPT and InstructGPT actually work? One of the secret ingredients is RLHF - Reinforcement Learning from Human Feedback. Let's dive into how RLHF works in 8 tweets!
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Research in AI is surprisingly more accessible to people with different backgrounds compared to other fields. Anyone (w/ relevant experience) can contribute to impactful research. Here are 5 research orgs you can join to contribute to real, open research in deep learning ↓
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The Tesla team discussed how they are using AI to crack Full Self Driving (FSD) at their Tesla AI Day event. They introduced many cool things: - HydraNets - Dojo Processing Units - Tesla bots - So much more... Here's a quick summary 🧵:
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After you train a machine learning model, the BEST way to showcase it to the world is to make a demo for others to try your model! Here is a quick thread🧵on two of the easiest ways to make a demo for your machine learning model:
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What matters most when training a neural network is how well it generalizes to unseen data. For neural networks, it turns out there's a simple principle that can allow you to understand model generalization. (1/18) A thread ↓
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Claude, 's powerful ChatGPT alternative, was trained with "Constitutional AI". Constitutional AI is particularly interesting since it uses less human feedback than other methods, making it more scalable. Let's dive into how Constitutional AI works in 13 tweets!
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So, I've heard people say anyone could have built ChatGPT. I think this is disingenuous. ChaGPT isn't just GPT-3 w/ a chat interface on top of it. The closest base model on the OpenAI API is probably text-davinci-003, but it was only released a day before ChatGPT! (1/9)
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Happy to finally announce that I'm one of the first recipients of the PhD fellowship!🥳👨‍🎓 Remainder of my PhD is funded with this fellowship. It's been great to be part of Stability AI as a PhD fellow for the past 4 months. Glad to be supported by this amazing org!
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I saw that recently followed me on Twitter! It's amazing that one of my deep learning idols from whom I have learned a lot (especially from the RNN, NN training recipe blog posts) is interested in the content I post here! Thanks for the follow, Andrej!
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Happy to share the fast.ai Part 2 course is now released! Wow what a long and fun journey it's been! I think this is one of the most cutting-edge courses about deep learning and specifically about diffusion models! (1/6)
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Our new course, "From Deep Learning Foundations to Stable Diffusion", is finally done after 8 months of work!!! With >30 hours of video content (all free, no ads!), you'll learn how to create and train a Stable Diffusion model starting from pure Python 🧵 fast.ai/posts/part2-20
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How does GPT-4 do in the medical domain? I got to play around with its multimodal capabilities on some medical images! Plus a recent Microsoft paper examined its text understanding and got SOTA results on USMLE medical exams! A quick thread ↓
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Given that this ML competition recently started, I thought it would be a good opportunity to share my approach to Kaggle competing A quick thread (1/7) 👇
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Calling all data scientists and artificial intelligence/machine learning researchers! Check out a new #AI research competition through @kaggle using the USPTO’s Open Data Portal. Enter the “U.S. Patent Phrase to Phrase Matching” competition here: bit.ly/3tuEMPI
The USPTO headquarters building behind a domed sculpture made of interconnected triangles
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A quick thread on my 2021 wins and 2022 goals ↓ My 2021 wins: • Became a 2x Kaggle Master • Passed my Ph.D. qualifying exam • Open-source contributions (fastai, DALL-E mini, etc.) • Started blogging • Submitted my 1st first-author paper • Reached >20k followers on Twitter
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June was a very busy month full of milestones from my PhD graduation to my 20th birthday few weeks ago! Can't believe two decades has passed so quickly🎂🎉🥳 Just within the past decade I graduated high school, graduated community college, obtained my bachelor's degree at UC… Show more
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Mixture of expert denoisers might be the next major trick/advancement for diffusion models. Both Baidu's ERNIE-ViLG 2.0 and NVIDIA's eDiffi do this. The idea is to have different models specialized for different noise levels:
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Had implemented RLHF for diffusion models 2 weeks back, replicating the DDPO paper. Here's a before/after comparison training with aesthetics reward. This is actually the 1st RL algorithm I've coded from scratch! Code linked in next tweet. Explanatory blog post coming soon!
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Applying deep learning to pathology is quite challenging due to the sheer size of the slide images (gigapixels!). A common approach is to divide images into smaller patches, for which deep learning features can be extracted & aggregated to provide a slide-level diagnosis (1/9)
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Beginners often get confused about why ReLU actually works as a good activation func. that can be used in a neural network to universally approximate any function. The animation by is quite good at providing a visual intuition behind this. (1/3)
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I am excited to share what I have been working on for the last several months in collaboration with Stability AI! Check out my new venture, ! Please support and share! ↓↓↓
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Announcing the launch of the MedARC! MedARC is a novel, open, & collaborative approach to medical AI research. It was created to develop large-scale AI models for medicine & build interdisciplinary teams to address clinical needs. (1/10) medarc.ai/blog/announcem
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App-integrated LLMs can be jailbreaked: showed how prompt injections can be incorporated in webpages or other content that may be retrieved by LLM systems to result in nefarious behavior. Here, text is embedded in a webpage to direct BingChat to perform a scam.
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In 2021, we saw many ML/AI models that tackle seemingly impossible problems: • Photorealistic text-to-image generation → DALL-E & GLIDE • Protein structure prediction → AlphaFold2 • Programming w/ natural language → Codex I wonder what problems ML/AI will tackle in 2022👀
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Have 2 surprises for my 20k milestone! First: A BOOK GIVEAWAY🎁 I'm autographing and giving 3 special color editions of 's book "Approaching Almost Any Machine Learning Problem" (which I helped review) To enter: like, RT this tweet & follow me by Jan 14th 10am PST
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It's kinda wild that two of the components of currently popular image generation AIs were actually invented for medical AI: 1. U-net - originally developed for cell segmentation 2. CLIP - a scaled-up version of ConVIRT, which was for learning medical visual representations
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Happy 20th Mother's Day to ! My mom quit her own PhD to raise me, 20 years later my gift this Mother's Day is finishing my PhD! 😉 Thankful for two decades of love, support, encouragement, & guidance. Without it, I wouldn't be here. My mom is truly a super-mom! ♥️
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I think there is some confusion in the #AiArt community about Stable Diffusion weights. Some folks think non-EMA is for inference, while EMA is for fine-tuning. Use EMA weights for generation! You can use non-EMA for fine-tuning but probably fine to use EMA for fine-tuning too
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1. DreamFusion by Text-to-3D generation starting from a pretrained text-to-image diffusion model and not needing any 3D training data:
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Happy to announce DreamFusion, our new method for Text-to-3D! dreamfusion3d.github.io We optimize a NeRF from scratch using a pretrained text-to-image diffusion model. No 3D data needed! Joint work w/ the incredible team of @BenMildenhall @ajayj_ @jon_barron #dreamfusion
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I thought maybe I could use it for getting LaTeX code but it's not that great. I was really hoping to be able to use it as a tool to get LaTeX of random equations. It may be good enough for starting out though.
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