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aicoffeebreak.bsky.social

@aicoffeebreak.bsky.social
187 followers 18 following 67 posts

📺 ML Youtuber youtube.com/AICoffeeBreak 👩‍🎓 PhD student in Computational Linguistics @ Heidelberg University | Impressum: t1p.de/q93um

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aicoffeebreak.bsky.social @aicoffeebreak.bsky.social · 27/09/2026
New AI Coffee Break video! ☕️🔥 LLMs can hallucinate and give the correct answer for the wrong reason. What about teaching them to admit “I don’t know”? 📺 youtu.be/796GVFTFiB0
youtu.be
Reducing Hallucinations: Merlin-Arthur Training and Evaluation EXPLAINED
YouTube video by AI Coffee Break with Letitia
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Heidelberg Laureate Forum @hlforum.bsky.social · 22/07/2026
💡Today, we speak with HLF alumna Letiția Pârcălăbescu @aicoffeebreak.bsky.social who will be joining us at the 13th HLF as a panelist! 🖥️🎓 During her PhD in computer science, Letitia developed tools to help multimodal LLMs complete tasks more "honestly". 👉 scilogs.spektrum.de/hlf/?p=14524
scilogs.spektrum.de
Keeping AI Honest - Heidelberg Laureate Forum - SciLogs - Wissenschaftsblogs
We speak to computer scientist Letiția Pârcălăbescu on her research to help train more transparent and "honest" AI models.
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Women in AI Research - WiAIR @wiair.bsky.social · 18/02/2026
🧠 Do Vision & Language Decoders Use Images and Text Equally? In our latest episode, we speak with Letitia Parcalabescu about her ICLR 2025 paper examining how vision–language *decoder* models use images and text — and how self-consistent their explanations really are. (1/8🧵)
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Women in AI Research - WiAIR @wiair.bsky.social · 06/02/2026
If you love @aicoffeebreak.bsky.social, this one's for you — Letitia Parcalabescu is our next guest on the #WiAIR_podcast! Stay tuned for our conversation: 🎬 YouTube: www.youtube.com/@WomeninAIRe...
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aicoffeebreak.bsky.social @aicoffeebreak.bsky.social · 02/11/2025
LLMs can memorize even a phone number seen once in training.🔒 Google’s VaultGemma fixes that, being the first open-weight LLM trained from scratch with differential privacy, so rare secrets leave no trace. ☕ new video explaining Differential Privacy through VaultGemma 👇 🎥 youtu.be/UwX5zzjwb_g
youtu.be
What's up with Google's new VaultGemma model? – Differential Privacy explained
YouTube video by AI Coffee Break with Letitia
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aicoffeebreak.bsky.social @aicoffeebreak.bsky.social · 19/10/2025
We explain diffusion models and flow-matching models side by side. Flow-Matching models are the new generation of AI image generators that are quickly replacing diffusion models. They take everything diffusion did well, but make it faster, smoother, and deterministic. 🎥 youtu.be/firXjwZ_6KI
youtu.be
Diffusion Models and Flow-Matching explained side by side
YouTube video by AI Coffee Break with Letitia
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aicoffeebreak.bsky.social @aicoffeebreak.bsky.social · 21/09/2025
Ever wondered how Energy-Based Models (EBMs) work and how they differ from normal neural networks? ☕️ We go over EBMs and then dive into the Energy-Based Transformers paper to make LLMs that refine guesses, self-verify, and could adapt compute to problem difficulty.
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aicoffeebreak.bsky.social @aicoffeebreak.bsky.social · 14/09/2025
The world’s largest NLP conference with almost 2,000 papers presented, ACL 2025 just took place in Vienna! 🎓✨ Here is a quick snapshot of the event via a short interview with one of the authors whose work caught my attention. 🎥 Watch: youtu.be/GBISWggsQOA
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aicoffeebreak.bsky.social @aicoffeebreak.bsky.social · 05/08/2025
My friend Vivi Nastase is working on a short science communication film called "Puppets of a Digital Brain". It aims to explain the tech behind AI chatbots (the good, the bad, the environmental) in an accessible, visual way. 💡 GoFundMe: gofund.me/453ed662
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aicoffeebreak.bsky.social @aicoffeebreak.bsky.social · 03/08/2025
How do LLMs pick the next word? They don’t choose words directly: they only output word probabilities. 📊 Greedy decoding, top-k, top-p, min-p are methods that turn these probabilities into actual text.
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aicoffeebreak.bsky.social @aicoffeebreak.bsky.social · 27/07/2025
Excited to be at ACL 2025 in Vienna this week 🇦🇹 #ACL2025 I’m always up for a chat about reasoning models, NLE faithfulness, synthetic data generation, or the joys and challenges of explaining AI on YouTube. If you're around, let’s connect!
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aicoffeebreak.bsky.social @aicoffeebreak.bsky.social · 07/07/2025
🤖 Can we trust AI in science? I'm excited to be speaking at the final event of the Young Marsilius Fellows 2025, themed "Dancing with Right & Wrong?" – a title that feels increasingly relevant these days. I'll be joining a panel on "(How) can we trust AI in science?" to discuss questions like:
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aicoffeebreak.bsky.social @aicoffeebreak.bsky.social · 20/06/2025
We train AI on human-selected or -generated data (yes, even taking a photo is concept selection – we capture what we find interesting; text even more so, expressing our conceptualisation of the world). Then we’re surprised when the AI's concepts and representations are similar to ours. 🤷‍♀️
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Nils Trost @trostnils.bsky.social · 20/06/2025
I'm very excited to finally share the main work of my PhD! We explored the evolutionary dynamics of gene regulation and expression during gonad development in primates. We cover among others: X chromosome dynamics (incl. in a developing XXY testis), gene regulatory networks and cell type evolution.
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aicoffeebreak.bsky.social @aicoffeebreak.bsky.social · 19/06/2025
💡 AlphaEvolve is a new AI system that doesn’t just write code, it evolves it. It uses LLMs and evolutionary search to make scientific discoveries. We explain how AlphaEvolve works and the evolutionary strategies behind it (like MAP-Elites and island-based population methods). 📺 youtu.be/Z4uF6cVly8o
youtu.be
AlphaEvolve: Using LLMs to solve Scientific and Engineering Challenges | AlphaEvolve explained
YouTube video by AI Coffee Break with Letitia
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aicoffeebreak.bsky.social @aicoffeebreak.bsky.social · 31/05/2025
Excited to share that I’ll be joining the Summer School “AI and Human Values” this September at the Marsilius-Kolleg of Heidelberg University as a speaker. I'll be giving an introduction to how large language models actually work—before the summer school dives deeper into broader implications.
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aicoffeebreak.bsky.social @aicoffeebreak.bsky.social · 18/05/2025
Long videos are a nightmare for language models—too many tokens, slow inference. ☠️ We explain STORM ⛈️, a new architecture that improves long video LLMs using Mamba layers and token compression. Reaches better accuracy than GPT-4o on benchmarks and up to 8× more efficiency. 📺 youtu.be/uMk3VN4S8TQ
youtu.be
Token-Efficient Long Video Understanding for Multimodal LLMs | Paper explained
YouTube video by AI Coffee Break with Letitia
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Evangelos Kazakos @ekazakos.bsky.social · 17/05/2025
Follow @aicoffeebreak.bsky.social!! Letitia is very effective in communicating research papers in just a few mins! Perfect for your coffee break. 😉
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aicoffeebreak.bsky.social @aicoffeebreak.bsky.social · 18/04/2025
We all know quantization works at inference time, but researchers successfully trained a 13B LLaMA 2 model using FP4 precision (only 16 values per weight!). 🤯 We break down how it works. If quantization and mixed-precision training sounds mysterious, this’ll clear it up. 📺 youtu.be/Ue3AK4mCYYg
youtu.be
4-Bit Training for Billion-Parameter LLMs? Yes, Really.
YouTube video by AI Coffee Break with Letitia
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aicoffeebreak.bsky.social @aicoffeebreak.bsky.social · 23/03/2025
Just say “Wait…” – and your LLM gets smarter?! We explain how just 1,000 training examples + a tiny trick at inference time = o1-preview level reasoning. No RL, no massive data needed. 🎥 Watch now → youtu.be/XuH2QTAC5yI
youtu.be
s1: Simple test-time scaling: Just “wait…” + 1,000 training examples? | PAPER EXPLAINED
YouTube video by AI Coffee Break with Letitia
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aicoffeebreak.bsky.social @aicoffeebreak.bsky.social · 01/02/2025
🎙️ Yesterday, I gave a keynote on large language models outfitted with visual understanding, and the faithfulness of their chain-of-thought reasoning at the National Conference on Governing the Digital Society and Human-Centered AI.
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Robert A. Bagheri @ayoubbagheri.nl · 01/02/2025
The National Conference on AI Transformations: Language, Technology, and Society organised by Utrecht University @utrechtuniversity.bsky.social was a success, and indeed Letiția‘s @aicoffeebreak.bsky.social talk was very inspiring.
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Heidelberg University NLP Group @hd-nlp.bsky.social · 27/01/2025
🎉 Exciting news from our team! The final paper of @aicoffeebreak.bsky.social's PhD journey is accepted at #ICLR2025! 🙌 🖼️📄 Check out her original post below for more details on Vision & Language Models (VLMs), their modality use and their self-consistency 🔥
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aicoffeebreak.bsky.social @aicoffeebreak.bsky.social · 26/01/2025
We explain 🥥COCONUT (Chain of Continuous Thought), a new paper using vectors for CoT instead of words. We break down: - Why CoT with words might not be optimal. - How to implement vectors for CoT instead words and make CoT faster. - What this means for interpretability. 📺 youtu.be/mhKC3Avqy2E
youtu.be
COCONUT: Training large language models to reason in a continuous latent space – Paper explained
YouTube video by AI Coffee Break with Letitia
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aicoffeebreak.bsky.social @aicoffeebreak.bsky.social · 22/01/2025
The last paper of my PhD is accepted at ICLR 2025! 🙌 🎊 We investigate the reliance of modern Vision & Language Models (VLMs) on image🖼️ vs. text📄 inputs when generating answers vs. explanations, revealing fascinating insights into their modality use and self-consistency. Takeaways: 👇
arxiv.org
Do Vision & Language Decoders use Images and Text equally? How Self-consistent are their Explanations?
Vision and language model (VLM) decoders are currently the best-performing architectures on multimodal tasks. Next to answers, they are able to produce natural language explanations, either in post-ho...
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aicoffeebreak.bsky.social @aicoffeebreak.bsky.social · 19/01/2025
An educational and a bit historical deep dive into LLM research. 💡Learn what breakthroughs since 2017 paved the way for AI like ChatGPT (it wasn't overnight). We go through: * Transformers * Prompting * Human Feedback, etc. and break it all down for you! 👇 📺 youtu.be/BprirYymXrg
youtu.be
LLMs Explained: A Deep Dive into Transformers, Prompts, and Human Feedback
YouTube video by AI Coffee Break with Letitia
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Franz Nowak @franznowak.bsky.social · 18/11/2024
Transformer language models like Chat GPT, when using chain-of-thought reasoning, are Turing complete. Specifically, they can execute probabilistic algorithms and generate any computable weighted language youtu.be/MMIJKKNxvec?...
youtu.be
Transformer LLMs are Turing Complete after all !?
YouTube video by AI Coffee Break with Letitia
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aicoffeebreak.bsky.social @aicoffeebreak.bsky.social · 09/01/2025
Don't forget to register! 🤭👇
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aicoffeebreak.bsky.social @aicoffeebreak.bsky.social · 08/12/2024
New video about: REPA (Representation Alignment), a clever trick to align diffusion transformers’ representations with pretrained transformers like DINOv2. It accelerates training and improves the diff. model’s ability to do things other than image generation (like image classification).
youtu.be
REPA Representation Alignment for Generation: Training Diffusion Transformers Is Easier Than You ...
YouTube video by AI Coffee Break with Letitia
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aicoffeebreak.bsky.social @aicoffeebreak.bsky.social · 03/11/2024
Why does math feel so intimidating? Prof. Yael Tauman Kalai shares her insights, and we look at what this says about how we view intelligence🧠, both human🧑and AI🤖. 📺 youtu.be/Su1puD4xQwI
youtu.be
Why do people fear math? – Prof. Yael Tauman Kalai 🔴at #HLF24
YouTube video by AI Coffee Break with Letitia
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aicoffeebreak.bsky.social @aicoffeebreak.bsky.social · 06/10/2024
How to make powerful LLMs understand graphs and their structure?🕸️ With Graph Language Models! They take a pre-trained LLM and fit it with the ability to process graphs. Watch if you're curious!👇 📺 youtu.be/JcHeaONGbmQ (Hint: it's about position embeddings, as the author explained at #ACL2024 🔴)
youtu.be
Graph Language Models EXPLAINED in 5 Minutes! [Author explanation 🔴 at ACL 2024]
YouTube video by AI Coffee Break with Letitia
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aicoffeebreak.bsky.social @aicoffeebreak.bsky.social · 13/09/2024
Here is what we think about the training procedure of OpenAI #o1. We speculate based on all the bread crumbs we could find, how exactly reinforcement learning (RL) helped train the model to “think” by producing private Chain-of-Thought tokens before answering. 👇 📺 youtu.be/MNE6QZaRavo
youtu.be
How OpenAI made o1 "think" – Here is what we think and already know about o1 reinforcement learning
YouTube video by AI Coffee Break with Letitia
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aicoffeebreak.bsky.social @aicoffeebreak.bsky.social · 10/09/2024
Can LLMs handle self-referential statements such as “This sentence has 5 words”? We recorded the #ACL2024 poster presentation of the paper „I am a Strange Dataset: Metalinguistic Tests for Language Models” by @TristanThrush @jaredlcm @migueljmonares @ChrisGPotts @douwekiela . 📺 youtu.be/m_nEIsQBh_c
youtu.be
I am a Strange Dataset: Metalinguistic Tests for Language Models – Paper Explained [🔴 at ACL 2024]
YouTube video by AI Coffee Break with Letitia
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aicoffeebreak.bsky.social @aicoffeebreak.bsky.social · 05/09/2024
Are transformer LLMs equivalent to Turing machines or not? Spoiler: they are, because @franz_nowak , @AnejSvete , @butoialexandra , and @RyanCotterell proved this in their latest paper! 📃 📺 youtu.be/MMIJKKNxvec We talk with Franz Nowak about RNNs, transformer encoders, decoders (with CoT).
youtu.be
Transformer LLMs are Turing Complete after all !?
YouTube video by AI Coffee Break with Letitia
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aicoffeebreak.bsky.social @aicoffeebreak.bsky.social · 02/09/2024
At the ACL, we recorded the poster presentation of the paper challenging Noam Chomsky's claim about LLMs! 🫢 📺 youtu.be/8lU6dGqR26s This paper, entitled “Mission: Impossible language models”, won an #ACL2024 best paper award. Congrats to the authors! 👏
youtu.be
Mission: Impossible language models – Paper Explained [ACL 2024 recording]
YouTube video by AI Coffee Break with Letitia
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aicoffeebreak.bsky.social @aicoffeebreak.bsky.social · 01/09/2024
Prefer reading over watching videos? 📚 Check out some of our videos in blog post format on Substack!👇 aicoffeebreakwl.substack.com We'll be adding more posts regularly, stay tuned! 📻
AI Coffee Break Substack announcement
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aicoffeebreak.bsky.social @aicoffeebreak.bsky.social · 20/08/2024
Text diffusion can finally generate good text!📃 We've combed through the dense math of the “Discrete Diffusion Modeling by Estimating the Ratios of the Data Distribution” paper to bring you the key insights and takeaways.👇 📺 youtu.be/K_9wQ6LZNpI The paper won the #ICML2024 best paper award.
youtu.be
Discrete Diffusion Modeling by Estimating the Ratios of the Data Distribution – Paper Explained
YouTube video by AI Coffee Break with Letitia
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aicoffeebreak.bsky.social @aicoffeebreak.bsky.social · 16/08/2024
I’ve made a video about my PhD journey! 👩‍🎓 I'm spilling all the (coffee) beans on why I chose a PhD ☕, the side quests along the way. I show my PhD hat 🎓and give an overview of my research. Plus, I'm giving tips to prospect PhD students and reasons why I started YouTube. 👇 📺 youtu.be/prGZTX-Sgqw
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My PhD Journey in AI / ML as a YouTuber
Here is my personal journey through my PhD experience! 👩‍🎓 In this special video, I’m spilling all the details—from why I chose to pursue a PhD to the extra duties I juggled, like teaching. I’ll also give you a peek at my PhD hat 🎓, share a quick overview of the research that shaped my thesis, and explain why I decided to start this YouTube channel during my PhD. 📺 Let’s dive in! 🚀 AI Coffee Break Merch! 🛍️ https://aicoffeebreak.creator-spring.com/ Thanks to our Patrons who support us in Tier 2, 3, 4: 🙏 Dres. Trost GbR, Siltax, Vignesh Valliappan, Michael, Sunny Dhiana, Andy Ma Outline: 00:00 Intro 01:24 Why do a PhD 03:30 Timeline of my PhD 05:32 Collaborations 06:33 Teaching 09:05 Thesis Writing 10:48 PhD Defense 12:20 PhD hat 14:35 Research Work 27:57 Challenges 31:46 Starting YouTube 34:52 Tips for PhD candidates 35:57 Reflections ▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀ 🔥 Optionally, pay us a coffee to help with our Coffee Bean production! ☕ Patreon: https://www.patreon.com/AICoffeeBreak Ko-fi: https://ko-fi.com/aicoffeebreak Join this channel to get access to perks: https://www.youtube.com/channel/UCobqgqE4i5Kf7wrxRxhToQA/join ▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀ 🔗 Links: AICoffeeBreakQuiz: https://www.youtube.com/c/AICoffeeBreak/community Twitter: https://twitter.com/AICoffeeBreak Reddit: https://www.reddit.com/r/AICoffeeBreak/ YouTube: https://www.youtube.com/AICoffeeBreak #AICoffeeBreak #MsCoffeeBean #MachineLearning #AI #research​ Video editing: Nils Trost Music 🎵 : Morning – Text Me Records
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aicoffeebreak.bsky.social @aicoffeebreak.bsky.social · 29/07/2024
This Thursday, I'll share my story about how I made over 100 YouTube videos explaining ML in your coffee break! ☕ Listen in by joining Roosh Circle 's No Papers Club. There will be lots of insights, inspiration, and practical advice. 🫱🫲 Join here: lnkd.in/e_wX2r_G ⌚ Aug 1 at 5:00 PM CEST!
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aicoffeebreak.bsky.social @aicoffeebreak.bsky.social · 26/07/2024
Excited to share my ACL 2024 presentation on my second-to-last PhD paper! 🎓📚 Watch it here if you are also interested in LLM self-explanations: 🤖 youtu.be/b3wbTOZXRyI Are you joining ACL 2024 in Bangkok? Ping me—let's chat! #ACL2024NLP #PhDLife
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[Own work] On Measuring Faithfulness or Self-consistency of Natural Language Explanations
Excited to share my ACL 2024 presentation on my almost-last PhD paper about LLM self-explanations! 🎓📚 Are you joining ACL 2024 in Bangkok? Ping me—let's c...
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aicoffeebreak.bsky.social @aicoffeebreak.bsky.social · 17/06/2024
Supercharge your RAG apps with Generative Feedback Loops! 🚀 - 📝 Feed data to your LLM - 💾 store outputs with vector embeddings, - 🔍 and search in real-time. In this video, we explain RAG, show demo code for generative feedback loops with Weaviate!👇 youtu.be/ijCjKnbQgXc
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Supercharging RAG with Generative Feedback Loops from Weaviate
How to supercharge RAG applications? With Generative Feedback Loops: feed data from a database to your LLM, store the outputs back into the database with a vector embedding! Then, search through the generated data in near real-time for future applications. In this video, we explain RAG, Generative Feedback Loops, give examples of applications that require them, and show you how to implement them with @Weaviate . Weaviate (Sponsor) 👉 https://weaviate.io/ AI Coffee Break Merch! 🛍️ https://aicoffeebreak.creator-spring.com/ Outline: 00:00 Generative Feedback Loops Motivation 01:32 RAG explained 03:21 Generative Feedback Loops 05:09 Concrete example with Weaviate code 08:30 DSPy: More Applications of Generative Feedback Loops 10:22 Conclusion, Weaviate Sponsor Thanks to our Patrons who support us in Tier 2, 3, 4: 🙏 Dres. Trost GbR, Siltax, Vignesh Valliappan, Michael, Sunny Dhiana, Andy Ma Resources: 📺 Vector Search and Vector Databases explained: https://youtu.be/YkK5IKgxp-c 📑 Generative Feedback Loops with LLMs for Vector Databases: https://weaviate.io/blog/generative-feedback-loops-with-llms 💻 Code used in the video: https://github.com/weaviate/recipes/blob/main/weaviate-features/generative-feedback-loops/generative-feedback-loops-airbnb.ipynb 📑 Hurricane: Writing Blog Posts with Generative Feedback Loops https://weaviate.io/blog/hurricane-generative-feedback-loops 🕊️ What DSPy can do: https://twitter.com/lateinteraction/status/1788241002035388917 DSPy paper: Khattab, Omar, Arnav Singhvi, Paridhi Maheshwari, Zhiyuan Zhang, Keshav Santhanam, Sri Vardhamanan, Saiful Haq et al. "Dspy: Compiling declarative language model calls into self-improving pipelines." arXiv preprint arXiv:2310.03714 (2023). https://arxiv.org/abs/2310.03714 📺 Weaviate Demo – Retrieval Augmented Generation • Vector Search • Generative Feedback Loops: https://www.youtube.com/watch?v=VAxrREiugxQ 📺 Generative Feedback Loops with Bob van Luijt - Weaviate Podcast #45! https://www.youtube.com/watch?v=1RALju6ZJz0 📺 Podcast summarization example (Connor): https://www.youtube.com/watch?v=I4Jle80AOaU 📚 Collection of papers and code snippets for running Generative Feedback Loops with Weaviate https://github.com/weaviate/Generative-Feedback-Loops ▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀ 🔥 Optionally, pay us a coffee to help with our Coffee Bean production! ☕ Patreon: https://www.patreon.com/AICoffeeBreak Ko-fi: https://ko-fi.com/aicoffeebreak Join this channel to get access to perks: https://www.youtube.com/channel/UCobqgqE4i5Kf7wrxRxhToQA/join ▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀ 🔗 Links: AICoffeeBreakQuiz: https://www.youtube.com/c/AICoffeeBreak/community Twitter: https://twitter.com/AICoffeeBreak Reddit: https://www.reddit.com/r/AICoffeeBreak/ YouTube: https://www.youtube.com/AICoffeeBreak #AICoffeeBreak #MsCoffeeBean #MachineLearning #AI #research​ Video editing: Nils Trost Music 🎵 : Cru – Yung Logos
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aicoffeebreak.bsky.social @aicoffeebreak.bsky.social · 27/05/2024
We explain GaLore, a new parameter-efficient training ⚙️ technique that outperforms LoRA in accuracy, and supports both pre-training and fine-tuning. You can even pre-train a LLaMA-7B from scratch on one 24GB GPU (NVIDIA RTX 4090), for example. 📺 youtu.be/VC9NbOir7q0
youtu.be
GaLore EXPLAINED: Memory-Efficient LLM Training by Gradient Low-Rank Projection
We explain GaLore, a new parameter-efficient training technique that outperforms LoRA in accuracy and supports both pre-training and fine-tuning. Now you can...
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aicoffeebreak.bsky.social @aicoffeebreak.bsky.social · 06/05/2024
Ever wondered how to interpret your #MachineLearning models? 🤔 We explain a powerful interpretability technique: Shapley Values – can be used to explain any model, including LLMs! 💻 We show simple code for how to use them and 📖 dive into the theory behind them. 📺 youtu.be/5-1lKFvV1i0
youtu.be
Shapley Values Explained | Interpretability for AI models, even LLMs!
Ever wondered how to interpret your machine learning models? 🤔 We explain a powerful interpretability technique for machine learning models: Shapley Values. They can be used to explain any model. 💻 We show a simple example code of how they work, and then 📖 explain the theory behind them. AssemblyAI (Sponsor) 👉 https://www.assemblyai.com/research/universal-1/?utm_source=youtube&utm_medium=social&utm_campaign=universal1_letitia AI Coffee Break Merch! 🛍️ https://aicoffeebreak.creator-spring.com/ Thanks to our Patrons who support us in Tier 2, 3, 4: 🙏 Dres. Trost GbR, Siltax, Vignesh Valliappan, Michael, Sunny Dhiana, Andy Ma Outline: 00:00 Interpretability in AI 01:02 AssemblyAI (Sponsor) 02:23 Simple example 03:51 Code example: SHAP 05:17 Shapley Values explained 07:59 Shortcomings of Shapley Values 💻 Demo for SHAP on LLaMA 2 LLM: https://drive.google.com/drive/folders/1EE2F5fbrBMO28DWzcKll9V_MImydsg3N?usp=sharing Keep in mind that you need to have the resources to run LLaMA 2. If not, try out the “gpt2” model in the code. You can find simple examples here: https://shap.readthedocs.io/en/latest/ (see e.g., “Text examples”) 📙“Interpretable Machine Learning” by C. Molnar: https://christophm.github.io/interpretable-ml-book/ ▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀ 🔥 Optionally, pay us a coffee to help with our Coffee Bean production! ☕ Patreon: https://www.patreon.com/AICoffeeBreak Ko-fi: https://ko-fi.com/aicoffeebreak Join this channel to get access to perks: https://www.youtube.com/channel/UCobqgqE4i5Kf7wrxRxhToQA/join ▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀ 🔗 Links: AICoffeeBreakQuiz: https://www.youtube.com/c/AICoffeeBreak/community Twitter: https://twitter.com/AICoffeeBreak Reddit: https://www.reddit.com/r/AICoffeeBreak/ YouTube: https://www.youtube.com/AICoffeeBreak #AICoffeeBreak #MsCoffeeBean #MachineLearning #AI #research​ Video editing: Nils Trost
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aicoffeebreak.bsky.social @aicoffeebreak.bsky.social · 08/04/2024
How did they steal parts of LLMs protected behind APIs? 🥷 We explain both papers that made a breakthrough on this, one from Carlini et al. (Google), and the other one from Finlayson et al. (USC), see references in the video description. 📺 youtu.be/O_eUzrFU6eQ
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Stealing Part of a Production LLM | API protect LLMs no more
How it is possible to steal part of LLMs protected behind an API? 🥷 We explain both papers that made a breakthrough on this, one from Carlini et al. (Google...
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aicoffeebreak.bsky.social @aicoffeebreak.bsky.social · 04/03/2024
Genie 🧞 just watched YouTube videos and inferred actions and learned to render environments! 🗺️ In this video, we explain the Genie paper from @googledeepmind.bsky.social . 👇 📺 youtu.be/QaqX9B3jqYI
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Genie explained 🧞 Generative Interactive Environments paper explained
Genie just watches YouTube videos and inferred actions and learned to render environments! 🗺️ In this video, we explain the Genie paper from Google DeepMind...
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aicoffeebreak.bsky.social @aicoffeebreak.bsky.social · 17/02/2024
We simply explain and illustrate Mamba and (Selective) State Space Models – SSMs. 📺 youtu.be/vrF3MtGwD0Y SSMs match performance of transformers, but are faster and more memory-efficient than them. This is crucial for long sequences!
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MAMBA and State Space Models explained | SSM explained
We simply explain and illustrate Mamba and (Selective) State Space Models – SSMs.SSMs match performance of transformers, but are faster and more memory-effic...
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aicoffeebreak.bsky.social @aicoffeebreak.bsky.social · 03/02/2024
Contextual sparsity: Take an LLM and make it sparse at inference time. In this video, we explain how the DEJAVU method implements contextual sparsity. 📺 youtu.be/DUkWMoi5nG4
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Sparse LLMs at inference: 6x faster transformers! | DEJAVU paper explained
Contextual sparsity: Take an LLM and make it sparse at inference time. In this video, we explain how the DEJAVU method implements contextual sparsity.📜 Liu,...
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aicoffeebreak.bsky.social @aicoffeebreak.bsky.social · 31/01/2024
Finetuning LLMs is now possible without reinforcement learning, but with Direct Preference Optimization (DPO). 📺 youtu.be/XZLc09hkMwA In this video, we explain: 👉 the DPO paper 👉 RLHF and why reinforcement learning was needed in the first place.
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Direct Preference Optimization: Your Language Model is Secretly a Reward Model | DPO paper explained
Direct Preference Optimization (DPO) to finetune LLMs without reinforcement learning. DPO was one of the two Outstanding Main Track Runner-Up papers.📜 Rafai...
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aicoffeebreak.bsky.social @aicoffeebreak.bsky.social · 31/01/2024
All you need to know about the transformer architecture: 👉 How to structure the inputs 👉 Attention (Queries, Keys, Values) 👉 Position embeddings 👉 Residual connections. 📺 youtu.be/ec9IQMiJBhs Bonus: an overview of the difference between Recurrent Neural Networks (RNNs) and transformers.
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Transformers explained | The architecture behind LLMs
All you need to know about the transformer architecture: How to structure the inputs, attention (Queries, Keys, Values), positional embeddings, residual conn...
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