Currently in Accra for @DeepIndaba
. Looking forward to a week of discussions around technical topics in AI and learning new cultures 🙂
@jeande_d
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Jean at Deep Indaba in Accra for AI Technical Discussions
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Stanford XCS224U: Natural Language Understanding Course 2023
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Stanford XCS224U: Natural Language Understanding, 2023 Excellent lectures on natural language understanding. The course covers a wide range of topics including domain adaptation for supervised sentiment, retrieval augmented in-context learning, NLP techniques/methods, etc…
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Karpathy’s GPT State of the Art Talk Remains Insightful
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This talk, "The state of GPT" by Karpathy, I have watched it multiple times and always surprised of how it still feels new. The talk covers the training paradigms of GPT assistant models, common prompting techniques, retrieval-augmented LLMs, …, and practical recommendation
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Deep Learning Indaba 2023 in Accra: African AI Community Meeting
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Deep Learning Indaba 2023 is happening in the next few days. It's the annual meeting of African AI community, happening in Accra this time. Many students from different countries in Africa wish to attend the event, but it's not easy for them to get the travel expenses. There is
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Natural Language Processing Course UT Austin Lecture Videos and Materials
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Natural Language Processing – UT Austin Lecture videos: https://
youtube.com/playlist?list=
PLofp2YXfp7TZZ5c7HEChs0_wfEfewLDs7
… Website(for slides, readings): https://
cs.utexas.edu/~gdurrett/cour
ses/online-course/materials.html
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UT Austin NLP Lectures: From Basics to LLMs and Beyond
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Natural Language Processing – UT Austin A concise series of NLP lectures from UT Austin. Covers a vector of topics from basics of machine learning, NLP fundamentals, models(BERT, BART, T5, GPT-3…), and hot topics/trends in LLMs including instruction tuning, chain-of-thoughts,
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Data privacy concerns and proactive measures discussed
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Data privacy is a concern in all walks of internet, but I am sure this is something they thought about and probably have actions in place.
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Specialists vs Generalists: When Task-Specific Models Outperform GPT
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There are instances where “doing well on one specific task” is better than being “a generalist”. GPT-3.5 and GPT-4 are generalists. They perform reasonably well on many language tasks without having to adapt them to any of those tasks, but their performances are limited in
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Transformers and Large Language Models Lectures at Simons Institute
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Large Language Models and Transformers – Simons Institute Excellent lectures on ongoing revolution in transformers and large language models. Topics range from recent publications, frontier/foundational works, and all things LLMs. Features people who are at the forefront of AI
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Stanford CS324 LLM Course: Comprehensive Notes on Large Language Models
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[Lecture notes] Stanford CS324 – Large Language Models Excellent notes on various topics related to large language models: fundamentals of language models, capabilities of LLMs, data behind LLMs, modeling, training, scaling laws, selective architectures, task adaptation, and