Awesome work by @pearsekeane (longtime collaborator w/
@GoogleAI & @GoogleDeepMind
) and many others from many institutions, showing that training a universal model on 1.6 million retinal images can then be fine tuned for 10+ downstream clinical tasks in ophthalmology & oculomics.
MACHINE LEARNING
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Universal Retinal Model Fine-Tuned for Clinical Ophthalmology Tasks
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Data Science Interview Questions and Answers Curated List
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GitHub – youssefHosni/Data-Science-Interview-Questions-Answers: Curated list of data science interview questions and answers https://
bit.ly/42FHnF3 #AI #MachineLearning #DeepLearning #LLMs #DataScience -
Foundation Models Terminology Debate in AI Discourse
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Still don't understand why people want to say "foundation models" when we've had -base models
-pretrained models etc forever. Some people even call them "foundational" models, I saw that term in some EU documents. Smh. -
Topics for Figure Research Event Discussion
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Let us know what topics you'd like to see discussed at a figure Research@ event
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Research@ Accra Showcases AI Applications Across Multiple Domains
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Last week we hosted Research@ Accra in Ghana—it was an inspiring day of lightning talks & interactive demos where researchers explored important topics like weather impact, building detection, food security, maternal health, & automatic speech recognition.
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SAS Expands Generative AI Strategy with Proven Deep Learning Expertise
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Shadi Shahin, VP Product Strategy, on our expanding GAI strategy & differentiation: "We've been around for a long time with proven muscle, and a strong history with the ingredients that go into categories of GAI, like reinforcement learning, deep learning, NLP…" #ExploreSAS
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Data Access and Domain-Specific AI Deployment Strategy
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Jared Peterson, SVP R&D, kicks off Day 2 of #ExploreSAS: "… data lives in a lot of places. We need to access it wherever it is to train & build models… Analytics & AI show up differently based on the domain they’re being deployed into. Those differences matter."
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Large Language Models Explained Simply Without Math
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Large language models, explained with a minimum of math and jargon https://
bit.ly/3OMcESV #AI #MachineLearning #DeepLearning #LLMs #DataScience -
Brilliant Interactive Explainer on How Transformers Work
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This interactive explainer from @madhumita29 & the team at FT about how transformers work is absolutely brilliant. Clear and informative. Required reading. https://
ig.ft.com/generative-ai/ -
Explanation of backpropagation: max function implements NAND gates
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This explanation was kind of polarising — some people found it pointlessly abstruse, others found it worked for them when others didn't: https://
thinc.ai/docs/backprop1
01
… If you get down to the bit with the two tables, it explains how a max function can implement nand, while a linear