#ArtificialIntelligence can potentially predict a patient’s response to cancer treatment https://
interestingengineering.com/health/artific
ial-intelligence-predict-response-cancer-treatment
… @IntEngineering #Healthcare #AI #MachineLearning #DataScience #BigData #Analytics #100DaysofCode #IoT #serverless #womenwhocode #DeepLearning #DigitalTransformation
DATA
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AI Predicts Patient Response to Cancer Treatment
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DeepMind’s Epistemic Networks Reduce LLM Fine-Tuning Data Requirements
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DeepMind’s Epistemic Neural Networks Enable Large Language Model Fine-Tuning With 50% Less Data https://
syncedreview.com/2022/11/16/dee
pminds-epistemic-neural-networks-enable-large-language-model-fine-tuning-with-50-less-data/
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Learning Actions from Data Rather Than Building Them In
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We don't need to build it in, because it's very easy to learn from data (cf. infants). And we arguably shouldn't, because what your actions are can change (e.g., moving your hands vs. driving your car).
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Data Science Innovation in Finance and Insurance Leadership
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Where is data science headed in finance and insurance? Read our new ebook for answers from FSI leaders at @jpmorgan
, @Allstate
, @BNYMellon
, @NM_Financial
, @NVIDIAAI and more! Read "The Finance and Insurance Data Science Innovator's Playbook" now! https://
domino.buzz/3ty3MVF -
Ramin Hasani on Liquid Neural Nets and Sequence Modeling
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Hi there! It’s Ramin Hasani @raminmh
! Over the next 24H, I’m taking over @MIT_CSAIL
’s Twitter! I’m a research affiliate at CSAIL. I design brain-inspired robust deep learning algorithms! Ask me anything about sequence modeling, time series, robots, & liquid neural nets, here -
IBM Research Uses Synthetic Data to Accelerate AI Training
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Synthetic data are computer-generated examples that can augment or replace real data to speed up the training of #AI. Here’s how @IBMResearch is using this “fake data”
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Hugging Face Releases 1.3T Parameter Mixture-of-Experts Model
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We’ve heard mixture-of-experts (MoE) were in the air (GPT4??) so we’ve just added the first one in the transformers library for you to play with 🙂 With for nothing less than a 1.3 trillion parameters checkpoint model on the hub! The largest model on the hub at the moment
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Technical risks of prolonged machine learning model training
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Nice ! Mais attention a l’incompréhension que tu suggère , c’est pas parce que on entraîne plus longtemps que c’est forcément mieux. Ton gradient peut diverger et aller dans les cactus . Ou juste stagner et là tu as juste gaspiller de l’électricité et un GPU.
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Datasette tutorials organization in core repository
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I started putting some tutorials together at https://
datasette.io/tutorials – but I've been wondering whether those should live in the core Datasette repository too -
Improving End-User Documentation for Data Projects
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I've been puzzling over that myself! It's the big missing hole in my projects – most of them are developer-focused, so I can get away with mostly API documentation – but I'm very aware that @datasetteproj itself needs much better docs for end-users