They said (paraphrase) "we train the audio models on CC data because training on copyrighted data would be problematic." Thus, they imply that training on copyrighted images is also problematic — but they don't care because there's no strong lobby like RIAA there.
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Artificial Intelligence Tracking Climate Invention Patents
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Tracking artificial intelligence in climate inventions with patent data – http://
Nature.com Read more here: https://
ift.tt/Ago8dfP #ArtificialIntelligence #AI #DataScience #100DaysOfCode #Python #MachineLearning #BigData #DeepLearning #NLP #Robots #IoT -
Large Language Models Will Define Artificial Intelligence
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Large Language Models Will Define Artificial Intelligence – Forbes Read more here: https://
ift.tt/zoqIBD6 #ArtificialIntelligence #AI #DataScience #100DaysOfCode #Python #MachineLearning #BigData #DeepLearning #NLP #Robots #IoT -
Data Science vs Artificial Intelligence Key Comparisons
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Data science vs. artificial intelligence (AI): Key comparisons – VentureBeat Read more here: https://
ift.tt/dawbJcK #ArtificialIntelligence #AI #DataScience #100DaysOfCode #Python #MachineLearning #BigData #DeepLearning #NLP #Robots #IoT -
AI Determines Brain Age Through Advanced Neural Analysis
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How old is your brain, really? Artificial intelligence knows – USC News Read more here: https://
ift.tt/jR1soGw #ArtificialIntelligence #AI #DataScience #100DaysOfCode #Python #MachineLearning #BigData #DeepLearning #NLP #Robots #IoT -
Generative Modeling for Time Series Forecasting with Diffusion VAE
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This work addresses the time series forecasting problem with generative modeling; involves a bidirectional VAE backbone equipped with diffusion, denoising for prediction accuracy, and disentanglement for model interpretability. 11 of 11
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Top Machine Learning Papers of the Week
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Top ML Papers of the Week (Jan 9-15): – DreamerV3
– DeepMatcher
– Multimodal deep learning
– Transformer compiler for RASP
– Potential misuses of LMs and mitigations
– Scaling laws for generative mixed-modal LMs
– Time series forecasting with generative modeling
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Open Architecture vs Fair Data Compensation in AI
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Seems to me that there are two orthogonal issues:
– should your architecture be open? – where do you get your data from/are contributors justly compensated? Both are tricky. But virtue in one doesn’t logically entail virtue in the other. -
McKinsey AI Strategy: Building Blocks and Data Intelligence
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McKinsey: Using #AI Strategically – Focus on Building Blocks, Making Sense of Data https://
mckinsey.com/capabilities/s
trategy-and-corporate-finance/our-insights/artificial-intelligence-in-strategy
… @pierrepinna @sallyeaves @PawlowskiMario @Xbond49 @gvalan @psb_dc @HaroldSinnott @Shi4Tech @mikeflache @Nicochan33 #MachineLearning #DeepLearning #Fintech #Datascience -
Data Scientists Can Now Benchmark Models Against AI Engine
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If you are a data scientist, you can now benchmark your model against those created by our AI engine. This is huge! Check it out here: https://
abacus.ai/humanchallenger