Feed Algorithms, Interest Mapping, Serendipity Engineering, Recommendation Systems
Startup Uses NVIDIA RTX-Powered Generative AI to Make Coolers, Cooler
blogs.nvidia.com·17h
Designing a metadata-driven ETL framework with Azure ADF: An architectural perspective
infoworld.com·19h
HFOSS at UN Open Source Week
blog.vipul.dev·22h
"What's Up, Doc?": Analyzing How Users Seek Health Information in Large-Scale Conversational AI Datasets
arxiv.org·2h
Mixed nuts #15
brycewray.com·12h
Incredible.
threadreaderapp.com·9h
Brain2Model Transfer: Training sensory and decision models with human neural activity as a teacher
arxiv.org·2h
Google Search tests “Preferred Sources” for Top Stories
searchengineland.com·13h
Deception Detection in Dyadic Exchanges Using Multimodal Machine Learning: A Study on a Swedish Cohort
arxiv.org·2h
Facing life’s wild unknowns | Science
science.org·17h
If we get things right, AI could have huge benefits
lesswrong.com·22h
Innovation Meets Intelligence: Announcing the Winners of the Built-On Databricks Startup Challenge
databricks.com·15h
The Road to Fully Autonomous Driving. Are We There Yet?
pub.towardsai.net·18h
Phonetically-Augmented Discriminative Rescoring for Voice Search Error Correction
machinelearning.apple.com·6h
In RAG systems, who's really responsible for hallucination... the model, the retriever, or the data?
Problem-solving is at least 50% of every job in tech and science.
threadreaderapp.com·20h
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