In the News
Companies hoping to use artificial intelligence should benefit from more efficient chip designs.
Inside Finland’s plan to train its whole population in artificial intelligence.
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On the convergence of human and artificial intelligence
A.I. needs lots of data to work well, which leads to virtuous circles (more data => better AI => better product => more data) that can benefit large established tech companies. Is this true though?
Scenarios have been discovered in which it is impossible to prove whether or not a machine-learning algorithm could solve a particular problem. This finding might have implications for both established and future learning algorithms.
Instagram’s recommender system serves over 1 billion users on a regular basis for feed and stories ranking as well as post recommendations and smart prefetching. Here are a few lessons learnt along the way of building this ML pipeline.
Software tools & code
Adblock Radio detects audio ads with machine-learning and Shazam-like techniques. The core engine is open source: use it in your radio product! You are welcome to join efforts to support more radios and podcasts.
About TextCNN, Bidirectional RNNs and Attention Models.
Library for training machine learning models with privacy for training data. This makes use of differential privacy.
The role of the data engineer in a startup data team is changing rapidly. Are you thinking about it the right way?
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