12 Posts
Getting high accuracy out of a classifier trained on a small number of examples is tricky. You might train the model on several large-scale datasets prior to few-shot training, but what if the few-shot dataset includes novel classes? A new method performs well even in that case.
Shoppers at Amazon’s newest grocery store can skip the checkout line. Amazon opened its first full-scale supermarket that monitors which items customers place in their cart and charges them automatically when they leave. It calls the system Just Walk Out.
Getting high accuracy out of a classifier trained on a small number of examples is tricky. You might train the model on several large-scale datasets prior to few-shot training, but what if the few-shot dataset includes novel classes? A new method performs well even in that case.
Shoppers at Amazon’s newest grocery store can skip the checkout line. Amazon opened its first full-scale supermarket that monitors which items customers place in their cart and charges them automatically when they leave. It calls the system Just Walk Out.
An AI system is helping aircraft avoid bad weather, restricted airspace, and clogged runways. Alaska Airlines will route all its flights using a system from Airspace Intelligence called Flyways.
Last week, I mentioned that one difference between traditional software and AI products is the problem of unclear technical feasibility. In short, it can be hard to tell whether it’s practical to build a particular AI system.
Many people both outside and inside the tech industry believe that AI will serve mostly to boost profits and monitor people — without regard for negative consequences.
An AI system is helping aircraft avoid bad weather, restricted airspace, and clogged runways. Alaska Airlines will route all its flights using a system from Airspace Intelligence called Flyways.
Last week, I mentioned that one difference between traditional software and AI products is the problem of unclear technical feasibility. In short, it can be hard to tell whether it’s practical to build a particular AI system.
Last week, I mentioned that one difference between traditional software and AI products is the problem of unclear technical feasibility. In short, it can be hard to tell whether it’s practical to build a particular AI system.
Many people both outside and inside the tech industry believe that AI will serve mostly to boost profits and monitor people — without regard for negative consequences.
Last week, I mentioned that one difference between traditional software and AI products is the problem of unclear technical feasibility. In short, it can be hard to tell whether it’s practical to build a particular AI system.
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