Automatic object recognition in images is currently tricky. Even if a computer has the help of smart algorithms and human assistants, it may not catch everything in a given scene. Google might change that soon, though; it just detailed a new detection systemthat can easily spot lots of objects in a scene, even if they're partly obscured. The key is aneural network that can rapidly refine the criteria it's looking for without requiring a lot of extra computing power. The result is a far deeper scanning system that can both identify more objects and make better guesses -- it can spot tons of items in a living room, including (according to Google's odd example) a flying cat. The technology is still young, but the internet giant sees its recognition breakthrough helping everything fromimage searches through to self-driving cars. Don't be surprised if it gets much easier to look for things online using only vaguest of terms.
Yesterday, we wrote that Coinbase customers were being charged multiple times for past transactions. While some speculated that the erroneous withdraws were down to a Coinbase engineering issue, Coinbase issued a statement saying it wasn’t liable for the duplicate charges. The blame, instead, rested with Visa for the way it handled a migration of merchant categories for cryptocurrencies, Coinbase said. While you can read my post yesterday for an in-depth description of what happened, the basic gist is that Visa refunded and recharged (under a different merchant category) a month of old transactions. Many users saw the recharge come through before the refund processed, making it look like they were double charged. Honestly, the issue was likely exacerbated by existing payment rails — it’s normal for refunds to take multiple days to show up on credit and debit statements. But here’s where it gets weird — this morning Visa issued a statement to some publications shifting the blam...
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