There is something immensely satisfying about identifying a real bargain in a charity shop or thrift store. In among the 17 copies of last year’s must-read summer-holiday novel, and the three cups with saucers that don’t match, you might stumble across a hidden gem. My best-ever find was a set
Continue Reading Data hoarding: Would a Marie Kondo approach to data storage bring you joy?
A properly trained special-purpose AI can be a wonderful thing. AI systems have already displayed super-human performance in many fields, from diagnosing specific medical conditions, to spotting fraudulent transactions, or identifying infringing content amongst the fire-hose of social media.
These systems tend to rely upon some form of neural-network based
Continue Reading Shall we play a game? Reinforcement learning and the AI training data challenge
67% … 84% … 93% … 99.2% … and then stuck interminably at 99.9%. C’mon! Download you unspeakable nuisance! I need to see the next episode.
We might think we still see the dread message “Buffering…” far too frequently, but in reality in any major metropolitan area we are already
Continue Reading Please wait: This article is buffering … Why massive bandwidth might not be the most important aspect of 5G and next generation Internet services
When was the last time you saw a panda? In fact, have you ever seen a real life panda…? They’re not that common after all. I know that I’ve only ever seen live pandas once in my just over four decades, and it required a very special effort to go
Continue Reading What’s black and white and wrong all over? AI and biases in training data.
Sitting at 36,000 feet over the Atlantic writing this article, I’m unusually aware of the traditional use of the phrase “black box”: an aircraft’s flight data recorder, there to let investigators understand what went awry should the worst happen. It seems odd that a device whose purpose is to provide
Continue Reading Isn’t the whole point of a black box to tell you exactly what happened? AI’s explainability conundrum
