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AI can’t solve this: The coronavirus could be highlighting just how overhyped the industry is

The world is facing its biggest health crisis in decades but one of the world’s most promising technologies — artificial intelligence (AI) – isn’t playing the major role some may have hoped for.

Renowned AI labs at the likes of DeepMind, OpenAI, Facebook AI Research, and Microsoft have remained relatively quiet as the coronavirus has spread around the world.

“It’s fascinating how quiet it is,” said Neil Lawrence, the former director of machine learning at Amazon Cambridge. “This (pandemic) is showing what bulls–t most AI is. It’s great and it will be useful one day but it’s not surprising in a pandemic that we fall back on tried and tested techniques.”

Those techniques include good, old-fashioned statistical techniques and mathematical models. The latter is used to create epidemiological models, which predict how a disease will spread through a population. Right now, these are far more useful than fields of AI like reinforcement learning and natural-language processing.

Of course, there are a few useful AI projects happening here and there. In March, DeepMind announced that it had used a machine-learning technique called “free modelling” to detail the structures of six proteins associated with SARS-CoV-2, the coronavirus that causes the Covid-19 disease. Elsewhere, Israeli start-up Aidoc is using AI imaging to flag abnormalities in the lungs and a U.K. start-up founded by Viagra co-inventor David Brown is using AI to look for Covid-19 drug treatments.

Verena Rieser, a computer science professor at Heriot-Watt University, pointed out that autonomous robots can be used to help disinfect hospitals and AI tutors can support parents with the burden of home schooling. She also said “AI companions” can help with self isolation, especially for the elderly.

Why hasn’t AI had more impact? AI researchers rely on vast amounts of nicely labeled data to train their algorithms, but right now there isn’t enough reliable coronavirus data to do that.

“AI learns from large amounts of data which has been manually labeled — a time consuming and expensive task,” said Catherine Breslin, a machine learning consultant who used to work on Amazon Alexa.

“It also takes a lot of time to build, test and deploy AI in the real world. When the world changes, as it has done, the challenges with AI are going to be collecting enough data to learn from, and being able to build and deploy the technology quickly enough to have an impact.”

AI can’t solve this: The coronavirus could be highlighting just how overhyped the industry is, CNBC, Apr 29

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