AI News, Tech Giants Hunt for AI Startups—and the Brains Behind Them artificial intelligence

AI-powered robot warehouse pickers are now ready to go to work

In the summer of 2018, a small Berkeley-based robotics startup received a challenge.

Knapp, a major provider of warehouse logistics technologies, was on the hunt for a new AI-powered robotic arm that could pick as many types of items as possible.

So every week, for eight weeks, it would send the startup a list of increasingly difficult items—opaque boxes, transparent boxes, pill packages, socks—that covered a range of products from its customers.

The startup team would buy the items locally and then, within the week, send back a video of their robotic arm transferring the items from one gray bin to another.

There are two categories of tasks in warehouses: things that require legs, like moving boxes from the front to the back of the space, and things that require hands, like picking items up and placing them in the right place.

“Moving stuff between the fixed points—that’s a problem that mechatronics is really great for.” But automating the motions of hands requires more than just the right hardware.

In the last few years research labs have made incredible advances in combining AI and robotics to achieve such dexterity, but bringing them into the real world has been a completely different story.

But it wasn’t until the recent progress in deep learning, and in particular reinforcement learning, that this level of accuracy became possible.

Inside, several industrial robots and “co-bots,” collaborative robots designed to operate safely around humans, train for every product possibility.

The team especially looks for things that might trip the robot up: highly reflective metallic surfaces, transparent plastics, and easily deformable surfaces like cloth and chip bags that will look different to a camera every time.

In seconds, the algorithm analyzes their positions, calculates the attack angle and correct sequence of motions, and extends the arm to grab on with a suction cup.

In one particularly impressive demonstration, the robot also reversed its air flow to blow a pesky bag pressed against a bin’s wall into the center for easier access.

“They don’t find people, so they need more automation.” Covariant has raised $27 million to date, with funders including AI luminaries like Turing Award winners Geoffrey Hinton and Yann LeCun.

In addition to product picking, it wants to eventually encompass all aspects of warehouse fulfillment, from unloading trucks to packing boxes to sorting shelves.

Can we ever trust Google with our health data?

As the tech giant moves deeper into healthcare, it plans to fight medical misinformation in search results, create tools to be used by thousands of doctors, and improve the accuracy of diagnosis with technologies like computer vision to read X-rays.

Google’s broader health mission was outlined at a conference in San Francisco earlier this month, where its top doctor set out to show why the company may be the most ambitious of the many trying to use technology to transform healthcare.

The wiry grey-haired child psychiatrist, who is the former chief executive of the Geisinger healthcare system in Pennsylvania, was hired last year to sort through Google’s scattershot health projects to find a focus —

One task is to combine artificial intelligence teams working on health at Google Brain and DeepMind with those working on smart devices for health at its Nest division.

a scandal erupted after the Wall Street Journal reported in November that Google engineers had access to medical records held by Ascension, the country’s second-largest healthcare system, as they built new products.

But if Google is going to come anywhere near reaching its ambitious goals in healthcare, it needs to convince health systems like Ascension to give up their patient data and ease patients’

Robert Wachter, chair of the department of medicine at the University of California, San Francisco, and author of Digital Doctor, a book about how technology is transforming medicine, says Google’s task has become harder as potential partners worry about the public reaction.

After transforming almost every other industry, the world’s largest tech companies now want to fix stretched healthcare systems, an industry worth $8.7tn worldwide.

Amazon has bought an online pharmacy and entered into a joint venture, Haven, with JPMorgan and Berkshire Hathaway, which aims to create a new kind of health insurance for the companies’

It could combine electronic health records with data from smartphones, genomes, information from sensors such as glucose monitors and even apps that record eating habits, he says.

Seen through that lens, he says Google’s recent $2.1bn offer for Fitbit, the activity tracking wearable technology company, is about acquiring “one of the most exquisite data sources for a couple of billion”.

As well as Fitbit, deals done by its Nest division suggest it sees the smart home as an important door into digital health, helping monitor patients outside of the hospital.

In 2017, it bought Senosis Health, which builds smartphone apps that track information such as lung function by using the microphone as a flowmeter, and Knit Health, which makes a smart baby monitor that could also be used to monitor adults’

Google has patented various of what it calls “non-invasive health-monitoring devices”, including a toilet seat sensor to measure heart rate and blood pressure, which some might consider invasive.

It is not yet clear how Dr Feinberg’s work will fit with health projects in other areas of Alphabet, Google’s parent company, which includes Verily, a life sciences division, and Calico, a unit researching ways to slow ageing.

Christine Lemke, co-founder and president of Evidation, a health measurement platform that provides data analytics to tech and pharma companies, says one of Google’s key advantages is it can use unconventional sources of data to understand health.

“Because of search, they’re already the largest provider of healthcare information and they can leverage that position to incorporate other non-traditional data to drive even more personalised care,”

Talking about Google’s work to improve the accuracy of mammograms by using medical records and genetic information, he said: “There is incredible power in the ability not only with the data, but combining the different data sets.”

“In some ways, after watching DeepMind in the NHS . . . it is completely predictable that a large data-sharing arrangement with a healthcare organisation was going to receive a lot of public scrutiny,”

A spokesperson said: “We believe our healthcare research could help save lives in the future, which is why we take privacy seriously and follow all relevant rules and regulations in our handling of health data.”

Google may actually be seen as the best of a bad bunch: in a Rock Health survey earlier this year, only 11 per cent of consumers said they were willing to share health data with tech companies.

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