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The robot dogs lined up in their dozens Thursday in Japan were no tech fair display. They were the dearly departed being honoured with their own traditional “funeral.” In some respects, it was a funeral like any other in Japan, with incense smoke wafting as a priest chanted a sutra, praying for the peaceful transition of the souls of the departed.
But the departed were 114 of Sony’s old generations of AIBO robot dogs, each wearing a tag to show where they came from and to which family they belonged. Electronics repair company A FUN, which specialises in fixing vintage products, has sent off some 800 AIBOs this way in recent years at a centuries-old Buddhist temple.
All companies testing autonomous vehicles on the state’s public roads must provide annual reports to the DMV about “disengagements” that occur when a human backup driver has to take over from the robotic system. The DMV told eight companies with testing permits to provide clarification about their reports. More than 50 companies have permits to test autonomous vehicles with backup drivers on California roads but not all of them have deployed vehicles.
It turns out that a number of the issues reported are shared across technology from different companies. Some of the problems had to do with the way the cars sense the environment around them. Others had to do with how the vehicles maneuver on the road. And some had to do with what you might expect from systems made up of networked gadgets: hardware and software failures.
A new study by scientists at Oregon Health and Science University and Massachusetts General Hospital on a specialised AI algorithm found that it was able to automatically diagnose a disease that causes childhood blindness more accurately than trained physicians can, a step towards automating medical tasks that are often bottle-necked by a shortage of doctors.
The algorithm was shown sample images of eye scans and correctly diagnosed patients with ROP 91 percent of the time. Physicians trained to diagnose the disease had an average accuracy of 82 percent using the same images.
In a recent conversation, Facebook AI research scientist Moustapha Cissésaid, “You are what you eat, and right now we feed our models junk food.” Well, just like you can’t eat better if you don’t know what’s in your food, you can’t train less biased models if you don’t know what’s in your training data. That’s why the recent paper “Datasheets for Datasets” is so interesting. In it, Timnit Gebru and her coauthors from Microsoft Research and elsewhere propose the equivalent of food nutrition labeling for datasets.
The “Datasheets” paper explores the idea of using standardised datasheets to communicate this information to users of datasets, commercialised APIs, and pre-trained models. In addition to helping to communicate data biases, the authors propose that such datasheets can improve transparency and provide a source of accountability.
In the UK, one business, Cera, is using technology to offer care services for older people who require assistance with day-to-day living and would benefit from professional home care.
“We use digital to streamline the matching of patients and carers based on a number of characteristics — where they are, the type of care they need, what time they need it, the skill mix of care workers, language, whether they have pets or not,” Ben Maruthappu, the company’s CEO, told CNBC’s Nadine Dereza.
To promote more creativity, Google is opening up a new investment programme for early-stage startups that share their passion for the digital assistant ecosystem, helping to push new ideas forward and advance the possibilities of what digital assistants can do.
This new programme will consist of several components:
Investment capital from Google to provide additional financial resources for the development, hiring, and management of these startups.
Advice from Google engineers, product managers, and design experts to share technical guidance and product development feedback.
Google partnership programs that provide early access to upcoming features and tools so startups can bring their products to market as quickly as possible.
Just 10 months after stepping down from the helm of People Operations at Google, Laszlo Bock turned heads yet again, revealing in a May 1, 2017 LinkedIn post that he and fellow ex-Googler Wayne Crosby were starting up a new venture called Humu.
A couple of days ago, after a year spent operating under the radar, Bock and Crosby marked Humu’s first anniversary by breaking their silence. In a post authored by Crosby, the head of engineering and product acknowledged some of what Humu and its 20 employees had accomplished out of the public eye, including quietly raised more than $40 million in series A and B funding led by Index Ventures and IVP, respectively. Crosby said in an interview, “Our mission is to make work better for everyone, everywhere. We think of ourselves as a behavioural change company that comes at this from how we can use the data in organisations to help make them better, and leverage some of the existing technology advancements in machine learning, as well as in behavioral science and behavioral economics.”