Ocado's warehouse in Erith, 15 miles east of London on the Thames estuary, is staffed by 1,050 "personal shoppers". Outnumbering them are 1,800 robots the size of small washing machines. You see them by climbing to the top level of the vast warehouse – at 564,000 sq ft, it is more than three times the size of St Peter's in Rome – where a sign tells you that photography is strictly prohibited. The online supermarket is paranoid that rivals will glimpse the technology it believes to be revolutionary. From the viewing platform you can watch these metal cubes endlessly whiz around, moving thousands of plastic crates as if they were playing an enormous game of chess. You occasionally sight bottles of bleach or rosé, packets of noodles and dog biscuits, before they are sent down to a lower level. "I find it quite mesmerising, like robotic ballet," says Mel Smith, CEO of Ocado Retail, the UK arm of the business. "The day I decided I wanted this job was when I went to [the warehouse] and thought, this is absolutely the future."
Last week the Canadian government tabled legislation as part of its climate action plan to meet and exceed Canada's emissions reduction targets. This followed comments made two days earlier by the Bank of Canada's Governor in which he cautioned that climate change will have a profound impact on our economy. A survey conducted by IBM last month shows that the majority Canadians agree – 73% believe the advancement of clean technologies and artificial intelligence are important in ensuring economic growth. The survey also reveals that most people are keen to integrate more technology into their personal lives if it would support planetary health – 74% of Canadians said they are willing to adopt technology solutions to help live a more environmentally friendly lifestyle. So, while countries around the world – including ours – work towards the 2050 net zero emission goal and implement other innovative'good tech' measures to combat climate change, how can we do our part with the technology we use every single day?
The number of artificial intelligence (AI) researchers in Canada's private sector is proportionally higher than that of other countries, according to Montreal-based Element AI's 2020 Global AI Talent Report. The report found that Canada has 367 AI researchers, making it second only to the US. The Global AI Talent Report measured the size of the available talent pool in the AI industry through self-reported data on social media and demand via the monthly total job postings for the same role up to August 2020. The goal of the report is to assess the most current global patterns for the worldwide AI talent pool. The report tracked 477,956 people worldwide working in the AI industry, of which 61 percent worked in productization, 38 percent in engineering, and a mere one percent in research.
As the number of COVID-19 infections are again spiking around the U.S., health care workers struggling to stay ahead have a tool with a novel approach to add to their arsenal in COVID-Net, an open source AI-based platform that uses radiological lung images to determine COVID-19-specific lung damage, as well as assess the degree of that damage. The technology was developed in March, during the early days of the pandemic, but has been gaining more notice as an example of artificial intelligence in health care as more organizations have adopted it. Although the nonprofit project is being led by Red Hat, Boston Children's Hospital and DarwinAI (a 3-year-old proprietary artificial intelligence startup headquartered in Waterloo, Ontario), it began as a collaboration between Canada's University of Waterloo and DarwinAI. "COVID-Net was an initiative to try to contribute to the whirlwind of the pandemic in March," DarwinAI CEO Sheldon Fernandez told ITPro Today. "We open sourced it and we didn't want it to be commercial.
Artificial intelligence is being used now to support human staff with text messaging being a prime example, an Ontario mutual CEO says. "We are seeing a reduction in cycle times that we have now eliminated that dreaded phone tag that really sucks the life out of the customer experience," Irene Bianchi, CEO of Peel Mutual Insurance Company, said recently at the Future of Insurance Canada online conference. Peel Mutual is talking with some of its customers using Hi Marley, an artificial intelligence-based text messaging system. The Boston-based company says its system lets employees interact with customers through a web-based application while customers communicate by texting. Those customers do not have to download an app or visit a website to speak with an insurance company rep.
AMP Robotics, the recycling robotics technology developer backed by investors including Sequoia Capital and Sidewalk Infrastructure Partners, is close to closing on as much as $70 million in new financing, according to multiple sources with knowledge of the company's plans. The new financing speaks to AMP Robotics' continued success in pilot projects and with new partnerships that are exponentially expanding the company's deployments. Earlier this month the company announced a new deal that represented its largest purchase order for its trash sorting and recycling robots. That order, for 24 machine learning-enabled robotic recycling systems with the waste handling company Waste Connections, was a showcase for the efficacy of the company's recycling technology. That comes on the back of a pilot program earlier in the year with one Toronto apartment complex, where the complex's tenants were able to opt into a program that would share recycling habits monitored by AMP Robotics with the building's renters in an effort to improve their recycling behavior.
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David Van Bruwaene and Fion Lee-Madan are the co-founders of Fairly AI, a Waterloo-Toronto Founder Institute portfolio company. Fairly AI is a tool for organizations to audit their artificial intelligence (AI) systems from across all business units, to eliminate bias, protect privacy, and ensure transparency of automated decisions. Research into fairness in machine learning is a topic becoming of increasingly greater interest to laypeople and non-technologists, because the implications that "biased" artificial intelligence can have on society are enormous. For example, if industries like housing, lending, education, or human resources that utilize AI in their decision-making - based on historical data that included variables such as gender, ethnicity, or disability - the AI may learn to replicate that input data's statistical regularities. If there was a pattern of discrimination in the "input data," then there will likely be a discriminatory pattern in the "output" data, resulting in machine learning that is not'fair.'