Yes, Apple's new video-streaming service is set to be unveiled later today -- we'll be reporting from the frontlines in San Francisco at 10am PT/1pm ET. Meanwhile, you might have missed Honda's plans for EV cycles, Overwatch changes are actually having an effect on toxic players and we put NVIDIA's RTX ray tracing to the test. Honda is having fun with electric cars, but what about the motorcycle? Don't worry, you'll get your fix soon. The automaker has unveiled prototypes for both the CR Electric dirt bike (above) and the Benly Electric delivery scooter, offering a peek at how it will approach emissions-free transportation on two wheels.

At its streaming service event in Cupertino on Monday, Apple announced that in addition to more than 300 magazine titles (including TechCrunch) as part of its newly revealed News app, the company will also include subscriptions to the LA Times and Wall Street Journal. What's more, users will get access to the entire digital newsstand for $9.99 a year. Given that users would have to shell out more than $8,000 annually to acquire these magazines individually, that's a pretty good deal. Another interesting feature included in News is the app's recommendation engine. Unlike the recommendation algorithms you'd find on other streaming services like Netflix, News's feature runs on the device itself, rather than remotely on Apple's servers.

The history of AI is often told as the story of machines getting smarter over time. What's lost is the human element in the narrative, how intelligent machines are designed, trained, and powered by human minds and bodies. In this six-part series, we explore that human history of AI--how innovators, thinkers, workers, and sometimes hucksters have created algorithms that can replicate human thought and behavior (or at least appear to). While it can be exciting to be swept up by the idea of super-intelligent computers that have no need for human input, the true history of smart machines shows that our AI is only as good as we are. On 14 February 1946, journalists gathered at the Moore School of Engineering at the University of Pennsylvania to witness a public demonstration of one of the world's first general-purpose electronic digital computers: the Electronic Numerical Integrator and Computer (ENIAC).

GITAI is a robotics startup with offices in Japan and the United States that's developing tech to put humanoid telepresence robots in space to take over for astronauts. Today, GITAI is announcing a joint research agreement with JAXA (the Japanese Aerospace Exploration Agency) to see what it takes for robots to be useful in orbit, with the goal of substantially reducing the amount of money spent sending food and air up to those demanding humans on the International Space Station. It's also worth noting that GITAI has some new hires, including folks from the famous (and somewhat mysterious) Japanese bipedal robot company SCHAFT. A quick reminder about SCHAFT: The company was founded by members of the JSK Laboratory at the University of Tokyo in order to build a robot to compete in the DARPA Robotics Challenge Trials in 2013. SCHAFT won the DRC Trials by a substantial margin, scoring 27 points out of a possible 32, 7 more points than the second place team (IHMC).

"Becoming a software company is really hard," said Vijay Gurbaxani, founding director of the Center for Digital Transformation at the University of California, Irvine. However, failing to become a software company could be detrimental to the outlook of any business. It's important for enterprises to focus on making software work for their benefit, not against it, he said in the opening remarks at the Road to Reinvention conference. The wave of improvements in machine learning during the last few years have been amazing, but it's also opening a new era of relations between humans and software that cannot be ignored, Gurbaxani explained. "New knowledge is no longer going to be restricted to humans conceiving of theories," he said.

This copy is for your personal non-commercial use only. To order presentation-ready copies of Toronto Star content for distribution to colleagues, clients or customers, or inquire about permissions/licensing, please go to: www.TorontoStarReprints.com The University of Toronto has received its largest ever donation, a $100-million gift to further the school's research on artificial intelligence. The donation from the Gerald Schwartz and Heather Reisman Foundation will in part go to a new 750,000-square-foot complex to be built at the northeast corner of College St. and Queen's Park starting this fall, school President Meric Gertler announced at a Monday news conference. The money will also help launch the Schwartz-Reisman Institute for Technology and Society. Gertler said the gift will help spark Canadian innovation and examine how technology shapes people's lives.

Government usually isn't the place to look for innovation in IT or new technologies like artificial intelligence. But Ott Velsberg might change your mind. As Estonia's chief data officer, the 28-year-old graduate student is overseeing the tiny Baltic nation's push to insert artificial intelligence and machine learning into services provided to its 1.3 million citizens. "We want the government to be as lean as possible," says the wiry, bespectacled Velsberg, an Estonian who is writing his PhD thesis at Sweden's Umeå University on how to use AI in government services. Estonia's government hired Velsberg last August to run a new project to introduce AI into various ministries to streamline services offered to residents.

Computer scientists have found a way around Google's reCAPTCHA tests, tricking the system into thinking an artificial intelligence program is human. But there's a catch, although the AI system can fool the bot test it doesn't live-up to the promise its creators give it. CAPTCHAs are the tests used by websites to battle back against bots, asking website visitors to prove they're human before proceeding. The leading system is Google's reCAPTCHA, which has previously asked website visitors to prove their humanity by checking words scanned from books or photographs of street signs. That was replaced with behavioural analysis, requiring humans to simply tick a box proclaiming "I'm not a robot".

IBM has come up with a way to use quantum computers to improve machine learning algorithms, even though we don't have anything approaching a quantum computer yet. The tech giant developed and tested a quantum algorithm for machine learning with scientists from Oxford University and MIT, showing how quantum computers will be able to map data at a far more sophisticated level than any classical computer. Somewhat ironically, the testing was minimized based on the current hardware capabilities, using only two qubits of quantum computing capacity, which can be simulated on a classical computer.. There are no fully working quantum computers because qubits can't stay in an entangled state for more than a few hundred microseconds, even in carefully controlled laboratory conditions. They break down into decoherence and can no longer be used to perform calculations in parallel, the feature of quantum computing that will give it awesome processing power.

AI has a data quality problem. In a survey of 179 data scientists, over half identified addressing issues related to data quality as the biggest bottleneck in successful AI projects. Big data is so often improperly formatted, lacking metadata, or "dirty," meaning incomplete, incorrect, or inconsistent, that data scientists typically spend 80 percent of their time on cleaning and preparing data to make it usable, leaving them with just 20 percent of their time to focus on actually using data for analysis. This means organizations developing and using AI must devote huge amounts of resources to ensuring they have sufficient amounts of high-quality data so that their AI tools are not useless. As policymakers pursue national strategies to increase their competitiveness in AI, they should recognize that any country that wants to lead in AI must also lead in data quality.