A number of researchers due to attend a prestigious conference on artificial intelligence in Canada next week have been unable to obtain visas in time, leading some executives to question the government's stated goal of becoming a world-leading destination for academics and companies developing the technology. It's unclear how many people have been affected by visa issues, but at least a dozen researchers circulated their stories on social media about having visas denied or applications held up. Timnit Gebru, a Google AI researcher and a founder of the group Black in AI that's holding a workshop at the event, said on Twitter that almost half of the 60-some academics it had asked to attend the workshop had visa applications turned down. "It's Africans living everywhere that are getting denied," she said. Several prominent AI researchers complained of the situation on Twitter in the hopes of getting the Canadian government to take action.

Choose "I don't think so." or "Yes, I think so.". In many ways, we are on the brink of this new mobility tech becoming mainstream. Just this month, Waymo was granted the go-ahead to test fully driverless cars in California. In the US, twenty-nine states have already enacted legislation related to autonomous vehicles. In places like Arizona, the cars are already on roads. In Florida, children are being driven to school in autonomous school buses.

Thanksgiving and Black Friday may be over, but Cyber Monday is here, and it's one of your last chances to grab several Amazon devices, plus lots of other electronics, kitchen appliances, and even fashion over at Amazon. We've gone and sniffed out some of the best Cyber Monday deals on Amazon you can find, including Instant Pots, Fitbits, robot vacuums and more, below. Slate has relationships with various online retailers. If you buy something through our links, Slate may earn an affiliate commission. We update links when possible, but note that deals can expire and all prices are subject to change.

In recent years, Elon Musk has become one of the most vocal critics of artificial intelligence, issuing numerous warnings about the threat that powerful machines pose to the future of mankind. Now the 47-year-old billionaire inventor and Tesla chief executive has unveiled a potential way for the meager human brain to compete with a superior force that Musk has compared to "an immortal dictator" and "the devil." During an interview with Axios co-founders Jim VandeHei and Mike Allen that aired Sunday, Musk said humans must merge with artificial intelligence, creating a "symbiosis" that leads to "a democratization of intelligence." "Essentially, how do we ensure that the future constitutes the sum of the will of humanity?" "And so, if we have billions of people with the high-bandwidth link to the AI extension of themselves, it would actually make everyone hyper-smart."

Perhaps even moreso than even big data or blockchain, AI is fast becoming the buzzword on everyone's lips. Machine learning has been a promising field for years, but with the astonishing success of deep learning techniques, we're rapidly being propelled into an automated future. But can AI withstand the hype? Ahead of Data Natives 2018 on the 22nd & 23rd November, I talked to four key speakers in the AI space about the future of AI, and what transformations AI will (and won't!) bring about. If you have enough data, an AI can learn anything.

Much the way that a master key can unlock every door in a building, these "DeepMasterPrints" use artificial intelligence to match a large number of prints stored in fingerprint databases and could thus theoretically unlock a large number of devices. The research team was headed by NYU Tandon Associate Professor of Computer Science and Engineering Julian Togelius and doctoral student Philip Bontrager, the lead author of the paper, who presented it at the IEEE International Conference of Biometrics: Theory, Applications and Systems, where it won the Best Paper Award. The work builds on earlier research led by Nasir Memon, professor of computer science and engineering and associate dean for online learning at NYU Tandon. Memon, who coined the term "MasterPrint," described how fingerprint-based systems use partial fingerprints, rather than full ones, to confirm identity. Devices typically allow users to enroll several different finger images, and a match for any saved partial print is enough to confirm identity.

Episode Summary: Some businesses are going to require a sea change in the way that their computation works and the kinds of computing power that they're leveraging to do what they need to do with artificial intelligence. Others might not need an upgrade in hardware in the near term to do what they want to do with AI. That's the question that we decided to ask today of Per Nyberg, Vice President of Market Development, Artificial Intelligence and Cloud at Cray. Cray is known for the Cray-1 supercomputer, built back in 1975. Cray continues to work on hardware and has an entire division now dedicated to artificial intelligence hardware.

That could be the setup for a very bad joke -- or a tremendously fascinating conversation. Fortunately for us, it was the latter. On a blustery evening in late September, in a private room at a bar near Times Square, the magazine gathered five brilliant scientists and thinkers around a table for a three-hour dinner. In the (edited) transcript below -- moderated by Mark Jannot, a story editor at the magazine and a former editor in chief of Popular Science -- you can see what they had to say about the future of medicine, health care and humanity. MARK JANNOT: For years, many pregnant women have undergone amniocentesis to test for rare metabolic disorders and other fetal issues. And couples who use in vitro fertilization can screen the embryos for genetic abnormalities. What sorts of advances in genetic screening and manipulation are coming, and where do you see that taking us? CATHERINE MOHR: When I was pregnant with my daughter, my husband and I were joking, "Well, if she gets the best of both of us, she'll be a superhero, and if she gets the worst of both of us, she's not going to make it out of first grade." And so we were rolling the genetic dice, which you do when you choose to have a child. It's not totally random, of course; there's all kinds of great things about your mate -- that's why you chose them -- and hopefully there's some pretty good things about you, too. But the temptation to engineer what you think of as the best combination, as we become more capable of doing it, I think it's going to be irresistible for a lot of people. You're investing so much of your life into this little being, and you're going to love this child, and you want to give them every advantage in life. We are already screening for diseases to avoid passing on our "bad" genes, but this same technology will let us start screening for our "best" genes -- the ones we really want to pass on. As screening becomes cheaper, easier and more reliable, and more people are using assisted-reproductive technologies, I see us, as a society, sliding down that slippery slope pretty far, one couple at a time, each trying to do what's best for the child they are hoping to bring into the world.

Most often, chat-bots are built to solve the purpose of a search engine or a human assistant: Their primary goal is to provide information to the user or help them complete a task. However, these chat-bots are incapable of responding to unscripted queries like "Hi, what's up", "What's your favourite food". Human evaluation judgments show that 4 humans come to a consensus on the intent of a given query which is from chat domain only 77% of the time, thus making it evident how non-trivial this task is. In our work, we show why it is difficult to break the chitchat space into clearly defined intents. We propose a system to handle this task in chat-bots, keeping in mind scalability, interpretability, appropriateness, trustworthiness, relevance and coverage. Our work introduces a pipeline for query understanding in chitchat using hierarchical intents as well as a way to use seq-seq auto-generation models in professional bots. We explore an interpretable model for chat domain detection and also show how various components such as adult/offensive classification, grammars/regex patterns, curated personality based responses, generic guided evasive responses and response generation models can be combined in a scalable way to solve this problem.

What do you think is the significant change in the IT Industry? Well, it definitely is Automation, Robotics, Artificial Intelligence and more! People fear – Will RPA replace people. The truth is Humans have an irreplaceable role in business, operations, decision making, especially when it comes creation, collaboration and interaction at work. Automation principally saves valuable time on monotonous jobs, which are diverted to the virtual workforce, to have focused on the value-added work, only possible by Humans.