Welcome to the now "annual" Canadian AI Ecosystem Map. What a year it's been. The report also goes to feed the excellent (and searchable!) directory at Canada.ai. The point of creating this map was to emphasize that the strength lies in the Canadian AI Ecosystem, as opposed to just one city's. This year, we've seen ties strengthen, but also some weaknesses exposed.

The MIT Machine Intelligence Community began with a few friends meeting over pizza to discuss landmark papers in machine learning. Three years later, the undergraduate club boasts 500 members, an active Slack channel, and an impressive lineup of student-led reading groups and workshops meant to demystify machine learning and artificial intelligence (AI) generally. This year, MIC and MIT Quest for Intelligence joined forces to advance their common cause of making AI tools accessible to all. Starting last fall, the MIT Quest opened its offices to MIC members and extended access to IBM and Google-donated cloud credits, providing a boost of computing power to students previously limited to running their AI models on desktop machines loaded with extra graphics processors. The MIT Quest and MIC are now collaborating on a host of projects, independently and through MIT's Undergraduate Research Opportunities Program (UROP).

Throughout the past five years, the susceptibility of neural networks to minimal adversarial perturbations has moved from a peculiar phenomenon to a core issue in Deep Learning. Despite much attention, however, progress towards more robust models is significantly impaired by the difficulty of evaluating the robustness of neural network models. Today's methods are either fast but brittle (gradient-based attacks), or they are fairly reliable but slow (score- and decision-based attacks). We here develop a new set of gradient-based adversarial attacks which (a) are more reliable in the face of gradient-masking than other gradient-based attacks, (b) perform better and are more query efficient than current state-of-the-art gradient-based attacks, (c) can be flexibly adapted to a wide range of adversarial criteria and (d) require virtually no hyperparameter tuning. These findings are carefully validated across a diverse set of six different models and hold for L2 and L_infinity in both targeted as well as untargeted scenarios. Implementations will be made available in all major toolboxes (Foolbox, CleverHans and ART). Furthermore, we will soon add additional content and experiments, including L0 and L1 versions of our attack as well as additional comparisons to other L2 and L_infinity attacks. We hope that this class of attacks will make robustness evaluations easier and more reliable, thus contributing to more signal in the search for more robust machine learning models.

In 1863 five members of the Chōshū han in Japan made a secret journey to University College London in the UK to study. At the time of their departure, travel overseas was illegal in Japan, nonetheless all five students made an impact on the University that is commemorated to this day, and returned to establish institutions that augured a new era in their homeland, including the National Mint, the Japanese railways and the first Prime Minister. In the same spirit of international collaborations fostering pioneering innovations, materials and data scientists met at the Japanese Embassy in London on Friday 21st June during the "Season of Culture" to discuss "Global Trends in Research on Data-driven Discovery in Materials Science". The event was the 10th scholarly colloquium organized by the journal Science and Technology of Advanced Materials (STAM). Developments in data present an interesting example in science diplomacy where science and technology may facilitate a diplomatic agenda that in turn serves the interests of science.

AI-enabled malware could soon be the newest weapon in the threat actors' arsenal, a recent report from Malwarebytes warned. Malwarebytes described AI-enabled malware and cyberattacks as threats that utilize machine learning and AI to find vulnerable systems, evade detection from security products and enhance social engineering techniques. While there are currently no examples of AI-enabled malware in the wild, the report said, it "would be better equipped to familiarize itself with its environment before it strikes," according to the report. "We are talking about how AI-enabled malware can be harder to detect," said Adam Kujawa, director of Malwarebytes Labs. "It could deliver more targeted malware, create better spearfishing campaigns, because it's able to collect big data from social media, and [create more convincing] fake news and clickbait."

Star Trek's stories are infused with myriad, complex technologies -- many of which can't easily be explained even by engineers. But what if they break down or learn too much? In the second season of Star Trek: Discovery, a sophisticated computer program known as Control ran amok, bent on fulfilling its mission in a way its human designers never intended. It took over computer systems and eventually starships and space stations. It also hacked into a human-robot hybrid and deployed swarms of nanobots for nefarious purposes.

Artificial intelligence no longer is the "next new thing." AI, machine learning, deep learning and other forms of algorithmic-based, automated processes are now mainstream and on their way to being deeply integrated into a wide range of front office, back office and in-the-field operations. And we certainly have seen a lot of great examples of AI being used to spot potential cybersecurity threats and preventing their infection on an organization. As business leaders, you have given at least some consideration to the notion that AI will completely replace soon your security operations center (SOC). After all, you've probably calculated the money it takes to run your SOC 24/7/365, and what it means when your CISO comes to an executive lunch or the board meeting and explains that we need more resources – i.e., people, technology and money – to fight new and more security threats.

TECHNOLOGY has advanced so much that one can now produce or alter audio or video content to show or present something that actually didn't happen. With deepfake technology (which combines "deep learning" with "fake"), one can, for example, superimpose someone's face over another person's to create a video to support his or her own agenda. The video is then circulated online, with disastrous consequences on the victim if the purpose is vile in nature, such as the sex video that is currently doing its rounds on social media in Malaysia. Deepfake is artificial intelligence (AI) at work, and there is little you can do to prevent it from happening to you, as highly-paid Hollywood actress Scarlett Johansson lamented. The subject of a fake porn video, she told the Washington Post (Dec 31, 2018): "The truth is, there is no difference between someone hacking my account or someone hacking the person standing behind me on line at the grocery store's account. It just depends on whether or not someone has the desire to target you. "Obviously, if a person has more resources, they may employ various forces to build a bigger wall around their digital identity.

So the robots are coming for our jobs, are they? Goes back to Elizabeth I and the stocking frame, if my memory serves me right. Machines have been taking our jobs forever. But economists, despite their reputation as practitioners of the "dismal science", have always been upbeat about that. Sure, machines destroy jobs, they say.

WASHINGTON - In recent weeks, U.S. President Donald Trump has drawn the ire of security hawks in Congress for suggesting he could trade away his blacklisting of Huawei Technologies Co. to secure a trade deal with China. On Saturday he took a big step toward doing just that, signaling that he cares more about selling U.S. products to China than embarking on a clash of civilizations advocated by some top advisers. In the long run, those business instincts may say more about where U.S.-China ties are headed than his deal with Chinese President Xi Jinping to suspend any new tariffs and resume trade talks. Trump's move last month to cut off supplies to Huawei, one of China's most celebrated companies, marked a major escalation in his confrontation with Beijing after he raised tariffs following a collapse in trade talks. Putting the company on a Commerce Department "entity list" normally reserved for rogue regimes and affiliated businesses was seen as the latest sign the U.S. and China were tumbling into a new technological cold war.