Microsoft President Brad Smith took a break from responding to the COVID-19 outbreak Tuesday to praise Washington state's landmark facial recognition regulations. Jay Inslee signed a bill Tuesday that establishes rules specifically governing facial recognition software. Smith called the law an "early and important model" and "a significant breakthrough" in a blog post published Tuesday. Some cities have enacted their own facial recognition rules, but Washington is the first to establish statewide regulations. "This balanced approach ensures that facial recognition can be used as a tool to protect the public, but only in ways that respect fundamental rights and serve the public interest," Smith said.

Deep learning has truly reshuffled things in machine learning field, and specifically in image recognition tasks. In 2012, Alex-net has initiated a (still far from ending) race towards solving, or at least significantly improving, computer vision tasks. Each of these research paths improves training quality (speed, accuracy, sometimes generalization), but it seems that doing more of the same thing may result in some gradual improvements, but not a in significant breakthrough. On the other hand, growing body of work in deep learning shows that there are significant flaws in current methods, especially in terms of generalization, e.g this recent one: generalization failure when objects are rotated: So there seems to be a need of improvements that are a bit more aggressive. Or perhaps expanding the research spectrum to ideas that may be a bit riskier.

Deep learning has truly reshuffled things in machine learning field, and specifically in image recognition tasks. In 2012, Alex-net has initiated a (still far from ending) race towards solving, or at least significantly improving, computer vision tasks. Each of these research paths improves training quality (speed, accuracy, sometimes generalization), but it seems that doing more of the same thing may result in some gradual improvements, but not a in significant breakthrough. On the other hand, growing body of work in deep learning shows that there are significant flaws in current methods, especially in terms of generalization, e.g this recent one: generalization failure when objects are rotated: So there seems to be a need of improvements that are a bit more aggressive. Or perhaps expanding the research spectrum to ideas that may be a bit riskier.

CISCO HAS HAILED its new network, as a "significant breakthrough" thanks to its ability to detect malware in encrypted traffic. The company says that this is'one of the most significant breakthroughs in enterprise networking', and that the new network can anticipate actions, stop security threats and continues to evolve and learn. Rather than manually entering lines of code, Cisco says that IT managers can automate policy to translate their business intent. "By building a more intuitive network, we are creating an intelligent platform with unmatched security for today and for the future that propels businesses forward," said Cisco CEO Chuck Robbins at a launch event this week. AI, in the form of Encrypted Traffic Analytics (ETA), uses Cisco's Talos threat intelligence to detect known attack signatures in all traffic, including encrypted data.