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Top Automation Trends to Watch in 2021


Yes, automation has made its presence felt but with the pandemic that shook the entire world, organizations are now forced to rethink as to how will they proceed further. Even though the vaccine rollout promises returning back to normalcy, it definitely doesn't mean that we will return to business as usual. All this has made organizations look forward to exploring options in digital transformation, automation and artificial intelligence like never before. Some areas can surely see these being implemented in the coming days considering the fact how swiftly the pandemic forced us to change the way we look at life. The pandemic led to a complete lockdown at least for a few days in a majority of countries.

MarqVision enables real-time counterfeit goods detection with technology.


When you found an excellent luxury product at an affordable price from an eCommerce platform, what makes you hesitate? Most of the customers hesitate if the product is a fraud or counterfeit one. "The counterfeit market has been on the rise for quite some time and, according to a Forbes study, sales from counterfeit and pirated goods total around $1.7 trillion every year -- more than drugs and human trafficking." MarqVision, A South Korean startup based in Boston and Seoul, was accepted by Y Combinator as YC 21 this January. The company provides an AI-powered platform to protect brands from counterfeits and an AI-enhanced video verification system for online retailers.

Why Python Is Best for Machine Learning - UrIoTNews


Today, most companies are using Python for AI and Machine Learning. With predictive analytics and pattern recognition becoming more popular than ever, Python development services are a priority for high-scale enterprises and startups. Python developers are in high-demand -- mostly because of what can be achieved with the language. AI programming languages need to be powerful, scalable, and readable. Python code delivers on all three.

China eyes next-generation chip technology to take on global rivals

The Japan Times

In just two decades, China sent people into space, built its own aircraft carrier and developed a stealth fighter jet. Now the world's youngest superpower is setting out to prove its capabilities once more -- this time in semiconductors. At stake is nothing less than the future of the world's No. 2 economy. Beijing's blueprint for chip supremacy is enshrined in a five-year economic vision, set to be unveiled during a summit of top leaders in the capital this week. It's a multi-layered strategy both pragmatic and ambitious in scope, embracing aspirations to replace pivotal U.S. suppliers -- and fend off Washington -- while molding homegrown champions in emergent technologies.

Machine Learning Can Help The Insurance Industry Throughout The Process Lifecycle


Insurance works with large amounts of data, about many individuals, many instances requiring insurance, and many factors involved in solving the claims. To add to the complexity, not all insurance is alike. Life insurance and automobile insurance are not (as far as I know) the same thing. There are many similar processes, but data and numerous flows can be different. Machine learning (ML) is being applied to multiple aspects of insurance practice.

[D] Simple Questions Thread December 20, 2020


Hi, I'm working in a museum, currently trying to optically characterize a big historic lens. Unfortunately, it is mounted in a device which can't really be taken apart (issues of conservation), so conventional methods are rather hard to do. I've been loosely following the advances in neural network based approaches ("Two minute papers" kinda stuff) and was wondering if anyone has already realized a solution to my problem using machine learning or similar techniques. That is: Print out a defined optical pattern (like a QR code), "wave" it on one side of the lens and record the image with a camera on the other to get a 3D model of the lens in the end. In my head, it should be possible to train a network using conventional light simulation of randomly generated glass bodies.

Microsoft brings RPA to Windows 10 with new Power Platform products


Microsoft announced AI-focused Power Platform products at its Microsoft Ignite 2021 conference, which kicked off in earnest today. Among the highlights is Power Automate Desktop for Windows 10 users, a robotic process automation service (RPA) that automates tasks within Windows across various apps. New Power Virtual Agents features were also unveiled. RPA -- technology that automates monotonous, repetitive chores traditionally performed by human workers -- is big business. Forrester estimates that RPA and other AI subfields created jobs for 40% of companies in 2019 and that a tenth of startups now employ more digital workers than human ones.

How will Singapore ensure responsible AI use?


Since 2019, government-sponsored initiatives around AI have proliferated across Asia Pacific. Such initiatives include the setting up of cross-domain AI ethics councils, guidelines and frameworks for the responsible use of AI, and other initiatives such as financial and technology support. The majority of these initiatives builds on the country's respective data privacy and protection acts. This is a clear sign that governments see the need to expand existing regulations when it comes to leveraging AI as a key driver for digital economies. All initiatives to date are voluntary in nature, but there are indications already that existing data privacy and protection laws will be updated and expanded to include AI.

Regression Vs Classification In Machine Learning


Regression and classification are many times confusing to many beginners in the field of Machine learning. Eventually, this will make it impossible for them to adopt the correct methodologies for solving problems with prediction. Regression and classification are both types of supervised machine learning algorithms, where a model is trained along with correctly labeled data according to the current model. Let's understand each algorithm first. Regression algorithms estimate a continuous value based on the input variables.

AI ethics research conference suspends Google sponsorship


The ACM Conference for Fairness, Accountability, and Transparency (FAccT) has decided to suspend its sponsorship relationship with Google, conference sponsorship co-chair and Boise State University assistant professor Michael Ekstrand confirmed today. The organizers of the AI ethics research conference came to this decision a little over a week after Google fired Ethical AI lead Margaret Mitchell and three months after the firing of Ethical AI co-lead Timnit Gebru. Google has subsequently reorganized about 100 engineers across 10 teams, including placing Ethical AI under the leadership of Google VP Marian Croak. "FAccT is guided by a Strategic Plan, and the conference by-laws charge the Sponsorship Chairs, in collaboration with the Executive Committee, with developing a sponsorship portfolio that aligns with that plan," Ekstrand told VentureBeat in an email. "The Executive Committee made the decision that having Google as a sponsor for the 2021 conference would not be in the best interests of the community and impede the Strategic Plan. We will be revising the sponsorship policy for next year's conference."