ICON.AI, the smart beauty device maker behind the world's 1st All-in-one Multi-Function Smart Makeup Mirror Device, named as CES 2020 Innovation Awards Honoree for Venus, Smart Makeup Mirror with Alexa Built-in. This press release features multimedia. ICON.AI, the smart beauty device maker behind the world's 1st All-in-one Multi-Function Smart Makeup Mirror Device, named as CES 2020 Innovation Awards Honoree for Venus, Smart Makeup Mirror with Alexa Built-in. ICON.AI reveals the Mirror at the 2020 CES .Venus is an all-in-one, multi-function smart makeup mirror featuring 7″ touchscreen LCD, Alexa built-in (smart display speaker), skin diagnostic/AR makeup function, table mood lamp, LED ring lights for makeup, in addition to the best user experience and user-centered design. Venus is a brand-new innovative beauty device which integrates artificial intelligence with various features/technology for beauty & cosmetic industry and customers.

My eyes were opened to many new opportunities to integrate economics, design thinking, big data and data science (AI / ML / DL) to further my case for a Nobel Prize in Economics (which I'd prefer not to be awarded posthumously). So, while we wait for that call from Stockholm, let's take a look at my 10 favorite 2019 blogs: There are many valuable lessons that data scientists can learn from the movie "Mr. And maybe the biggest challenge for the development of smart, autonomous products is knowing when "good enough" is actually "good enough". When trying to optimize the operations of these smart, autonomous products, one must be prepared to realize that the current path to performance optimization may not actually be the optimal path, and the data science team must be prepared to jettison their existing work and try a different approach that might lead to a better performing analytic model. This is an important lesson for the creation of our AI-induced "smart" products – that there must be constant testing, learning, and maybe even some unlearning and re-starting afresh in order to find the optimal models.

Technology is global, but ideas are local. The same IoT technology is being deployed all over the world, but a small Japanese startup might be who helps us make sense of it all. There is amazing work being done in user experience design, but most designers are operating with the contract of keeping users engaged. This is a fundamental shift from the traditional user-centered and functional design approaches. Today we sit down with Kaz Oki, founder of Mui Lab, and we talk about user design can actually improve our lives and help us disengage. We also talk about the challenges of getting VCs to invest in hardware startups, why Kyoto might be Japan's next innovation hub, and what it takes for a startup to successfully spin out of a Japanese company It's a great discussion, and I think you will really enjoy it. Welcome to Disrupting Japan, straight talk from Japan's most successful entrepreneurs. If you're a fan of Disrupting Japan, you know that I have a strong dislike for attempts to make Japan sound too exotic and this goes in both directions. On one side, we have consultants who claim that Japanese business practices are so unique, arcane, and confusing that the only way westerners can possibly understand them is by paying large sums of money to consultants such as themselves. And on the other side, of course, we have people insisting that foreigners can't really understand Japanese anime without a thorough and nuanced knowledge of Japanese language and history. I mean, there are differences, of course, and those differences should be acknowledged and respected, but whether an idea is coming from Japan or America, or Germany, one true measure of the value of that idea is its universality. The most important achievements might emerge out of cultural biases or sensitivities but they address something universally true, something deeply human. Today, we sit down with Kaz Oki of Mui Lab and we're going to talk about Mui's radical rethinking of how we should interact with computers and the different contexts for that interaction. The Mui itself is a tactile and visual user interface that literally fades into the furniture when you're not using it.

'It's not opening the gates of hell, but it's not a paradise,' Kasparov says about AI. Artificial intelligence learns from us, so we should really fear bad actors, not killer robots. Garry Kasparov was one of the first victims of the AI automation revolution. His loss to IBM's Deep Blue made him the first human chess champion to lose a match to a computer. But Kasparov is not jaded; his book, Deep Thinking, explores how AI can actually help us become more human. The real challenge, Kasparov told me at SXSW in Austin earlier this month, is keeping these tools from the humans who want to use them to do harm. And in that regard, we may already be too late. Dan Costa: After a career playing chess and battling Deep Blue, you've since then become a chess AI expert of sorts.

The Chinese robotics market is growing strong, but not without its own pains. Trade tensions and a global economic slowdown, particularly in automotive manufacturing, have affected demand in the Chinese robotics market. However, interest in supply chain automation and political support of domestic innovation could encourage growth in 2020. This is Part 2 of The Robot Report's Q&A with Georg Stieler, managing director for Asia at international consulting firm STM Stieler. In Part 1, he discussed the state of the robotics market in China, looking at causes for the current slowdown and what types of robots are in demand. Here, Stieler continues his analysis with a look ahead.

Today, doing more with less is a key principle that drives business strategy across many resource-intensive industries. Businesses are looking to get a higher return out of artificial intelligence (AI) and machine learning (ML) than just great insights. They need access to recommendations that help simplify complex decisions around how scarce resources should be allocated, how to schedule tasks, and how to deal with constraints. As Alex Fleischer points out in his blog, a recent Enterprise Strategy Group (ESG) technical validation report cites the need to improve operational efficiency as the overarching theme driving AI and ML interest. To learn more, I sat down with Virginie Grandhaye, offering manager for IBM Decision Optimization.

Well, it is not just end of the year, but end of the decade as well. So, for the last article of 2019, we decided to write about awarded research papers from Neural Information Processing Systems (NeurIPS) conference. Looking at the logo of NeurIPS conference, my wife asked me "What is that? Is that a witchcraft conference?". Close, but no, it is one of the most important machine learning conferences.

As the technological progress codified as Moore's Law slows down, computer scientists are turning to alternative methods of computing, such as superconducting quantum processors to deliver computing gains in the future. Jeffrey Welser, vice president and lab director at IBM Research at Almaden, spoke about quantum computing at the 49th annual Semicon West chip manufacturing show in San Francisco last week. I caught up with him to get his take on quantum computing for the layperson. IBM also displayed a part of its IBM Q System at the show, giving us an idea of how much refrigeration technology has to be built around a current quantum processor to ensure its calculations are accurate. Binary digits -- ones and zeroes -- are the basic components of information in classical computers. Quantum bits, or qubits, are built on a much smaller scale. And qubits can be in a state of 0, 1, or both at any given time.

Donald Knuth is one of the greatest and most impactful computer scientists and mathematicians ever. He is the recipient in 1974 of the Turing Award, considered the Nobel Prize of computing. He is the author of the multi-volume work, the magnum opus, The Art of Computer Programming. He made several key contributions to the rigorous analysis of the computational complexity of algorithms. He popularized asymptotic notation, that we all affectionately know as the big-O notation.

This publication draws on a wide range of expertise to illuminate the year ahead. Even so, all our contributors have one thing in common: they are human. But advances in technology mean it is now possible to ask an artificial intelligence (AI) for its views on the coming year. We asked an AI called GPT-2, created by OpenAI, a research outfit. GPT-2 is an "unsupervised language model" trained using 40 gigabytes of text from the internet.