AI magic is here to save the world, making us giddy with excitement and terrifying us at the same time. However, AI is still mostly unknown, and figuring out exactly how it will work in the design world is pretty much like trying to figure out how many angels can dance on the head of a pin. AI (artificial intelligence) has become an over-hyped buzzword across many industries and the design world is no exception. There are ongoing conversations between designers and developers around the future impact of AI, Machine Learning, Deep Learning… VR, AR, and MR (virtual, augmented, and mixed realities), and how our jobs may be changing. So, what does design bring to the conversation?

Researchers from Google AI (formerly Google Research) and Toyota Technological Institute of Chicago have created ALBERT, an AI model that achieves state-of-the-art results that exceed human performance. ALBERT now claims first place on major NLP performance leaderboards for benchmarks like GLUE and SQuAD 2.0, and high RACE performance score. On the Stanford Question Answering Dataset benchmark (SQUAD), ALBERT achieves a score of 92.2, on General Language Understanding Evaluation (GLUE) benchmark, ALBERT achieves a score of 89.4, and on ReAding Comprehension from English Examinations (RACE) benchmark, ALBERT gets a score of 89.4%. ALBERT is a version of Transformer-based BERT that "uses parameter reduction techniques to lower memory consumption and increase the training speed of BERT," according to a paper published on OpenReview.net The paper was published alongside other papers being considered for publication as part of the International Conference of Learning Representations, which will take place in April 2020 in Addis Ababa, Ethiopia.

Of course, we live in a data-driven world. From your handheld computer, called a smartphone, to the supercomputer on your desktop, data is everywhere. The social media that has become the go-to source of communication and interaction depends on input--data--to provide that communication. For decades, data on design, engineering, modeling, and other aspects of the construction process has been created and stored on computers. CAD (computer-aided design), CAE (computer-aided engineering), and BIM (building information modeling) are all common acronyms in the business of building.

Activision has released a mobile version of the popular Call of Duty video game that is free-to-play on Android and iOS devices. 'Call of Duty' is firing a salvo at'Fortnite,' with a new, mobile video game that includes a battle royale mode for up to 100 players. "Call of Duty: Mobile," out Tuesday for Android and iOS devices, is a free-to-play game featuring a variety of maps, weapons, characters and play modes from the multibillion-dollar "Call of Duty: Black Ops" and "Modern Warfare" video game franchises. Other popular multiplayer modes in the game include Team Deathmatch, Search and Destroy, and Domination. Popular maps from the game franchise that will be included are Nuketown, Crash, Hijacked and more.

It is one of the most forgotten and painful chores – taking out the trash. Technology has come to the rescue with a smart garbage can that can be pre-programmed with a specific schedule and park itself curbside for pick up. Paired with a companion app, SmartCan rolls out to a docking station by the road and autonomously returns once the garbage has been picked up. Taking out the trash has become one of the most dreaded chores. One must make their way outside in rain, sun, sleet or snow, and then haul a heavy trash can to the curb for pick up.

AI is a continuum of technology innovation, says Yonatan Hagos, chief product officer at Beyond Limits. If you go beyond the fiction and beyond the hype, you see that the evolution of AI has been prompted by the quest for better answers to business problems. This drive forward is the foundation of the powerful AI solutions we see in action today -- and should also be the catalyst for companies to push beyond the limits of traditional AI. The ultimate goal of AI was always to find out if we could get machines to think like a human, with the understanding that machines should be able handle the analysis of huge data sets far more quickly and effectively than humans ever could. Today, forms of AI have proven to be effective as powerful neural networks and deep learning tools took over the heavy lifting for data processing.

This article was originally published on CMSWire by Sean Zinsmeister, Vice President of Product Marketing at Infer. The buzz surrounding machine learning and artificial intelligence (AI) in the consumer world has rapidly bled over into the enterprise. Much of this hype stems from the new consumer trends that hint at the possibilities of AI, such as self-driving cars and intelligent voice-first products like Amazon's Alexa and Apple's Siri. At the same time, mainstream cloud adoption and ever-increasing computing power in the form of new solutions like Google Spanner are accelerating the development, accuracy and speed of AI's underlying foundations, from data availability and spam detection, to machine learning, predictive analytics and natural language processing. So it should come as no surprise that sales and marketing leaders are questioning what all this means for their departments and companies.

A US firm is flogging facial-expression software to analyse job candidates' performance in video interviews and make initial selections for companies including Unilever. The Marmite and Persil maker has previously used facial recognition software to analyse shoppers' reactions to in-store displays of products, and is now turning to algorythms to help in choosing its workforce. Hirevue software claims to analyse facial expressions and language to select the best candidates. Job seekers sit in front of a laptop or mobile phone and complete an automated video interview. This is analysed and compared against results from candidates who have already proved to be good at the job, according to The Telegraph.

Editor's Note: This article was submitted in response to the call for ideas issued by the co-chairs of the National Security Commission on Artificial Intelligence, Eric Schmidt and Robert Work. It addresses the second part of the second question on AI expertise and skill sets for the national security workforce. The race to harness artificial intelligence for military dominance is on -- and China might win. Whoever wins the AI race will secure critical technological advantages that allow them to shape global politics. The United States brings considerable strengths -- an unparalleled university system, a culture of innovation, and the only military that bestrides the globe -- to this contest.

The use of Artificial Intelligence in healthcare has been a reoccuring topic in conversation in the popular media and in academia. Often discussed in terms of its revolutionary potential. This article in Nature does a great job of summing up some of the tricky nuances showing how the use of such datacentric systems can backfire when it comes to providing suitable healthcare to marginalized populations. Thought it might be of interest, would also love to hear what examples of AI use in health care exist in Europe and how these have been assessed given the concerns highlighted in this article.