The problem of finding the sparsest vector (direction) in a low dimensional subspace can be considered as a homogeneous variant of the sparse recovery problem, which finds applications in robust subspace recovery, dictionary learning, sparse blind deconvolution, and many other problems in signal processing and machine learning. However, in contrast to the classical sparse recovery problem, the most natural formulation for finding the sparsest vector in a subspace is usually nonconvex. In this paper, we overview recent advances on global nonconvex optimization theory for solving this problem, ranging from geometric analysis of its optimization landscapes, to efficient optimization algorithms for solving the associated nonconvex optimization problem, to applications in machine intelligence, representation learning, and imaging sciences. Finally, we conclude this review by pointing out several interesting open problems for future research.

NAIROBI (Thomson Reuters Foundation) - Countries are rapidly developing "killer robots" - machines with artificial intelligence (AI) that independently kill - but are moving at a snail's pace on agreeing global rules over their use in future wars, warn technology and human rights experts. From drones and missiles to tanks and submarines, semi-autonomous weapons systems have been used for decades to eliminate targets in modern day warfare - but they all have human supervision. Nations such as the United States, Russia and Israel are now investing in developing lethal autonomous weapons systems (LAWS) which can identify, target, and kill a person all on their own - but to date there are no international laws governing their use. "Some kind of human control is necessary ... Only humans can make context-specific judgements of distinction, proportionality and precautions in combat," said Peter Maurer, President of the International Committee of the Red Cross (ICRC).

Finnish technology firm Reaktor and the University of Helsinki joined forces to educate people on AI for free. The institutions combined to develop an online course to teach the basics of AI to anyone interested in the technology. Reaktor and the University also challenged organizations to train their staff in AI, so far over 200 organisations have pledged to do so – including banks, telecoms, and healthcare organizations. Almost 90 000 students have signed up for the course since it began in May. While popular with Finns, the course is already seeing strong demand globally, attracting students from over 80 different countries.

In the 10 days leading up to Christmas this year, I searched on Instagram for three of my exes, an acquaintance I met on a trip to Cuba four years ago, an account dedicated to astrology memes, a past roommate, my own dog's account (@lucythetherapypup), my best friend's sweater-wearing poodle, a famous Pomeranian who lives in New York, a bird named Parfait I recently met at a San Francisco market, 10 contestants of the reality TV show Love Island, and the hashtag #wienerdog. I know all of this because Instagram told me. That's because this month, I submitted a data request under California's new privacy law to see just how much information the company has on me. What I got was a wide-ranging look at how my life has changed in the last 10 years since I first logged on to Instagram, and a window into what the company is willing to share about what it knows about me. Under the California Consumer Privacy Act, I have the right to demand companies disclose "any personal information" they collect about me and request a copy of that information.

Find here a listing of the latest industry news in genomics, genetics, precision medicine, and beyond. Updates are provided on a monthly basis. Sign-Up for our newsletter and never miss out on the latest news and updates. As 2019 came to an end, Veritas Genetics struggled to get funding due to concerns it had previously taken money from China. It was forced to cease US operations and is in talks with potential buyers. The GenomeAsia 100K Project announced its pilot phase with hopes to tackle the underrepresentation of non-Europeans in human genetic studies and enable genetic discoveries across Asia. Veritas Genetics, the start-up that can sequence a human genome for less than $600, ceases US operations and is in talks with potential buyers Veritas Genetics ceases US operations but will continue Veritas Europe and Latin America. It had trouble raising funding due to previous China investments and is looking to be acquired. Illumina loses DNA sequencing patents The European Patent ...

Users expect to see that friendly search box in their applications. They seem to really like it, because it's so simple to use. You don't need a user manual to figure out search. In fact, if your application doesn't have search, you'll be pelted with negative reviews. No wonder you see search in so many applications. It's very difficult to implement. We all know it's more than just simple text matching. Those of us with database backgrounds know that searching for "prefix*" is a lot easier than searching for "*suffix". And users want to do all sorts of weird searches like "*run*", which should match ran, or shrunken or brunt, or--you get the idea. Quick search results and performance are important, as is accuracy and ranking.

The discriminatory biases of the algorithms, the invasion of privacy, the risks of facial recognition and the regulation of human-machine relations are challenges that AI needs to face. However, the interests of governments and large companies often prevail over good practices. Artificial intelligence (AI) is no longer a science fiction thing, it is everywhere. Your bank uses it to know if it is going to give you a credit or not and the ads you see on your social networks come out of a classification carried out by an algorithm, which has microsegmented and'decided' if it shows you offers of wrinkle creams or high-end cars. Facial recognition systems, which use airports and security forces, are also based on this technology.

Most companies report measurable benefits from AI where it has been deployed; however, much work remains to scale impact, manage risks, and retrain the workforce. A group of high performers shows the way, as explained in this article by Arif Cam, Michael Chui and Bryce Hall of McKinsey. Adoption of artificial intelligence (AI) continues to increase, and the technology is generating returns. The findings of the latest McKinsey Global Survey on the subject show a nearly 25 percent year-over-year increase in the use of AI2 in standard business processes, with a sizable jump from the past year in companies using AI across multiple areas of their business. A majority of executives whose companies have adopted AI report that it has provided an uptick in revenue in the business areas where it is used, and 44 percent say AI has reduced costs.

Through play children (and adults) learn how to use their imaginations, to experiment with different ways of doing things. This might seem like it has relevance only for their self-development, but it's also through imagination and experimentation that the human race as a collective arrives at the solutions to its problems. As such, it's vital that we encourage children and people more generally to use their imaginations and to experiment, and it's to this end that LEGO, of all things, has an important role to play in nurturing the next generation of engineers, scientists and problem solvers. And we're not just talking about informal play with LEGO here, since one organization in particular has taken it upon itself to incorporate the famous Danish toy in competitions and workshops, all of which aim to instil a love for science and engineering in children. This organization is FIRST (For Inspiration and Recognition of Science and Technology), a not-for-profit public charity based in New Hampshire that works to inspire young people to pursue careers and education in STEM (science, technology, engineering and mathematics) subjects. Beginning in 1999, it partnered with the LEGO Group itself to launch the FIRST LEGO League, tapping into the LEGO brand to bring children to science.

New York, January 07, 2020: Based on Deployment, the global Enterprise Artificial Intelligence market is segmented in Cloud and On-Premises. The report also bifurcates the global Enterprise Artificial Intelligence market based on Solution in Business Intelligence, Customer Management, Sales & Marketing, Finance & Operations, Digital Commerce, and Others. The global Enterprise Artificial Intelligence market is segregated on the basis of Deployment as Cloud and On-Premises. Based on Service the global Enterprise Artificial Intelligence market is segmented in Professional Service and Managed Service. Based on End User the global Enterprise Artificial Intelligence market is segmented in Automotive, Media and Entertainment, Healthcare, Retail, IT & Telecommunication, BFSI, and Aerospace.