Lifeboat Foundation

Microsoft researchers propose an approach to training AI that uses smiles as a reward signal. They say it achieves superior efficiency.

So, what can businesses do to address this? A big part of the answer lies in emerging technologies such as artificial intelligence (AI) and automation, which will drive new ways of securing the cloud in 2020 and beyond.

That might explain things…

There may soon be serious financial and legal ramifications to the proliferation of deepfake technology. The Wall Street Journal reported last week that a UK energy company’s chief executive was tricked into wiring €200,000 to a Hungarian supplier because he believed his boss was instructing him to do so. Instead, it was a thief using deepfake tech.

To start, Volvo’s Vera will ferry goods from a logistics center to a port in Gothenburg, Sweden. But more Veras will eventually mean fewer trucking jobs.

In this age of “big data,” artificial intelligence (AI) has become a valuable ally for scientists. Machine learning algorithms, for instance, are helping biologists make sense of the dizzying number of molecular signals that control how genes function. But as new algorithms are developed to analyze even more data, they also become more complex and more difficult to interpret. Quantitative biologists Justin B. Kinney and Ammar Tareen have a strategy to design advanced machine learning algorithms that are easier for biologists to understand.

The algorithms are a type of artificial neural network (ANN). Inspired by the way neurons connect and branch in the brain, ANNs are the computational foundations for advanced machine learning. And despite their name, ANNs are not exclusively used to study brains.

Biologists, like Tareen and Kinney, use ANNs to analyze data from an experimental method called a “massively parallel reporter assay” (MPRA) which investigates DNA. Using this data, quantitative biologists can make ANNs that predict which molecules control specific genes in a process called gene regulation.

Race on to find proven ways to help people live longer, healthier lives.

In terms of the number and scale of its success stories, the 2010s have a good claim for being the greatest 10 years in the history of artificial intelligence. What were the biggest advances in A.I. over the past decade? Digital Trends takes a trip down recent memory lane.

Sending construction robots into outer space will help pave the way for human exploration, but there are some real challenges that lie ahead.

“As an entrepreneur I like to know the next two or three things I might start a company on. For me it was robotics, bio-hacking, and quantum.”–whurley.