Companies have rushed to embrace deep learning's potential in their efforts to automate their enterprises, often with an eye towards replacing as much of their human workforce as possible or to scale their operations without expanding their hiring. An endless stream of success stories tout AI's success in replacing an ever-growing array of traditionally automation-resistant jobs, while developers are hard at work finding ways to replace the rest of them. Yet social media platforms give pause to this idea that deep learning is quite at the inflection point of causing a wave of job displacement. Silicon Valley has been at the vanguard of the AI revolution, pioneering the developments that have pushed the field forward. At the same time, those companies have also been hiring vast armies of human workers to augment the limitations of those very same algorithms.

The government has announced its third successive hand-out to the NHS in as many days with a pledge by Boris Johnson of £250m to be invested in artificial intelligence. The prime minister claimed AI would transform care and cut waiting times as he announced the money for a national artificial intelligence lab, to work on digital advances to improve the detection of diseases by predicting who is most likely to get them. However, health experts warned that the NHS had a poor record with technology and any new systems would need "robust evaluation" to ensure they did more good than harm as well as proper implementation with safety standards and training. They also raised concerns over where the money was coming from and whether it was the result of trade-offs elsewhere in the cash-strapped health service. AI is already being used in some hospitals to predict cancer survival and cut the number of missed appointments.

I am so thrilled to welcome you to the absolutely awesome world of data science. It is an interesting subject, sometimes difficult, sometimes a struggle but always hugely rewarding at the end of your work. While data science is not as tough as, say, quantum mechanics, it is not high-school algebra either. It requires knowledge of Statistics, some Mathematics (Linear Algebra, Multivariable Calculus, Vector Algebra, and of course Discrete Mathematics), Operations Research (Linear and Non-Linear Optimization and some more topics including Markov Processes), Python, R, Tableau, and basic analytical and logical programming skills. If you are studying the Data Science course at Dimensionless Technologies, you are in the right place.

It was not a surprise to see Donald Trump and a cabal of other Republican politicians seeking to implicate video games in the US's latest mass shootings. The idea that young men can be driven to kill by Doom, Call of Duty or Fortnite is a seductive one: it's simple, it ties in with fears that older voters harbour about digital culture and screen time, and it conveniently draws attention away from more complex societal concerns such as poverty, neglect, easy access to deadly firearms and a violently confrontational political culture. There's just one problem: despite years of research and hundreds of studies, there is no compelling evidence that video game violence causes real-life bloodshed. Every time these claims are made, the industry seems unwilling to analyse or engage with the reasons why games are so often implicated in violent acts. The standard response is blanket outrage and denial – games don't cause real-world violence, they're "apolitical" fun, so we don't have to think about the issue, we don't have to consider how the shooters portray or utilise military violence.

South Wales police are to have a facial recognition app installed on their phones to identify suspects without having to take them to a police station. The force intends to test the app over the next three months with 50 officers using the technology to confirm the names of people of interest who are stopped on routine patrols. The app will allow officers to run a snapshot of a person through a database of suspects called a watchlist, and find potential matches even if the individual gives false or misleading information. The move is the latest sign that police forces in Britain are eager to embrace the controversial technology which has been criticised for infringing privacy and increasing state powers of surveillance. Liberty, the campaign group, called the announcement "chilling", adding that it was "shameful" that South Wales police had chosen to press ahead with handheld facial recognition systems even as it faced a court challenge over the technology.

From picking fruit to carrying out minor surgery, soft robotic hands made from jelly-like plastic are thought by scientists to be the future solution to many human needs. But being gentle and soft enough to avoid damaging fruit or flesh has made the robots prone to damage and left them largely impractical for use in the real world – until now. A European commission-funded project, led by scientists at the Free University of Brussels and the University of Cambridge, aims to create "self-healing" robots that can feel pain, or sense damage, before swiftly patching themselves up without human intervention. The researchers have already successfully developed polymers that can heal themselves by creating new bonds after about 40 minutes. The next step will be to embed sensor fibres in the polymer which can detect where the damage is located.

As data breaches, misuse of personal information and the spread of disinformation erode the public's trust in Silicon Valley, it can be all too easy to become cynical about technology's impact on the world. But there are still plenty of reasons to be optimistic about tech's role in society moving forward. Below, TIME speaks to 10 innovators, founders, investors and even athletes who remain upbeat about technology's influence despite the many challenges facing the industry today. Moustapha Cisse left Senegal a decade ago to study artificial intelligence, and now he believes the technology can change Africa for the better. Cisse, 34, is leading Google's AI research center in Accra, Ghana, the company's first such venture in Africa. "I built my team here around people who are really committed to make a difference in people's lives," Cisse tells TIME. "[They] bring a fresh perspective in the field by looking at the problems that we have in Africa." Growing up, no one would have expected Cisse to be heading up a multi-billion dollar corporation's research initiative.

SoftBank Group Corp. said Wednesday its group net profit in the April-June period jumped more than threefold to a record ¥1.12 trillion ($10.6 billion) from a year earlier -- marking the best quarter for a Japanese firm since 2004 -- boosted by a special profit from selling part of its stake in Chinese e-commerce giant Alibaba Group Holding Ltd. SoftBank Group said its operating profit fell 3.7 percent to ¥688.82 billion in the three months that ended June 30 on sales of ¥2.34 trillion, up 2.8 percent on a consolidated basis. The company logged the largest group net profit on a quarterly basis among 400 major firms listed on bourses operated by Japan Exchange Group Inc. since Nomura Holdings Inc. started compiling such data in 2004. The investment giant said it booked a one-time gain of ¥1.22 trillion in the quarterly period following the completion of the partial sale of the stake in Alibaba. The company's profit was also boosted by gains from investments in technology startups made by its Vision Fund, through which SoftBank made investments in 81 companies as of the end of June. "It is remarkable for us to mark a (group net) profit of more than ¥1 trillion in a quarter for the first time," said Chairman and CEO Masayoshi Son at a news conference in Tokyo.

Former Olympian and personal trainer Julia Russell tries out a pair of new AR swimmers goggles from FORM. One summer weekend, I was granted two-day access to a nearby resort-style fitness facility with a deluxe indoor pool. So I went for a swim – while connected, of course. Before leaving my apartment, I grabbed my iPhone (selfie or it didn't happen), packed a pair of swimming trunks, and headed toward the door before realizing, "I forgot to charge my goggles." FORM, developed by a Vancouver-based startup, is what happens when your typical pair of swim goggles receive a total 2.0 upgrade.

According to a study published in the journal Radiology, when machine learning is combined with common heart scan, it can predict heart attacks and other cardiac events better than traditional risk models. Observing the worldwide data, heart disease is the most common and leading cause of death in both men and women, especially in the United States. Consequently, precision in risk assessment is mandatory for early intervention to say diet, exercise, drugs including cholesterol-lowering statins. In this context, CCTA (Coronary Computed Tomography Arteriography) provides with a highly detailed set of images of the heart vessels and happens to be a refining risk assessment tool. The study lead author Kevin M. Johnson, M.D., CCTA recently investigated a machine learning system which can mine the myriad details in CCTA-obtained images for a better and comprehensive prognostic picture.