Data is a new reality of life and tech industries in Silicon Valley and across the globe know it. Every small and big tech giant is working to capture the attention of customers. Artificial intelligence (AI) is indispensable in bringing a true digital revolution to turn history upside down. Nvidia is also trying to maintain its clout in the global computing industry through frequent bold steps. It will sell a new AI chip later this year to enhance data processing and AI modeling.

Most image-recognition systems are trained using large databases that contain millions of photos of everyday objects, from snakes to shakes to shoes. With repeated exposure, AIs learn to tell one type of object from another. Now researchers in Japan have shown that AIs can start learning to recognize everyday objects by being trained on computer-generated fractals instead. It's a weird idea but it could be a big deal. Generating training data automatically is an exciting trend in machine learning.

Humans are instinctively tribal creatures. When we observe the interactions of people around us, we can intuitively infer whom we should get along with and whom we shouldn't. This might sound like a negative instinct, but it's actually what makes teamwork possible. Researchers at MIT believe this skill may be an important prerequisite for creating sociable AI systems that can cooperate with us in our day-to-day lives. Game-playing AI agents also require an understanding of the relationship landscape to know whom to cooperate and compete with.

"Andrew Ingram" is a digital assistant that scans your emails, gives scheduling ideas for the meetings and appointments you discuss with your coworkers, sets up tasks, and sends invites to the relevant parties with very little assistance. It uses the advanced artificial-intelligence capabilities of X.ai, a New York–based startup that specializes in developing AI assistants. The problems it solves can save a lot of time and frustration for people (like me) who have a messy schedule. But according to a Wired story published in May, the intelligence behind Andrew Ingram is not totally artificial. It's backed by a group of 40 Filipinos in a highly secured building on the outskirts of Manila who monitor the AI's behavior and take over whenever the assistant runs into a case it can't handle.

To put that into perspective, experts at OpenAI recently developed Dactyl, a robotic hand that could handle objects. This is a task that any human child learns to perform subconsciously at an early age. But it took Dactyl 6,144 CPUs and 8 GPUs and about one hundred years' worth of experience to develop the same skills. While it is a fascinating achievement, it also highlights the stark differences between narrow AI and the way the human brain works.

Two miniature cars are zooming around a loop of track in a new robotics arena. The other is controlled by artificial intelligence – and it's kicking my ass. From August 2017, the University of Essex's robotic games laboratory will pit AI systems against each other in robot challenges, starting with these remote-controlled cars. The AI I'm racing has been honed to complete the track in super-quick time, but the real competitions won't be so straightforward. The rules will change between heats: in one, the cars' brakes might be disabled, in another, obstacles could be added to the track.