The maritime and scientific communities have set themselves the ambitious target of 2030 to map Earth's entire ocean floor. You can argue about the numbers but it's in the region of 80% of the global seafloor that's either completely unknown or has had no modern measurement applied to it. The international GEBCO 2030 project was set up to close the data gap and has announced a number of initiatives to get it done. What's clear, however, is that much of this work will have to leverage new technologies or at the very least max the existing ones. Which makes the news from Ocean Infinity - that it's creating a fleet of ocean-going robots - all the more interesting. US-based OI is a relatively new exploration and survey company.

Doctors have used a robot to perform extremely delicate surgical operations on breast cancer patients in the first human trial of the technology. Eight women had the robot-assisted procedure at Maastricht University Medical Center, in the Netherlands, to alleviate a common complication of breast cancer surgery. The robot helped a specialist surgeon divert thread-like lymphatic vessels, as narrow as 0.3mm, around scar tissue in the patients' armpits, and connect them to nearby blood vessels. The operation, which requires immense care and precision, is offered to some breast cancer patients to reduce swelling in the arms that builds up when the lymphatic system cannot drain properly. Because the vessels are so small, surgeons need exceptionally steady hands to perform the operation well.

Until pretty recently, computers were hopeless at producing sentences that actually made sense. But the field of natural-language processing (NLP) has taken huge strides, and machines can now generate convincing passages with the push of a button. These advances have been driven by deep-learning techniques, which pick out statistical patterns in word usage and argument structure from vast troves of text. But a new paper from the Allen Institute of Artificial Intelligence calls attention to something still missing: machines don't really understand what they're writing (or reading). This is a fundamental challenge in the grand pursuit of generalizable AI--but beyond academia, it's relevant for consumers, too. Chatbots and voice assistants built on state-of-the-art natural-language models, for example, have become the interface for many financial institutions, health-care providers, and government agencies.

What is artificial intelligence and why can it be dangerous? As learning algorithms can process data sets with precision and speed beyond human capacity, artificial intelligence (AI) applications have become increasingly common in finance, healthcare, education, the legal system and beyond. However, reliance on AI also carries risks, especially where decisions are made without human oversight. Machine learning relies on pattern-recognition within datasets. Problems arise when the available data reflects societal bias.

For video game fans, the concept of artificial intelligence (AI) is just as familiar as extra lives, respawns, and end bosses. Gamers have spent decades going up against computer-controlled opponents, whether a Pong paddle trying to prevent them from scoring a point or Bowser trying to stop Mario from rescuing Princess Peach. But recent developments in AI are pushing the gaming field even further, as researchers develop algorithms that can help fans make exciting new titles on their own. The history of AI and that of gaming are inexorably intertwined. Early AI researchers saw games like chess as markers of intelligence, and thus perfect testing grounds for their work.

It can also reflect human flaws and inconsistencies, including 180 known types of bias. Biased AI is everywhere, and like humans, it can discriminate against gender, race, age, disability and ideology. AI bias has enormous potential to negatively affect women, minorities, the disabled, the elderly and other groups. Computer vision has more issues with false-positive facial identification for women and people of color, according to research by MIT and Stanford University. A recent ACLU experiment discovered that nearly 17 percent of professional athlete photos were falsely matched to mugshots in an arrest database.

AI is the method by which self-driving cars perceive joggers, cyclists, traffic lights, road signs, trees, shrubs, and more, and it informs the way in which they choose to behave when encountered with those signals. The vehicles in Waymo's fleet aren't an exception to the rule -- they tap AI to make real-time driving decisions, in part by matching obstacles spotted by their onboard sensors to the billions of objects in the Alphabet company's database. Large data sets are invaluable in the autonomous driving domain because they enable the underpinning AI to self-improve. But it's been historically tough for engineers to surface samples within those sets without investing time and manual effort. That's why Waymo developed what it calls Content Search, which draws on tech similar to that which powers Google Photos and Google Image Search to let data scientists quickly locate almost any object in Waymo's driving history and logs.

With the coronavirus growing more deadly in China, artificial intelligence researchers are applying machine-learning techniques to social media, web, and other data for subtle signs that the disease may be spreading elsewhere. The new virus emerged in Wuhan, China, in December, triggering a global health emergency. It remains uncertain how deadly or contagious the virus is, and how widely it might have already spread. Infections and deaths continue to rise. More than 31,000 people have now contracted the disease in China, and 630 people have died, according to figures released by authorities there Friday.

Plenty of people have a pet project that they are drawn to or consider themselves particularly good at. As the leader of the data science department at Trupanion in Seattle, David Jaw's projects are actually around pets. Jaw, GeekWire's latest Geek of the Week, uses artificial intelligence and machine learning to help automate medical insurance claims for pets, streamlining the process and removing the worry about what's covered and what's not. Born and raised in a suburb near Toronto, Jaw's family moved to Albuquerque, N.M., when he was 13 years old. He stayed there through college, where he studied mechanical engineering, pursuing a childhood dream of designing airplanes and spaceships.

A new drug created with artificial intelligence (AI) to treat patients with obsessive-compulsive disorder (OCD) will be entering human clinical trials this March – a first for AI. It has cut the drug development time from four and a half years to just 12 months, accelerating the time it typically takes to develop drugs for clinical trials. Exscientia, an Oxford-based AI start-up, collaborated with the Japanese pharmaceutical firm Sumitomo Dainippon Pharma to develop the OCD drug. It has been difficult to invent new drugs with AI that are safe and effective for humans to use. But, it has been successful with machine learning algorithms to look through data and identify which patients can benefit the most from existing medicines. AI has also been used beyond medical approaches, and has also been used to track the coronavirus outbreak and to tackle America's opioid crisis.