A fleet of 11 uncrewed vessels will traverse the world's oceans over the next ten years in a bid to map the sea floor. The bottom of the world's oceans remains a mystery, with around 80 per cent either poorly imaged or not visualised at all. Ocean Infinity launched in 2016 and has pledged its support to an international collaboration to try and map every inch of the ocean floor within the next decade. It has also attempted to use its technology to try and locate the missing Malaysian Airlines MH370 flight that tragically went missing with 239 people on board nearly six years ago. It has announced it has bought a fleet of 11 uncrewed vessels will traverse the world's oceans over the next ten years in a bid to map the sea floor Uncrewed Surface Vessels (USV) are the latest technology which open up the possibility for long-term marine missions. They have no humans on board and are controlled by computers via a satellite link and a central computer base.

An AI can predict from people's brainwaves whether an antidepressant is likely to help them. The technique may offer a new approach to prescribing medicines for mental illnesses. "We have a central problem in psychiatry because we characterise diseases by their end point, such as what behaviours they cause," says Amit Etkin at Stanford University in California. "You tell me you're depressed, and I don't know any more than that. I don't really know what's going on in the brain and we prescribe medication on very little information."

There are a variety of tools that can help researchers analyze large volumes of written material. In this post, I'll examine two of these tools: part-of-speech tagging and tone analysis. I'll also show how to use these methods to find patterns in a large set of Facebook posts created by members of Congress. Part-of-speech (POS) tagging is a process that labels each word in a sentence with an algorithm's best guess for the word's part of speech (for example, noun, adjective or verb). This is based on both the definition of each word and the context in which it appears.

All 1,200 employees of insurer Prudential Singapore will be able to learn how to better use data in their daily work through a new online certification programme. More than 170 staff have signed up for the free course in machine learning since it launched on Feb 1, said Prudential yesterday. Machine learning is a branch of artificial intelligence (AI) that focuses on developing computer programmes that can learn from new data so as to perform tasks without needing explicit instructions from humans. Participants will be trained by data scientists from the public and private sectors, and will take scenario-based assessments to show that they can apply what they have learnt. The 30-hour course is called Machine Learning for Humans and follows a foundational course called AI in Finance, which was taken by over 200 Prudential staff last year.

It's a cloudy day in early October and I'm circling my rented Jeep Wrangler around a maze of industrial buildings in Hamilton, Ohio. Hamilton is a small city 30 miles north of Cincinnati with a population of just over 62,000 people. Like much of Ohio, farming is important here. I'm on my way to a farm called 80 Acres, but it isn't the sprawling midwestern wheat field you're picturing in your mind. This tech-centric farm is indoors, housed entirely in a nondescript 10,000-square-foot warehouse.

AGC Glass Europe and Citrine Informatics are collaborating to use artificial intelligence (AI) to accelerate the development of next-generation glass. Citrine Informatics is a technology platform that harnesses the power of AI to bring new materials to market faster, and capture materials-enabled product value. AGC is providing experimental data to build proprietary AI models using the Citrine platform and is testing the newly suggested materials. The models are improved by Citrine through this sequential learning process, which targets the identification of the best process conditions to reach high-performance glass materials. Marc Van Den Neste, CTO of the Building & Industrial Glass Company from AGC said: "The future of materials development depends on speed. Developing these high performance materials faster will require managing and using data more effectively, which includes consolidating data into a single consistent searchable format, as well as structuring, storing, and using materials data to harness the power of AI." "Artificial Intelligence is expected to dramatically change how the scientists design experiments or value data, leading to breakthrough results."

Whilst the term artificial intelligence (AI) may conjure images of futuristic utopia and modern-day visionary technologies; the concept has actually been a societal forethought for longer than we think. Meanwhile, turn the clocks back considerably further to Ancient Egypt, and you'll find robotic-inspired animated ceremonial statues. Artificial intelligence is, in fact, centuries-old, and its implementation has long been a desire of the human race. Fast-forward to today and the omnipresence of robotics is remarkable. Not only are robots applied to large-scale industrial manufacturing chains (both assembling cars and integrated with vehicles themselves), but they're also found much closer to home on a smaller scale; hoovering our floors, mowing our lawns and, in some cases, stocking our shelves at local supermarkets1.

A recent post from Angel List, "Boring' Industries Benefits Most from AI." Petum's recent performance is a great example of the IT press tour. We have the opportunity to hear the compelling and informative case for AI, Perong's co-founder and CTO Kirong Ho. The goal of PETUIM is to transform AI technology from black-box architecture into a standard engineering process, with consistent and standard building blocks in organizations and industries. AI is hard, though, and is projected to grow 6X to $ 175 billion by 2025. There is a 99% talent error.

Andy O'Brien, CEO of M&M Food Market, is photographed in the company's Toronto offices. At M&M Food Market, the most valuable product isn't necessarily the food, but the mix of different ingredients the company uses to grow in Canada's highly competitive grocery and prepared meals sector. The recipe isn't complicated: Take a well-known brand – M&M Meats until the company rebranded in 2016 – add a helping of customer data and sprinkle it with predictive analytics and artificial intelligence tools. A company that has gone from a niche purveyor of bacon-wrapped filet to a data-driven prepared-food business tuned into customer habits and desires. M&M's mission today is to be agile and attentive to the appetites of millions of regular customers across Canada, says its chief executive officer, Andy O'Brien.

The FDA has cleared what it describes as the first software that uses AI to guide family doctors, registered nurses and other clinicians in taking cardiac ultrasounds. Developed by Brisbane, California-based Caption Health, the software communicates instructions via prompts on a screen-based interface. The prompts allow non-experts to capture images and videos of diagnostic quality. "This is especially important because it demonstrates the potential for artificial intelligence and machine learning technologies to increase access to safe and effective cardiac diagnostics that can be life-saving for patients," Robert Ochs, a deputy director in the FDA's Center for Devices and Radiological Health, said in a statement. The software is called Caption Guidance and was cleared for use with a diagnostic ultrasound system developed by Teratech Corp., though the software has the potential to be used with other systems, according to the FDA. In granting clearance to the software, the agency said it looked at two independent studies.