"AI has the potential to completely revolutionise every part of how we approach healthcare, from how we diagnose diseases and the speed at which our doctors and nurses deliver treatments to how we support people's mental health. "The 38 projects we are backing reflect the UK's trailblazing approach to innovation in the healthcare sector, and could help us take a leap forward in the quality of care and the speed of disease diagnoses and treatment in the NHS. "Confronted with this global pandemic, our tech sector has risen to the challenge and upended how we do things through innovations to support people to test from home, complete remote consultations and diagnose issues safely." "Precision cancer diagnosis, accurate surgery, and new ways of offering mental health support are just a few of the promising real world patient benefits. Because as the NHS comes through the pandemic, rather than a return to old ways, we're supercharging a more innovative future. "So today our message to developers worldwide is clear - the NHS is ready to help you test your innovations and ensure our patients are among the first in the world to benefit from new AI technologies." The AI in Health and Care Award aims to accelerate the testing and evaluation of AI in the NHS so patients can benefit from faster and more personalised diagnosis and greater efficiency in screening services. For example, use of Paige Prostate will be able to give more information about prostate cancer, including detecting a tumour, its size and how severe it is, enabling clinicians to make treatment more specific and more targeted. As well as this, Mia by Kheiron Medical, a winner from the first round of the AI Awards, aims to replace the need for two radiologists to review breast cancer scans by instead using one radiologist and the AI, making the process faster and more efficient. "These trials are making the AI revolution a reality for patients.

We generally use moments in statistics, machine learning, mathematics, and other fields to describe the characteristics of a distribution. Let's say the variable of our interest is X then, moments are X's expected values. Now we are very familiar with the first moment(mean) and the second moment(variance). The third moment is called skewness, and the fourth moment is known as kurtosis. The third moment measures the asymmetry of distribution while the fourth moment measures how heavy the tail values are.

Deep learning (DL) tools like convolutional neural networks which contain millions of simulated neurons structured in layers enable artificial intelligence (AI) to imitate the learning, reasoning, perception and problem solving of the human brain. This technological change is revolutionizing every dimension of the insurance industry. While insurers, suppliers, insurance brokers and consumers are getting better at implementing DL and AI tools for the improvement of reasoning and productivity, cost minimization and the enhancement of the customer experience, this technological shift will be even faster. In this blog post, we are going to share with you four aspects insurers need to focus on and how they can get prepared so as to get the most out of this tech-driven transformation. The number of connected consumer devices will drastically rise in the near future.

IMAGE: An artificial skin attached to a person's knee develops a purple "bruise " when hit forcefully against a metal cabinet. Credit: Adapted from ACS Applied Materials & Interfaces 2021, DOI: 10.1021/acsami.1c04911 When someone bumps their elbow against a wall, they not only feel pain but also might experience bruising. Robots and prosthetic limbs don't have these warning signs, which could lead to further injury. Now, researchers reporting in ACS Applied Materials & Interfaces have developed an artificial skin that senses force through ionic signals and also changes color from yellow to a bruise-like purple, providing a visual cue that damage has occurred.

Governments' increasing use of artificial intelligence (AI) technology and people's inability to avoid official computer services present threats politicians must address with law, privacy watchdogs say. "Regulatory intervention is necessary," the B.C. and Yukon ombudsman and information and privacy commissioners said in a report released June 17. "The regulatory challenge is deciding how to adapt or modernize existing regulatory instruments to account for the new and emerging challenges brought on by government's use of AI. The increasing automation of government decision-making undermines the applicability or utility of existing regulations or common law rules that would otherwise apply to and sufficiently address those decisions." Just as fairness and privacy issues resulting from the use of AI in commercial facial recognition systems have been shown to have bias and infringe people's privacy rights, government use of AI can have serious, long-lasting impacts on people's lives and could create tension with the fairness and privacy obligations of democratic institutions, the report said.

Wading through the vast array of information for data science newcomers on machine learning algorithms can be a difficult and time-consuming process. Figuring out which algorithms are widely used and which are simply novel or interesting is not just an academic exercise; determining where to concentrate your time and focus during the early days of study can determine the difference between getting your career off to a quick start and experiencing an extended ground delay. How, exactly, does one discriminate between immediately useful algorithms worthy of attention and, well, not so much? Determining how to come up with an objective list of machine learning algorithms of authority is inherently difficult, but it seems that going directly to practitioners for their feedback may be the optimal approach. Such a process presents a whole host of difficulties of its own, as could be easily imagined, and results of such surveys are few and far between.

A team of researchers from Germany's Fraunhofer FKIE institute has created a drone that can locate screaming humans. While it sounds like the stuff of dystopian fiction, it's actually something they set out to create to make it easier for first responders to find survivors following a natural disaster. "(Drones) can cover a larger area in a shorter period of time than rescuers or trained dogs on the ground," Macarena Varela, one of the lead engineers on the project, told The Washington Post. "If there's a collapsed building, it can alert and assist rescuers. It can go places they can't fly to or get to themselves."

On Thursday, the CEOs of NVIDIA and Arm addressed the controversy around the $40 billion dollar deal that saw NVIDIA purchase the company from Softbank in September. Arm CEO Simon Segars and NVIDIA CEO Jensen Huang spoke with analyst Pat Moorhead at the Six Five Summit and both argued that the merger would benefit a number of industries. Segars said Arm is overwhelmed with demand and has been unable to deal with the increased need for more computing. "Right now, we're looking at everything we can do in a day. We've just got way more to do than people to do it. That's always been the case but right now it's more so than ever," Segars explained.

There are many powerful techniques that perform keywords extraction (e.g. However, they are mainly based on the statistical properties of the text and don't necessarily take into account the semantic aspects of the full document. KeyBERT is a minimal and easy-to-use keyword extraction technique that aims at solving this issue. It leverages the BERT language model and relies on the transformers library. So go check his repo (and clone it) if you're interested in using it.

Transform, the world's leading event on applied AI for enterprise business & technology decision makers, will host thousands of executives across industries to share their AI and data technology stories. VentureBeat is bringing back its AI survey to sample leaders who are innovating and integrating AI and other large data projects into their workflows and product development, as well as those who are interested in learning how to get started. It takes just a few minutes, and in return, you'll get an exclusive look at the full results. You'll also be invited to join Transform as a VIP passholder and hear from Matt Marshall, CEO at VentureBeat, on July 16th for top learnings and trends gleaned from results. Attendees from across the globe will join Transform online to hear from top industry experts on strategy and technology in the main application areas of AI/ML automation technology, data, analytics, intelligent automation, conversational AI, intelligent AI assistants, AI at the edge, IoT, & computer vision.