A predictive tool using artificial intelligence could provide hope for earlier diagnosis of type 1 diabetes in children across the UK, reducing the risk of potentially fatal diabetic ketoacidosis (DKA), early research presented at the Diabetes UK Professional Conference 2022 has revealed. Type 1 diabetes is a serious auto-immune condition that cannot yet be prevented, and the gradual destruction of insulin-making beta cells can start months or even years before being diagnosed. Symptoms usually start to appear much closer to diagnosis. Early diagnosis and awareness of the signs and symptoms of diabetes are crucial to ensure that both children and adults who develop it do not become critically ill. A quarter of children and young people (25%1) aren't diagnosed with type 1 diabetes until they are in DKA2, a life-threatening condition that can lead to coma or even death.

We are witnessing an exciting time in the automotive industry. As innovation is reaching new heights with connected and autonomous vehicles, the auto insurance industry is also experiencing its own evolution, using technology to enhance the way road accidents and damages are handled, saving people time and money and improving the often stressful experiences of handling the aftermath of accidents. A transformation is badly needed in the insurance industry. In addition to poor customer experiences when making claims, some $25 billion goes unaccounted for each year due to adjuster costs, fraud, delays in repair shops and more. Innovation can change that -- and it is already starting to.

At the Finovate Europe 2022 conference in London, FinTech Futures caught up with Jethro MacDonald, product manager at SmartStream, to chat about how the firm is utilising artificial intelligence (AI) and machine learning (ML) to help companies achieve regulatory alignment and accurate MiFID II transaction reporting. FinTech Futures also spoke with SmartStream CEO Haytham Kaddoura ahead of Sibos 2021 to discuss the most prevalent technology trends and opportunities as finance moves into the future. You can read the full interview here. You can also watch our video interview with Peter Dehaan, new business director for cash and liquidity management at SmartStream, here. We discuss how new technology and operational strategies can help firms better manage their data in the aftermath of the pandemic.

What does it mean to be human in an age where artificial intelligence agents make decisions that shape human actions? That's a deep question with no easy answers, and it's been on the mind of Dan Huttenlocher SM '84, PhD '88, dean of the MIT Schwarzman College of Computing, for the past few years. "Advances in AI are going to happen, but the destination that we get to with those advances is up to us, and it is far from certain," says Huttenlocher, who is also the Henry Ellis Warren Professor in the Department of Electrical Engineering and Computer Science. Along with former Google CEO Eric Schmidt and elder statesman Henry Kissinger, Huttenlocher recently explored some of the quandaries posed by the rise of AI, in the book, "The Age of AI: And Our Human Future." For Huttenlocher and his co-authors, "Our belief is that, to get there, we need much more informed dialogue and much more multilateral dialogue. Our hope is that the book will get people interested in doing that from a broad range of places," he says.

Q: Senthil, it's always great to meet a new face in AEC software. Can you tell us about your previous work and what you do at Slate? A: I've been working on advanced data technology in global software companies for over two decades now. I've helped pioneer multiple technological endeavours during that time, including AI, Blockchain, dge, cloud computing, metaverse, IoT, swarm robotics, system autonomy, and Big Data computing in industries spanning autonomous vehicles, fintech, smart buildings and cities, geospatial engineering, insurance, health care, and medicine. I've also helped develop the emerging AI Industry standards, such as the EU Artificial Intelligence Act, and also work in numerous industry think tanks and advisory boards of well-known academia and startups. Recently, my pioneering AI work was cited in the wall street journal and was recognised by the World Economic Forum.

Adam: Hello, this is CoRecursive and I'm Adam Gordon Bell. Today on April 1st, 2014, something interesting happened. Hacker News moderator Dan G, or dang, he made the following post. Challenge: Keep lame April Fools' jokes off the front page. Most April Fools' gags are lame. Only the very best ones that show some sort of ingenuity deserve attention. I propose that we, or rather you, flag these jokes so they don't end up on the front page. Dang wasn't the first person to complain about the lameness of tech company April Fools' Day jokes, but I think to the various developers and tech company people hanging out on Hacker News, dang's statement was a really big one. It kind of marked the end of this era of companies dropping these big jokes on April Fools'. So today in our first This Day in History Segment, I want to share some of history not just of April Fools', but of tech pranks in general, all leading up to that sort of cancellation statement by dang, and even right up to today actually. Why were pranks and April Fools' jokes traditionally celebrated in tech, and why are they now considered as dang said, "lame?" And here to talk about those pranks, I have my frequent co-host and developer extraordinaire, possible neighbor, Don McKay, and also my favorite PhD candidate and mathematician, Krystal Maughan. Why don't you guys say hello? Krystal: Hi, I'm happy to be here! I would challenge your assumption that they died on that day. I think we very much still see them today and they're just as an annoying today as they were in 2014. Krystal: I really like them because for me, getting into tech in general was through things like Hackerspaces and DEFCON, maybe some of these jokes flop, but when they're great, they're really funny. And I think that those kind of things should be encouraged as long as they're not necessarily malicious. That's the goal, but the reality is that everybody tries to do it and not everybody's good at it.

Have you ever wondered how does the google voice assistant recognizes what we speak and convert it to text? Or how does Amazon gives us different and mostly accurate recommendations? Or maybe how gmail knows which email is a potential spam? Many applications that we see around us uses Machine Learning or Data Science or Artificial Intelligence to provide us with different services. From Google Translate to Self Driving Cars, all the applications and software that tries to predict, classify or maybe even analyse some data uses Artificial Intelligence and Machine Learning.

Nvidia CEO Jensen Huang recently hosted yet another spring GTC event that drew more than 200,000 participants. And while he didn't succeed in acquiring Arm for $80 billion, he did have a lot of things to show off to those gathering at the big event. He gave an update on Nvidia's plans for Earth-2, a digital twin of our planet that -- with enough supercomputing simulation capability within the Omniverse –could enable scientists to predict climate change for our planet. The Earth 2 simulation will require the best technology -- like Nvidia's newly announced graphics processing unit (GPU) Hopper and its upcoming central processing unit (CPU) Grade. Huang fielded questions about the ongoing semiconductor shortage, the possibility of investing in manufacturing, competition with rivals, and Nvidia's plans in the wake of the collapse of the Arm deal. He conveyed a sense of calm that Nvidia's business is still strong (Nvidia reported revenues of $7.64 billion for its fourth fiscal quarter ended January 30, up 53% from a year earlier). Gaming, datacenter, and professional visualization market platforms each achieved record revenue for the quarter and year. He also talked about Nvidia's continuing commitment to the self-driving vehicle market, which has been slower to take off than expected. Huang held a Q&A with the press during GTC and I asked him the question about Earth-2 and the Omniverse (I also moderated a panel on the industrial metaverse as well at GTC). I was part of a large group of reporters asking questions. Question: With the war in Ukraine and continuing worries about chip supplies and inflation in many countries, how do you feel about the timeline for all the things you've announced? For example, in 2026 you want to do DRIVE Hyperion. With all the things going into that, is there even a slight amount of worry? Jensen Huang: There's plenty to worry about. I have to observe, though, that in the last couple of years, the facts are that Nvidia has moved faster in the last couple of years than potentially its last 10 years combined. It's quite possible that we work better, actually, when we allow our employees to choose when they're most productive and let them optimize, let mature people optimize their work environment, their work time frame, their work style around what best fits for them and their families. It's very possible that all of that is happening. It's also true, absolutely true, that it has forced us to put a lot more energy into the virtual work that we do. For example, the work around OmniVerse went into light speed in the last couple of years because we needed it. Instead of being able to come into our labs to work on our robots, or go to the streets and test our cars, we had to test in virtual worlds, in digital twins.

In interview 21 of The Gradient Podcast, we talk to Percy Liang, an Associate Professor of Computer Science at Stanford University and the director of the Center for Research on Foundation Models. He is also a strong proponent of reproducibility through the creation of CodaLab Worksheets. His awards include the Presidential Early Career Award for Scientists and Engineers (2019), IJCAI Computers and Thought Award (2016), an NSF CAREER Award (2016), a Sloan Research Fellowship (2015), a Microsoft Research Faculty Fellowship (2014), and multiple paper awards at ACL, EMNLP, ICML, and COLT. Removing spurious features can hurt accuracy and affect groups disproportionately.

Consumers have invited AI into their lives with voice-activated personal assistants like Siri and Alexa, but how do they feel about computer vision technologies that can provide visual coaching and feedback in their homes? Sanjay Nichani, vice president of artificial intelligence and computer vision at Peloton Interactive, describes one compelling use case in the at-home fitness space. Sanjay Nichani is vice president of artificial intelligence and computer vision at Peloton Interactive. In that role, he leads an AI/computer vision team focused on human pose estimation, activity recognition, and movement-tracking technologies for the fitness domain. He also leads the ongoing development of Peloton Guide, a new camera-based interactive strength-training product. Previously, Nichani was vice president of the computer vision and machine learning team at Acuant, working on document forensics technologies for detecting fraud. Before that, he was vice president of the Mitek Labs R&D group, where he led the development of a deep learning-based image-processing pipeline for identity verification. He also founded 3D sensor technology company Merakona and cofounded Pelfunc, developer of a photo-sharing app/service. He has advanced degrees in business from Babson College and computer science from the University of South Florida.