AI is transforming the practice of medicine. It's helping doctors diagnose patients more accurately, make predictions about patients' future health, and recommend better treatments. This Specialization will give you practical experience in applying machine learning to concrete problems in medicine. Machine learning is a powerful tool for prognosis, a branch of medicine that specializes in predicting the future health of patients. You'll then use decision trees to model non-linear relationships, which are commonly observed in medical data, and apply them to predicting mortality rates more accurately. Finally, you'll learn how to handle missing data, a key real-world challenge.

The arrival of artificial intelligence (AI) in embedded computing has led to a proliferation of potential solutions that aim to deliver the high performance required to perform neural-network inferencing on streaming video at high rates. Though many benchmarks such as the ImageNet challenge work at comparatively low resolutions and can therefore be handled by many embedded-AI solutions, real-world applications in retail, medicine, security, and industrial control call for the ability to handle video frames and images at resolutions up to 4kp60 and beyond. Scalability is vital and not always an option with system-on-chip (SoC) platforms that provide a fixed combination of host processor and neural accelerator. Though they often provide a means of evaluating the performance of different forms of neural network during prototyping, such all-in-one implementations lack the granularity and scalability that real-world systems often need. In this case, industrial-grade AI applications benefit from a more balanced architecture where a combination of heterogeneous processors (e.g., CPUs, GPUs) and accelerators cooperate in an integrated pipeline to not just perform inferencing on raw video frames but take advantage of pre- and post-processing to improve overall results or handle format conversion to be able to deal with multiple cameras and sensor types.

I recently caught up with Ian Hogarth and Nathan Benaich, who each year produce The State of AI Report, a must-read snapshot of how commercial applications of A.I. are evolving. Benaich is the founder of Air Street Capital, a solo venture capital fund that is one of the savviest early-stage investors in A.I.-based startups I know. Hogarth is the former co-founder of concert discovery app Songkick and has since go on to become a prominent angel investor as well one of the founders behind the founder-lead European venture capital platform Plural. There's always a lot to digest in their report. But one of the key takeaways from this year's State of AI is that concerns established tech giants and their affiliated A.I. research labs would monopolize the development of A.I. have been proven, if not exactly wrong, then at least premature. While it is true that Alphabet (which has both Google Brain and Deepmind in its stable), Meta, Microsoft, and OpenAI (which is closely partnered now with Microsoft) are building large "foundational models" for natural language processing and image and video generation, they are hardly the only players in the game.

As Machine Learning solutions to real-world problems spread, people are beginning to acknowledge the glaring need for solutions that go beyond training a single model and deploying it. The simplest process should at least cover feature extraction, feature generation, modeling, and monitoring in a traceable and reproducible way. In BigML, it's been a while since we realized that, and the platform has constantly added features designed to help our users easily build both basic and complex solutions. Those solutions often need to be deployed in particular environments. Our white-box approach is totally compatible with that, as users can download the models created in BigML and predict with them wherever needed by using bindings to Python or other popular programming languages.

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Deep Learning Tutorial with What is Deep Learning, Example of Deep Learning, Architecture of Deep Learning, Deep Learning Applications, Advantages and Disadvantages etc.

Autonomous shuttle with a demand responsive transit (DRT) system South Korea's autonomous transportation startup 42dot, owned by Hyundai Motor Group, on Monday unveiled a driverless electric shuttle installed with a demand responsive transit (DRT) system. The autonomous shuttle, dubbed aDRT, is a purpose-built vehicle (PBV), or an eco-friendly multi-purpose mobility vehicle. It was built for driverless public transportation from the design stage, unlike a conventional self-driving vehicle installed with an autonomous driving kit, the company said. The eight-seat PBV not only drives rotating routes, but also plans optimized routes depending on demand to improve user convenience. It can accommodate up to seven passengers, as well as one seat for the safety guard, and drive up to 300 kilometers on a single charge.

This week, guest host Zak Rosen from The Best Advice Show and Slate's Mom and Dad Are Fighting podcast talks to Liza Bielby and Richard Newman of the Detroit-based theater company The Hinterlands. They talk about how The Hinterlands' latest production Will You Miss Me? came into being, their influences, their rehearsal process, and the importance of deadlines After the interview, Zak and co-host June Thomas chat about collaboration, how to kill your darlings, and how Zak implements Julia Cameron's concept of the "artist's date." Send your questions about creativity and any other feedback to working@slate.com or give us a call at (304) 933-9675.

Holly Herndon, the self-described "computer musician," swears her latest creation--an AI-powered vocal clone that is, at least theoretically, infinitely capable--was not made with the intent of freaking anyone out. "Definitely not," Herndon says on a call from her home in Berlin, laughing. "I'm trying to do the opposite." Named Holly, the vocal clone sings in Herndon's voice but can be prompted to sing anything. In a recent TED talk, Herndon displayed Holly singing songs in languages she doesn't speak.

The holiday shopping season reaches its peak when Cyber Monday deals roll around. Sales are often better than on Black Friday, but with every retailer promising the best Cyber Monday discounts, it can be tricky to work out what deals to snag and when to pass. Luckily, we have done the hard work for you. WIRED reviewers try countless gadgets, tools, and digital delights of all kinds every week, and we have developed smart shopping tips and tricks to weed out fake discounts and bring you the real deals. We can say with confidence that these are the absolute best Black Friday and Cyber Monday deals you're going to find this weekend. You will find regular updates as products go out of stock and prices change, and we'll keep scouring to find more deals worth grabbing. Updated November 27, 2022: We've added deals on umbrellas, mobile accessories, and more. We've also updated pricing and availability. We test products year-round and handpicked these deals. Products that are sold out or no longer discounted as of publishing will be crossed out . We'll update this guide throughout the Cyber Monday weekend. If you buy something using links in our stories, we may earn a commission. This helps support our journalism. Just like upgrading the bed you sleep on, few things will improve your life like a good chair. If you park your body in front of a desk all day, it's a good idea to give the humble chair more attention. Some of our favorites are on sale right now. See our Best Office Chairs guide for more. Our top office chair pick is a bit cheaper right now. We've tested more than 35 office chairs in the past year and this is the one to get based on comfort, quality, adjustability, and price. At this price, you'd be hard-pressed to find a cheaper way to get seven points of adjustment. The only thing we don't like is that pet hair tends to cling, so keep a lint roller handy. The Zeph looks wonderful--there are dozens of color customizations--but the only adjustment you can make is to raise the seat up or down. You might think that would make for an uncomfortable chair, but it doesn't. This lack of adjustability is by design as the Zeph is designed to mold to your body. We do suggest you get the seat pad and arms, which add a smidge more comfort, though it does jack the price up a bit. The Zeph is compact, making it a great option for smaller spaces.