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But mean target encoding is their turbocharger The post Decision Trees Natively Handle Categorical Data appeared first on Towards Data Science.

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This is today’s edition of The Download, our weekday newsletter that provides a daily dose of what’s going on in the world of technology. What’s next for AI and math The modern world is built on mathematics. Math lets us model complex systems such as the way air flows around an aircraft, the way financial markets fluctuate, and the way blood flows through the heart. Mathematicians have used computers for decades, but the new vision is that AI might help them crack problems that were previously uncrackable.   However, there’s a huge difference between AI that can solve the kinds of problems set in high school—math that the latest generation of models has already mastered—and AI that could (in theory) solve the kinds of problems that professional mathematicians spend careers chipping away at. Here are three ways to understand that gulf.  —Will Douglas HeavenThis story is from our What’s Next series, which looks across industries, trends, and technologies to give you a first look at the future. You can read the rest of them here. Inside the effort to tally AI’s energy appetite —James O’Donnell After working on it for months, my colleague Casey Crownhart and I finally saw our story on AI’s energy and emissions burden go live last week.  The initial goal sounded simple: Calculate how much energy is used when we interact with a chatbot, then tally that up to understand why leaders in tech and politics are so keen to harness unprecedented levels of electricity to power AI and reshape our energy grids in the process.It was, of course, not so simple. After speaking with dozens of researchers, we realized that the common understanding of AI’s energy appetite is full of holes. I encourage you to read the full story, which has some incredible graphics to help you understand this topic. But here are three takeaways I have after the project. This story originally appeared in The Algorithm, our weekly newsletter on AI. To get it in your inbox first, sign up here, and check out the rest of our Power Hungry package about AI here. The must-reads I’ve combed the internet to find you today’s most fun/important/scary/fascinating stories about technology. 1 Elon Musk has turned on Trump He called Trump’s domestic policy agenda a “disgusting abomination.” (NYT $)+ House Speaker Mike Johnson has, naturally, hit back. (Insider $) 2 NASA is in crisisIts budget has been cut by a quarter, and now its new leader has had his nomination revoked. (New Scientist $)+ What’s next for NASA’s giant moon rocket? (MIT Technology Review)3 Here’s how Big Tech plans to wield AITo build ‘everything apps’ that keep you inside their ecosystem, forever. (The Atlantic $)+ The trouble is, the experience isn’t always slick enough, as Google has discovered with its ‘Ask Photos’ feature. (The Verge $)+ How to fight your instinct to blindly trust AI. (WP $)4 Meta has signed a 20-year deal to buy nuclear power It’s the latest in a race to try to keep up with AI’s surging energy demands. (ABC)+ Can nuclear power really fuel the rise of AI? (MIT Technology Review) 5 Extreme heat takes a huge toll on people’s mental healthIt’s yet another issue we’re failing to prepare for, as summers get hotter and hotter. (Scientific American $)+ The quest to protect farmworkers from extreme heat. (MIT Technology Review) 6 China’s robotaxi companies are planning to expand in the Middle East And they’re getting a warmer welcome than in the US or Europe. (WSJ $)+ China’s EV giants are also betting big on humanoid robots. (MIT Technology Review)7 AI will supercharge hackersThe full impact of new AI techniques is yet to be felt, but experts say it’s only a matter of time. (Wired $)+ Five ways criminals are using AI. (MIT Technology Review)8 It’s an exciting time to be working on Alzheimer’s treatments 12 of them are moving to the final phase of clinical trials this year. (The Economist $)+ The innovation that gets an Alzheimer’s drug through the blood-brain barrier. (MIT Technology Review)9 Workers are being subjected to more and more surveillanceNot just in the gig economy either—’bossware’ is increasingly appearing in offices too. (Rest of World) 10 Noughties nostalgia is rife on TikTokIt was a pretty fun decade, to be fair. (The Guardian) Quote of the day  “This is scientific heaven. Or it used to be.” —Tom Rapoport, a 77-year-old Harvard Medical School professor from Germany, expresses his sadness about Trump’s cuts to US science funding to the New York Times.  One more thing OLCF What’s next for the world’s fastest supercomputers When the Frontier supercomputer came online in 2022, it marked the dawn of so-called exascale computing, with machines that can execute an exaflop—or a quintillion (1018) floating point operations a second.Since then, scientists have geared up to make more of these blazingly fast computers: several exascale machines are due to come online in the US and Europe.But speed itself isn’t the endgame. Researchers hope to pursue previously unanswerable questions about nature—and to design new technologies in areas from transportation to medicine. Read the full story. —Sophia Chen We can still have nice things A place for comfort, fun and distraction to brighten up your day. (Got any ideas? Drop me a line or skeet ’em at me.) + If tracking tube trains in London is your thing, you’ll love this live map.+ Take a truly bonkers trip down memory lane, courtesy of these FBI artifacts.+ Netflix’s Frankenstein looks pretty intense.+ Why landlines are so darn spooky

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Speedata, a Tel Aviv-based startup developing an analytics processing unit (APU) designed to accelerate big data analytic and AI workloads, has raised a $44M Series B funding round, bringing its total capital raised to $114M. The Series B round was l

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