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5 ways computer vision could impact how we do AI


This is an exciting time for those of us in computer vision — we’re seeing it merge with AI to enable all kinds of new possibilities. At the LDV Vision Summit in New York a few weeks ago, I came away with five key insights about where computer vision will impact AI:

1. Smart assistants will battle it out over vision

AI needs data with which to learn and process, and as we move closer to more “human”-like AI, it will increasingly need visual data. “This is one of the reasons all the major companies are at war to own the visual data of our activities,” said LDV Capital’s Evan Nisselson. “To do that, they need to own the camera.” Amazon recently added a camera to its Alexa-powered Echo, for example, and Google (Lens) and Facebook recently made new recent augmented reality announcements.

2. Optics alone could be enough to direct self-driving cars

We are seeing debate over whether self-driving cars need LiDAR or can depend solely on optical solutions. Tesla CEO Elon Musk, for example, doesn’t think that LiDAR, a bulky and expensive device that uses lasers to maps its environment in real time, is necessary for fully-autonomous driving. Wheras Humatics CTO Gregory Charvat said at the vent that cars “need more than just optical sensor platforms [cameras], they also need LiDAR, radar, and high-precision radio navigation more precise than differential GPS.”

LiDAR and radar work by pinpointing actual objects in the surrounding environment by range and angle, whereas deep learning-based camera solutions need to run images through algorithms and are ultimately still predictions. Optical solutions are nevertheless better at actually identifying what something is — for example, a pedestrian versus a bunch of pixels that look like a Christmas tree, as Auto X Founder and CEO Jianxiong Xiao showed during a demo of his company’s impressive and low-cost self-driving solution that only uses cameras.

Technology pros and cons aside, car companies typically work five years in advance, so the necessary hardware would need to be purchased now to make a 2021 deadline. For now, LiDAR and more advanced forms of radar are still expensive ($80,000 is considered cheap for the former) and bulky. Meanwhile, operating all these optical and sensor technologies in a fused way needs supercomputers small enough to fit in a car.

3. Vision could teach machines better than machine learning

As a few of the demos at LDV reminded us, machines don’t just learn through neural networks and machine learning. There are other ways they can learn to identify and analyze the world around them. Google Research scientist Tali Dekel demonstrated a technique that used computer vision to identify and then enlarge deviations from straight lines on a roof or the subtle presence of purplish color on fruit to, say, determine if there are structural problems in an old home or which tomatoes are riper than others. It seems simple enough, and yet it’s the type of thing that computer vision is better at than humans.

4. Machine vision can help with medical diagnoses

When a pathologist has, on an average day, 500 slides, each containing tens and hundreds of thousands of individual cells that need to be analyzed for, say, the presence of cancer, it’s easy to miss a diagnosis. “This is an impossible task for a human to do as effectively as a computer, simply because we’re not able to look carefully at every single cell,” said Andrew Beck, cofounder and CEO of PathAI. “We think computers can be really good at getting the perfect diagnosis every time.”

According to an American Medical Association study, just under half of the pathologists agree on a correct diagnosis. Citing another study focused on breast cancer lymph node biopsies, Beck showed the difference between the hotspots found by a computer versus a human pathologist; the former highlighted many additional areas that turned out to contain cancer cells. “We provide pathologists with both the raw image, so they’re still looking at the data they’re used to, as well as the image processed by the learning system, which essentially identifies the areas of cancer, enabling a physician to focus in on those areas,” said Beck. The breast cancer study found that without AI, this kind of biopsy only has an accuracy rate of 85 percent. With the AI-aided solution, the error rate plummeted to .5 percent.

5. The field of computer vision is getting easier and easier to jump into

The commoditization of better cameras, sensors, and deep learning software libraries such as Google TensorFlow has significantly expanded access to computer vision, and we are seeing many new startups emerge as a result. In the Vision Summit’s two startup competitions, we saw everything from a technology that generates demographic insights out of Google Street View images to an app that assesses the damage and calculates repair costs of a car that’s just been in an accident — from nothing more than a picture.

“What’s emerged is this incredible commoditization of so many parts of computer vision and machine learning that used to require teams of PhDs to develop in terms of infrastructure,” said Cornell Tech Professor and Summit coorganizer Serge Belongie, “but now it’s possible for individual hackers or developers on small startup teams to bring that kinds of functionality to any kind of product.”

Even so, commoditization still isn’t 100 percent plug and play. As Albert Wenger, Managing Partner at Union Square Ventures, told me, “It’s one of those curves where it’s easy to get 80 percent, and then extremely hard to get the rest done.”

So there’s still a lot of work to be done, which is a good thing for anyone interested in helping build the next big visual technology — whether it’s for business, health, or pleasure.

Ken Weiner is CTO at GumGum.

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About Ms. A. C. Kennedy

Ms. A. C. Kennedy
My name is Ms A C Kennedy and I am a Health practitioner and Consultant by day and a serial blogger by night. I luv family, life and learning new things. I especially luv learning how to improve my business. I also luv helping and sharing my information with others. Don't forget to ask me anything!

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What we’re watching: ‘Raw’ and ‘Feast of Fiction’

Welcome back to Video IRL, where several of our editors talk about what they've been watching in their spare time. This month we're kicking things off with some seasonally-appropriate horror fare, that you can catch right away on Netflix or Amazon Prime. Then it's time for a Gundam throwback before Kris Naudus points out a couple of YouTube food channels perfect for binge eating or binge watching.

Them / Raw


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Associate Editor

To get into the Halloween spirit, I've been watching at least one horror movie a day since the end of September -- the lower the budget, the better. Problem is, so many of the American low-budget or indie horror offerings on Amazon and Netflix are crappy Paranormal Activity clones, cheap-thrill gore-fests or uninspired found-footage "documentaries." Whether it's by design or coincidence, I've found that French horror movies have held my attention the most lately. Specifically, 2016's Raw, as well as Them, from ten years prior. They're more psychological thrillers than straight-up horror, but that didn't stop me from being more on edge while watching them one afternoon than I was during A Haunting in Saginaw, Michigan, late at night. Both start with a car crash, but they couldn't finish any more differently.

Raw, recently added to Netflix, tells the tale of a vegetarian girl in her first week at a prestigious veterinary school. During a hazing ritual, she's forced to eat a raw rabbit kidney. She immediately gets sick, throws up and wakes herself up that night scratching a full-body rash to near bleeding. This bout with food poisoning is just the beginning, though, and soon protagonist Justine finds out she has a taste for forbidden fruit. As the remaining 70-ish minutes unfolded, I lost track of how many times I clasped my hands over my mouth, agape in shock, to stifle my shouts of "OHMYGODWHATTHEFUCKISEVENHAPPENING?!"

But French director Julia Ducournau balances every body-horror scene either with something pedestrian twisted into being unsettling (like a horse on a treadmill) or with something that makes you ask how far Justine can go before someone confronts her about her new diet. And those questions keep coming right until the credits roll. I can't say I enjoyed watching Raw, but it was a hell of a ride.

The same goes for Them, currently streaming on Amazon Prime. Its focus is narrow, centering on a young couple living in a cavernous farmhouse, terrorized over the course of a night by unseen horrors. The camera never quite gives away who (or what) the perpetrators are, and revealing the twist would be a sin. As with Raw, its atmosphere and overall creepiness won me over straightaway. The scariest part? Realizing that I've probably driven past a shot like the final scene countless times and not thought twice about it. If you're willing to read subtitles, both of these should make you shiver and scream more than The Conjuring 2 on HBO Go could ever hope to.

Mobile Suit Gundam The 08th MS Team


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David Lumb
Contributing Editor

I'd heard that a lot of anime had left Hulu, but I scanned their selection anyway looking for classic shows I'd missed, like the original Mobile Suit Gundam. They don't have that -- but they did have a series I didn't finish the first time it aired on Toonami, the 1996 classic Gundam side story The 08th MS Team. Unlike the franchise's other show released the year before, the massively successful Gundam Wing, 08th ditches the brand's typical pretty-boys-in-unbeatable-robots for a grounded and sobering story about the people who get caught up in wars -- desperate soldiers, civilians and guerrillas alike. It's dirty, honest, utterly humane and gorgeously animated.

It's also a little preachy and melodramatic, and it shows its age with odd sexist moments. While it's still the Thin Red Line of the Gundam universe, I remember it far more fondly from when my 14-year-old self grazed the series on its first American airing. There's something sad in seeing an old favorite for the flawed media it always was. Much like Waypoint's Rob Zacny, I've grown up and seen a lot since I first caught the show as a starry-eyed teen. I still think The 08th MS Team is a wonderful little 12-episode miniseries with a big heart, but I won't revere it so highly -- and will think a little harder about who I recommend it to.

Feast of Fiction / Binging with Babish


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Senior Editor, Database

Back in March, I came home from a trip only to discover that my oven didn't work. The cooking gas in my building had been shut off due to a leak. My building management seemed to be on it, so I made do with a combination of microwavables, toaster oven and Seamless. Unfortunately, weeks and months went by, calls to the city were made and permits were issued, but, even as I write this in October, gas still has not been restored to my building. My landlords eventually threw their collective hands in the air and began installing electric ranges in every apartment, so a few weeks ago I was finally able to cook for myself again.

I am so jazzed to be able to make food. Hot food! Scrambled eggs! Steak! Cookies! I started reading food blogs and cookbooks, and shopping to refill my pantry. I'm halfway through Kenji Alt-Lopez's The Food Lab, a huge 900-page hardcover that talks about the science of how food cooks. On the lighter side, I've also been reading food-themed comics like Delicious in Dungeon and Food Wars. And the latter title (which is also an anime) ended up sucking me into a YouTube hole of food videos that I've been obsessed with ever since.

You see, the very first chapter of Food Wars features the "Gotcha" Pork Roast, a bacon-wrapped potato loaf that hero Soma Yukihira makes to save his family restaurant. It looks pretty tasty, so I searched for recipes and pics online and stumbled onto Jimmy Wong and Ashley Adams' Feast of Fiction, a series that demonstrates how to make various foods seen in cartoons, video games and comics. If you ever wanted to taste Steven Universe's beloved Cookie Cat ice cream sandwiches or Kirby's super-spicy curry, there's an episode for you. One thing I really enjoy is how they also incorporate crafts into it, showing how to make paper wrappers for your Reptar chocolate bars or genuine-looking Ecto Cooler Hi-C boxes.

I've been marathoning through the episodes, which the YouTube algorithms have definitely picked up on at this point, throwing food show after food show into my suggestions. One that caught my eye was Binging with Babish. Where Feast of Fiction mostly sticks to the realm of kids' cartoons, anime and video games, Binging with Babish is a little more mainstream, covering foods from popular media like Mad Men, Seinfeld and House of Cards. Still, there's a bit of overlap -- both Babish and Feast have done their own takes on the Ultimeatum from Regular Show and Krabby Patties from SpongeBob SquarePants. But the recipes are different, and I watch the shows for the personalities. Feast of Fiction is pretty silly (and there's a cute dog), while Binging with Babish is a little more subdued. Not that Babish can't be ridiculous as well -- the Moist Maker is one of the most ridiculously complicated sandwiches I have ever seen, basically asking you to cook an entire Thanksgiving dinner.

Sadly, I still haven't done a lot of actual cooking since getting my stove back. I'm having too much fun watching other people do it instead, with the added bonus that I don't have to clean up the mess.

"IRL" is a recurring column in which the Engadget staff run down what they're buying, using, playing and streaming.

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