5 AI startups out to vary the world

Advances in deep studying and neural networks have delivered big breakthroughs in pure language processing and pc imaginative and prescient, they usually have the potential to unravel massive issues in manufacturing, retail, provide chain, agriculture, and numerous different enterprise domains. Naturally, know-how startups are behind among the most necessary improvements.

In current articles, we checked out startups revolutionizing pure language processing and startups main the way in which in MLops. Right here we’ll check out “utilized AI” startups. These are corporations which can be making use of completely different strategies—whether or not it’s processing photos, textual content, audio, video, categorical or tabular knowledge, or combos of the above—to handle varied trade challenges, from fulfilling the promise of self-driving automobiles to pushing the boundaries of agricultural manufacturing.

Argo AI

Are we there but? It appears we’ve been ready on the guarantees for years now, however the work in self-driving know-how continues. Argo AI is an organization that goals to change into the whole platform for self-driving automobiles, protecting all of the software program, {hardware}, maps, and distant infrastructure that might be required to deliver us to the fantastic future the place we don’t need to be on a bus or a practice to learn a guide on the commute to work.

Working with companions equivalent to Ford and Volkswagon, Argo AI is pushing ahead the boundaries of analysis, having just lately simply introduced Argo Lidar (mild detection and ranging), a brand new strategy to performing distance checks of objects as much as 400 meters away, in addition to working properly at night time and in low-light circumstances and having the ability to deal with transitions equivalent to popping out of tunnels that may trigger points for different Lidar arrays (and let’s face it, us poor people too).

Argo AI will not be making wild guarantees about its present tech, however seems to be doing the lengthy exhausting slog of constructing all of the blocks for a protected assisted-driving expertise, testing in six cities throughout the US, with testing in Europe slated for later this yr.

Ceres Imaging

Possibly it isn’t fairly as gee-whiz as self-driving, however the know-how that Ceres Imaging is bringing to bear on rising crops might properly assist to decrease your grocery invoice lengthy earlier than you may get right into a self-driving automotive and have it take you to the grocery store.

Ceres Imaging affords an exquisite mixture of old-school and cutting-edge know-how, eschewing satellite tv for pc or drone imagery for high-resolution cameras mounted onto fixed-wing plane and utilizing these photos as enter to an array of fashions to supply vital data to farmers, equivalent to discovering irrigation issues two to 3 weeks earlier than they’d be seen within the subject, correcting over-watering or under-watering eventualities, and calculating how fixing these points will have an effect on yields.

As well as, Ceres Imaging can relieve farmers of the burden of easy, labor-intensive duties like tree counting, as an alternative producing tree counts from aerial imagery. Ceres will ship a report that tallies the variety of bushes by varietal, and pinpoints the places of lacking and broken bushes, even going as far as producing the nursery order for replacements. It’s only one tiny instance of how AI strategies are unlocking advances even in areas which may not instantly come to thoughts when any individual says the phrases “neural community.”

Touchdown AI

Based by Andrew Ng, co-founder of Google Brain and former head of data science at Baidu, Landing AI is an attempt to bring the power of AI to domains that have not yet seen the advances it can bring. The company’s first product, LandingLens, is an integrated platform that allows manufacturers to pair their expertise with Landing AI’s to produce a continuously improving visual inspection platform. In addition to manufacturing, Landing AI is also working on visual inspection systems for the agriculture and automotive industries.

One interesting aspect of Landing AI’s approach is how it puts users’ data at the center of the solution. Dealing with input data is often the least exciting part of a data scientist’s job, but despite great strides being made in self-supervised solutions in the past few years, input data is where you can make the biggest impact on your application. It doesn’t matter how fancy your model is; if you feed it garbage, you’re going to get garbage out. So Landing AI focuses on efficient and easy-to-use labelling systems, making sure that data is collected continuously, easy retraining and validation of models, and of course, being able to alert quickly if inferences suddenly skew (e.g., if a camera loses a color channel).


Sooner, rather than later, we’re going to need a way of detecting deepfakes. While deepfaking—using AI techniques to generate fake audio and video of real people—still hasn’t quite made it to the mainstream, the expense and knowledge needed to generate such media is decreasing on a weekly basis. You may have seen recent news stories about the remarkably convincing Tom Cruise deepfake TikTok. Even more convincing fake Tom Cruises are in our future.

Headquartered in Estonia, Sentinel is striving to be one of the leaders in that arena. With impressive credentials from NATO cybersecurity and backing from the former president of Estonia, they are offering an API that draws on various deep learning approaches, as well as a massive database of existing fakes for comparison purposes, to determine whether uploaded media is fake or not. The Sentinel system even produces a report one what was done to generate the fake in the case of a positive result.


Like the Amazon Go stores that dot a few major US cities, Standard offers the promise of brick-and-mortar shopping without lines. You check in with a mobile app when you enter a store, wander around and grab what you want, and then you just leave. Standard’s computer vision technology keeps track of everything you leave the building with and charges your account. The experience is even more friction-free than Amazon Go, with no turnstiles or gates.

Standard would very much like to be the company that makes this technology ubiquitous among retailers, hooking into their supply chains to provide detailed analytics as well as the smoothest of checkout experiences. Currently, Standard has a flagship store in San Francisco (but of course!) and has inked a deal with Circle K on some pilot experiments in Arizona, retrofitting four stores with autonomous checkout technology. If all goes well, we could see Standard’s shopping AI spreading across the country fast.

Where next?

What we can see in this short tour of startups is that the range of verticals where the cutting-edge techniques of computer vision, natural language processing, and other deep learning approaches is vast and most likely underestimated. The neural networks are learning more and more all the time. They’re already in our phones, and they’re coming to our stores, cars, supply chains, manufacturing plants, and farms. Who knows where else they’ll be by the time 2030 rolls around?

Copyright © 2021 IDG Communications, Inc.

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