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Amazon starts shipping its $249 DeepLens AI camera for developers

Back at its re:Invent conference in November, AWS announced  its $249 DeepLens, a camera that’s specifically geared toward developers who want to build and prototype vision-centric machine learning models. The company started taking pre-orders for DeepLens a few months ago, but now the camera is actually shipping to developers. Ahead of today’s launch, I had a chance to attend a workshop in Seattle with DeepLens senior product manager Jyothi Nookula and Amazon’s VP for AI Swami Sivasubramanian to get some hands-on time with the hardware and the software services that make it tick. DeepLens is essentially a small Ubuntu- and Intel Atom-based computer with a built-in camera that’s powerful enough to easily run and evaluate visual machine learning models. In total, DeepLens offers about 106 GFLOPS of performance. The hardware has all of the usual I/O ports (think Micro HDMI, USB 2.0, Audio out, etc.) to let you create prototype applications, no matter whether those are simple toy apps that send you an alert when the camera detects a bear in your backyard or an industrial application that keeps an eye on a conveyor belt in your factory. The 4 megapixel camera isn’t going to win any prizes, but it’s perfectly adequate for most use cases. Unsurprisingly, DeepLens is deeply integrated with the rest of AWS’s services. Those include the AWS IoT service Greengrass, which you use to deploy models to DeepLens, for example, but also SageMaker, Amazon’s newest tool for building machine learning models. These integrations are also what makes getting started with the camera pretty easy. Indeed, if all you want to do is run one of the pre-built samples that AWS provides, it shouldn’t take you more than 10 minutes to set up your DeepLens and deploy one of these models to the camera. Those project templates include an object detection model that can distinguish between 20 objects (though it had some issues with toy dogs, as you can see in the image above), a style transfer example to render the camera image in the style of van Gogh, a face detection model and a model that can distinguish between cats and dogs and one that can recognize about 30 different actions (like playing guitar, for example). The DeepLens team is also adding a model for tracking head poses.

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Amazon starts shipping its $249 DeepLens AI camera for developers

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Indian food delivery startup Swiggy raises $210M at a $1.3B valuation

India’s food delivery race is hotting up after Swiggy , one of the startups vying for pole position, landed $210 million in new capital for expansion and joined the billion-dollar startup unicorn club. The investment is led by existing backer Naspers, the media conglomerate famous for an early bet on Tencent in China, and new investor DST Global. Others taking part in the round include returning investor China’s Meituan Dianping and (another new investor) Coatue Management. The deal takes Swiggy’s valuation past the $1 billion mark for the first, with sources close to the company confirming that the deal values the company at around $1.3 billion. That’s perhaps not a tonne of surprise around today’s announcement since it has been rumored in Indian press for some time, with Economic Times first reporting on it in April . This Series G investment comes just months after Naspers and Meituan Dianping invested $100 million into Swiggy in February . The new round takes Swiggy to over $465 million raised from investors to date, making it India’s most-capitalized food delivery startup. Nearest competitor Zomato has raised some $440 million from investors that include Alibaba’s Ant Financial affiliate, Sequoia Capital and Temasek, but its business also includes markets outside of India, whereas Swiggy’s is firmly focused on its homeland. ( Zomato was most recently valued at $1.1 billion. ) Swiggy claims to cover 35,000 restaurants with a delivery fleet of over 40,000. The company isn’t giving financials at this point, but it said that it has seen “a three-fold increase in revenues in the last financial year.” The company isn’t saying in specifics how it will use the new capital, but a representative told TechCrunch that the plan is to invest in extending its reach to new locations in India and also to build out its logistics network to better serve customers.

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