Computer Vision Jobs in Chicago

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Our New Relationship with Food: Computer Vision and Robotics in the Grocery Aisle

Curbside pickup. Order online, pickup in store. Mealkits and subscription boxes. Self-checkout. Contactless payments, Robots-as-a-Service (RaaS), smart carts, and more. These are just a few of the advances which have been amped up during the pandemic and could be here to stay.  Now well-versed in physical distancing and self-preservation from quarantine to vaccine, we have reestablished a healthy relationship with food and where it comes from. Food is our way to connect with others and to be social. Our shopping experience has found a hybrid life virtually and physically using the latest in computer vision and robotics technologies.  Here are three few ways your grocery experience has been transformed. RoboticsSmart cartsDark Stores and Ghost Kitchens Pickup on Aisle 3! Robots in Store and Behind the Scenes In an effort to protect shoppers, cashiers, and the countless essential workers who kept everyone in food and sundries, some groceries have opted for a robotic assist. What do these robots do? Think hazard warnings, inventory control, and a device workers can turn to for help with items on the highest warehouse shelf. No more lugging the step or extension ladder. While they can’t do everything at once. These robots can assist humans where help is most needed.  There is no one-size-fits-all robot. Each is equipped with its own unique speciality. Where one robot warns shoppers and employees of spills in both Spanish and English, another alerts staff to misplaced products or out-of-stock items. When it comes to inventory, the early days of COVID-19 showed how imperative it was to keep necessary items fully stocked. Anyone else remember the run-on toilet paper? Using Machine Learning and Computer Vision to identify spills, out-of-stock items, or misplaced products, these robots make the rounds giving workers more time to focus on customers. Smart Carts ID Preferences Imagine a self-checkout right from your shopping cart. Lined up next to traditional shopping carts or buggies, these branded smart carts take note of what is being put into them. It may make recommendations of additional items or recipes from what’s already in the cart. And the days of putting your product in the cart, then taking them out again to be scanned could soon be a thing of the past. Because not only can your smart cart scan both your labeled and your weighted item, it tallies your bill and allows you to pay from what is essentially a grocery counter on wheels. It’s not quite contactless. But it's close. Going Dark in Light of Pandemic-era Shopping Dark grocery stores are brick-and-mortar stores closed to the public, so they can be more efficient as fulfillment centers for the increased load of pickup and delivery options. In an effort to stay safe, more and more people turned to online shopping, and the trend shows no signs of slowing down. While online shopping, or rather online grocery shopping, isn’t new. The pandemic-related issues of close contact launched those on the fence and the demand for delivery continues.  In a Nutshell: Our Renewed Relationship with Food Last year brought a renewed relationship with our food. We used it to reconnect with our families and our friends via video. Many of us got back to our roots and creative forces sourcing local ingredients, baking and breaking bread with the loved ones. In a renewed relationship with food, we have a better understanding of what fuels us.  And in a McKinsey interview with Brian Solis, Salesforce.com’s Global Innovation Engineer explains his vision of what the future could be like in retail: “By 2030, 5G will have given way to 6G. We’ll have sensors, computer vision, artificial intelligence, augmented reality, immersive and spatial computing. How can these worlds play together in a way that is almost fantasy-like? Figuring that out takes imagination. It takes experience architecture—a new type of discipline and expertise. I wouldn’t be shocked if the best retailers in 2030 are employing game designers or spatial-computing designers.” Check out this article for other ways your grocery experience may have changed. Whether it's food, fashion, or fun, the next projects to consider are those that play together. Use your imagination and, if you’re looking for your next role in Big Data, Analytics, Computer Vision, or Robotics, Harnham may have a role for you.  Check out our current vacancies or contact one of our expert consultants to learn more.  For our West Coast Team, contact us at (415) 614 - 4999 or send an email to sanfraninfo@harnham.com.  For our Mid-West and East Coast teams contact us at (212) 796-6070 or send an email to newyorkinfo@harnham.com.  

Why You Should Always Be Learning In Data Science: Tips From Kevin Tran

Last month we sat down with Kevin Tran, a Senior Data Scientist at Stanford University, to chat about Data Science trends, improvements in the industry, and his top tips for success in the market.  As one of LinkedIn’s Top Voices of 2019 within Data & Analytics. his thoughts on the industry regularly garner hundreds of responses, with debates and discussions bubbling up in the comments from colleagues eager to offer their input.  This online reputation has allowed him to make a name for himself, building out his own little corner of the internet with his expertise. But for Tran, it’s never been about popularity. “It’s not about the numbers,” he says without hesitation. “I don’t care about posting things just to see the number of likes go up.” His goal is always connection, to speak with others and learn from them while teaching from his own background. He’s got plenty of stories from his own experiences. For him, sharing is a powerful way to lead others down a path he himself is still discovering.  When asked about the most important lesson he’s learned in the industry, he says it all boils down to staying open to new ideas.  “You have to continue to learn, and you have to learn how to learn. If you stop learning, you’ll become obsolete pretty soon, particularly in Data Science. These technologies are evolving every day. Syntax changes, model frameworks change, and you have to constantly keep yourself updated.”  He believes that one of the best ways to do that is through open discussion. His process is to share in order to help others. When he has a realisation, he wants to set it in front of others to pass along what he’s learned; he wants to see how others react to the same problem, if they agree or see a different angle. It’s vital to consider what you needed to know at that stage. Additionally, this exchange of ideas allows Tran to learn from how others tackle the same problems, as well as get a glimpse into other challenges he may have not yet encountered.  “When I mentor people, I’m still learning, myself,” Tran confesses. “There’s so much out there to learn, you can’t know it all. Data Science is so broad." At the end of the day, it all comes down to helping each other and bringing humanity back to the forefront. In fact, this was his biggest advice for both how to improve the industry and how to succeed in it. It’s a point he comes back to with some regularity in his writing. “It doesn’t matter how smart you are, stay humble and respect everyone,” one post reads. “Everyone can teach you something you don’t know.” Treating people well, understanding their needs, and consciously working to see them as people instead of numbers or titles—this, Tran argues, is how you succeed in the business. To learn and grow, you must work with people, especially people with different skills and mindsets. Navigating your career is not all technical, even in the world of Data. “The thing that cannot be automated is having a heart,” he tells me sagely. Beyond this, Tran stresses the need for a solid foundation. The one thing you can’t afford to do is take shortcuts. You have to learn the practicalities and how to apply them, but to be strong in theory as well.  Understanding what is happening underneath the code will keep you moving forward. He compares knowing the tools to learning math with a calculator. “If you take the calculator away, you still need to be able to do the work. You need the underlying skills too, so that when you’re in a situation without the calculator, you can still provide solutions.” By constantly striving to collaborate and improve, Tran believes the Data industry has the best chance of innovating successfully.  If you’re looking for a new challenge in an innovative and collaborative environment, we may have a role for you. Take a look at our latest opportunities or get in touch with one of our expert consultants to find out more. 

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