Shelf-scanning robot Tally will be donning a new apron soon. Simbe, the company that makes the robot, announced its first deployment with Save Mart, the largest family owned grocery chain in California, which acquired 132 Albertsons stores in 2006 has continued growing. Tally robots will be rolling out to 7 stores across all three Save Mart banners in the Bay Area to bring greater visibility to inventory, streamline operations for store teams and improve the customer experience. This is an important milestone for a sector that's been fixated on wider adoption and sees a real opportunity in the shadow of COVID-19, despite notable setbacks and some in the industry questioning the value of retail robotics late last year. In November 2020, Walmart killed a large contract with Simbe competitor Bossa Nova, which also makes a robot for inventory auditing and data-driven inventory insights.
Machine learning MLSys 2021: Bridging the divide between machine learning and systems Amazon distinguished scientist and conference general chair Alex Smola on what makes MLSys unique -- both thematically and culturally. Email Alex Smola, Amazon vice president and distinguished scientist The Conference on Machine Learning and Systems ( MLSys), which starts next week, is only four years old, but Amazon scientists already have a rich history of involvement with it. Amazon Scholar Michael I. Jordan is on the steering committee; vice president and distinguished scientist Inderjit Dhillon is on the board and was general chair last year; and vice president and distinguished scientist Alex Smola, who is also on the steering committee, is this year's general chair. As the deep-learning revolution spread, MLSys was founded to bridge two communities that had much to offer each other but that were often working independently: machine learning researchers and system developers. Registration for the conference is still open, with the very low fees of $25 for students and $100 for academics and professionals. "If you look at the big machine learning conferences, they mostly focus on, 'Okay, here's a cool algorithm, and here are the amazing things that it can do. And by the way, it now recognizes cats even better than before,'" Smola says. "They're conferences where people mostly show an increase in capability. At the same time, there are systems conferences, and they mostly care about file systems, databases, high availability, fault tolerance, and all of that. "Now, why do you need something in-between? Well, because quite often in machine learning, approximate is good enough. You don't necessarily need such good guarantees from your systems.
"Mitchell knows what she's talking about. Artificial Intelligence has significantly improved my knowledge when it comes to automation technology, [but] the greater benefit is that it has also enhanced my appreciation for the complexity and ineffability of human cognition."―John Warner, Chicago Tribune "Without shying away from technical details, this survey provides an accessible course in neural networks, computer vision, and natural-language processing, and asks whether the quest to produce an abstracted, general intelligence is worrisome . . . Mitchell's view is a reassuring one." AI isn't for the faint of heart, and neither is this book for nonscientists . . .
Apple will discontinue its original HomePod four years after first releasing the smart speaker. The Cupertino, California-based tech giant says it will instead focus on its new and smaller HomePod mini, which went on sale in November for $99. "We are discontinuing the original HomePod, it will continue to be available while supplies last through the Apple Online Store, Apple Retail Stores and Apple Authorized Resellers," Apple said in a statement, reported by TechCrunch. "We are focusing our efforts on HomePod mini." Apple didn't immediately respond Saturday to USA TODAY's request for comment.
Chris Fregly is a Developer Advocate for AI and Machine Learning at Amazon Web Services (AWS) based in San Francisco, California. He is also the founder of the Advanced Spark, TensorFlow, and KubeFlow Meetup Series based in San Francisco. Chris regularly speaks at AI and Machine Learning conferences across the world including the O'Reilly AI, Strata, and Velocity Conferences. Previously, Chris was Founder at PipelineAI where he worked with many AI-first startups and enterprises to continuously deploy ML/AI Pipelines using Apache Spark ML, Kubernetes, TensorFlow, Kubeflow, Amazon EKS, and Amazon SageMaker. He is also the author of the O'Reilly Online Training Series "High Performance TensorFlow in Production with GPUs" Antje Barth is a Developer Advocate for AI and Machine Learning at Amazon Web Services (AWS) based in Düsseldorf, Germany.
Nowadays, retail industry is in a constant state of transformation. The sector highly depends on data from its own operations and customer analysis as a whole to make crucial decisions. The retailers are attempting to survive the fierce competition on the market and fast-changing customer shopping habits using technology. Artificial intelligence in retail industry comes with several benefits such as predictive merchandising, programmatic advertising, market forecasting, in-store visual monitoring & surveillance, and location-based marketing. The implementation of technology has impacted constant changes in CRM and sales, manufacturing, logistics and customer service.
'An excellent book that treats the fundamentals of machine learning from basic principles to practical implementation. The book is suitable as a text for senior-level and first-year graduate courses in engineering and computer science. It is well organized and covers basic concepts and algorithms in mathematical optimization methods, linear learning, and nonlinear learning techniques. The book is nicely illustrated in multiple colors and contains numerous examples and coding exercises using Python.' John G. Proakis, University of California, San Diego'Some machine learning books cover only programming aspects, often relying on outdated software tools; some focus exclusively on neural networks; others, solely on theoretical foundations; and yet more books detail advanced topics for the specialist.
In the past year, lockdowns and other COVID-19 safety measures have made online shopping more popular than ever, but the skyrocketing demand is leaving many retailers struggling to fulfill orders while ensuring the safety of their warehouse employees. Researchers at the University of California, Berkeley, have created new artificial intelligence software that gives robots the speed and skill to grasp and smoothly move objects, making it feasible for them to soon assist humans in warehouse environments. The technology is described in a paper published online today (Wednesday, Nov. 18) in the journal Science Robotics. Automating warehouse tasks can be challenging because many actions that come naturally to humans -- like deciding where and how to pick up different types of objects and then coordinating the shoulder, arm and wrist movements needed to move each object from one location to another -- are actually quite difficult for robots. Robotic motion also tends to be jerky, which can increase the risk of damaging both the products and the robots.
Artificial intelligence stocks are rarer than you might think. Many companies tout AI technology initiatives and machine learning. But there really are few -- if any -- public, pure-play artificial intelligence stocks. The "AI" stock ticker, though, has been claimed. Startup C3.ai, which sells AI software for the enterprise market, filed on Nov. 13 for an initial public offering. Thomas Siebel, who started Siebel Systems and sold it to Oracle for nearly $6 billion in 2006, founded Redwood City, Calif.-based C3.ai.
Tango Eye, a Chennai-based AI video analytics startup that converts CCTV data into actionable insights, has raised an undisclosed amount of seed funding led by Delhi-based eyewear retailer Lenskart, which entered the elite unicorn club last year. Silicon Valley-based seed fund RiSo capital and angel investor Gaurav Gulati, Co-founder, Innov8 (acquired by Oyo) also participated in the round. Currently implemented at about 1,000 outlets, the startup said the new funding will help scale to 10,000 outlets in addition to expanding the product features. In a release, Tango Eye said that this investment will enable Lenskart to enhance customer experience, security and safety protocols in stores, and merchandising placement, among others. Founded in 2018, Tango Eye uses AI and Computer Vision to deliver a SaaS solution that utilises existing CCTV cameras to measure social distancing, improve sales conversion, optimise product placement and monitor SOPs across retail outlets.