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Category: robotics/AI – Page 800

For about a year and a half, Coca-Cola has experimented with limited-edition beverages that have mystery tastes — most of them with vague, futuristic concepts and undisclosed flavors.

The latest one, Coca-Cola Y3000, fits the bill. The one distinction: It’s supposed to taste like the future. Fittingly, the soft-drink giant used artificial intelligence to help determine the flavor and packaging.

It’s important for Coca-Cola to keep customers — particularly younger ones — excited about Coke, its more-than-a-century-old signature product. In recent years, health-conscious consumers have shied away from sugary beverages, making it trickier for soda sellers to market their legacy brands. Coca-Cola has used its Creations platform, responsible for limited-edition flavors like Y3000, to try to make the brand resonate with younger consumers.

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Companies are struggling with where to start with generative AI. The authors’ case studies, based on their growing global community of over 3,000 GenAI practitioners, point to a new category of work, more precise and actionable than “knowledge work.” They call it WINS Work — the places where tasks, functions, possibly your entire company or industry — are dependent on the manipulation and interpretation of Words, Images, Numbers, and Sounds (WINS). This framework can help leaders identify how vulnerable their business is to changes from this new technology and plan their response.

Page-utils class= article-utils—vertical hide-for-print data-js-target= page-utils data-id= tag: blogs.harvardbusiness.org, 2007/03/31:999.362921 data-title= Where Should Your Company Start with GenAI? data-url=/2023/09/where-should-your-company-start-with-genai data-topic= AI and machine learning data-authors= Paul Baier; Jimmy Hexter; John J. Sviokla data-content-type= Digital Article data-content-image=/resources/images/article_assets/2023/09/Sep23_09_AlexWilliam-383x215.jpg data-summary=

Understand where your company stands — and what it needs to do.

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A Meta team, hand-picked by Zuckerberg, is working on the new AI tool.

Meta will unveil a superior artificial intelligence model in 2024, which is touted to be on par with the most powerful model created by OpenAI, the company that birthed ChatGPT and is backed by Microsoft, reported The Wall Street Journal.

WSJ spoke to people familiar with the matter, most likely Meta insiders, who said that the new model would be two times more advanced than Llama 2, the open-source large language model launched by Meta in July and distributed by Microsoft’s cloud Azure services.

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German scientists present a method by which AI could be trained much more efficiently.

In the last couple of years, research institutions have been working on finding new concepts of how computers can process data in the future. One of these concepts is known as neuromorphic computing. Neuromorphic computing models may sound similar to artificial neural networks but have little to do with them.

Compared to traditional artificial intelligence algorithms, which require significant amounts of data to be trained on before they can be effective, neuromorphic computing systems can learn and adapt on the fly.

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On Thursday, AI-maker and OpenAI competitor Anthropic launched Claude Pro, a subscription-based version of its Claude.ai web-based AI assistant, which functions similarly to ChatGPT. It’s available for $20/month in the US or 18 pounds/month in the UK, and it promises five-times-higher usage limits, priority access to Claude during high-traffic periods, and early access to new features as they emerge.

Like ChatGPT, Claude Pro can compose text, summarize, do analysis, solve logic puzzles, and more.

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Strategic agreement calls for fleet of Boston Dynamics robots to be deployed across more than 20 facilities over the next two years, to position retailer for the future.

Hamburg, Germany / Waltham, MA, USA – September 11, 2023 – The Otto Group, one of the world’s largest e-commerce retailers, has signed a strategic agreement with Boston Dynamics, the global leader in mobile robotics, to continue automating its logistics operations. The plan is to deploy Boston Dynamics’ Spot® robots in more than 10 and Stretch™ robots in more than 20 of the group’s facilities over the next two years, beginning with Hermes Fulfilment. The deployment supports Otto Group’s efforts to improve safety, increase operational efficiency and address labor shortages for specific types of warehouse work and the agreement marks the first time both of Boston Dynamics’ commercially available robots will be deployed together at enterprise scale.

Under the terms of the agreement, Spot, the four-legged mobile robot from Boston Dynamics, will support tunnel inspections and predictive maintenance activities for operations equipment, including thermal monitoring, analog gauge reading and acoustic detection of pressurized air and gas leaks. The Spot fleet will also run autonomous missions, collecting data for machine learning models to support tasks like fire exit egress monitoring and detecting slight changes in storage racks to keep Otto Group’s warehouses even safer. In addition, the Otto Group will be utilizing Stretch, Boston Dynamics’ box-moving robot designed for warehouse applications. Stretch will begin unloading containers at 10 facilities next year, with the goal of having all sites operational by the end of 2025. Stretch, which is particularly useful for unloading heavy packages in the container sector, will provide technological support for physically demanding activities.

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A machine-learning algorithm demonstrated the capability to process data that exceeds a computer’s available memory by identifying a massive data set’s key features and dividing them into manageable batches that don’t choke computer hardware. Developed at Los Alamos National Laboratory, the algorithm set a world record for factorizing huge data sets during a test run on Oak Ridge National Laboratory’s Summit, the world’s fifth-fastest supercomputer.

Equally efficient on laptops and supercomputers, the highly scalable solves hardware bottlenecks that prevent processing information from data-rich applications in , , social media networks, national security science and earthquake research, to name just a few.

“We developed an ‘out-of-memory’ implementation of the non-negative matrix factorization method that allows you to factorize larger than previously possible on a given hardware,” said Ismael Boureima, a computational physicist at Los Alamos National Laboratory. Boureima is first author of the paper in The Journal of Supercomputing on the record-breaking algorithm.

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This talk is about how you can use wireless signals and fuse them with vision and other sensing modalities through AI algorithms to give humans and robots X-ray vision to see objects hidden inside boxes or behind other object.

Tara Boroushaki is a Ph.D student at MIT. Her research focuses on fusing radio frequency (RF) sensing with vision through artificial intelligence. She designs algorithms and builds systems that leverage such fusion to enable capabilities that were not feasible before in applications spanning augmented reality, virtual reality, robotics, smart homes, and smart manufacturing. This talk was given at a TEDx event using the TED conference format but independently organized by a local community.

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