Organizations have to figure out the potential implications of tapping generative artificial intelligence tools, such as ChatGPT, while consumers should consider how they establish digital engagement.
Category: robotics/AI – Page 1,531
Researcher develops poetic generative AI applications rivaling ChatGPT
Despite its popularity, ChatGPT has been criticized for generating unreliable and biased search results. A recent media report, for example, concluded that ‘ChatGPT Is Pretty Bad At Poetry, According To Poets.’ Yet that doesn’t mean that the literary ability of all AI should be discounted, applications created by INSEAD’s AI lab using exacting rules can potentially be more useful and reliable than ChatGPT.
Artificial intelligence is now capable of defeating fighter pilots in aerial combat
Artificial intelligence (AI) is continuing to advance and has now defeated a human fighter pilot in a virtual combat simulation.
This result was achieved in the US Army’s AlphaDogfight competition, which aimed to demonstrate the feasibility of developing autonomous agents capable of defeating enemy aircraft in aerial combat.
Eight teams participated in a series of tests and in the final last Thursday, Heron Systems was declared the winner after two days of aerial combat using only nose-mounted guns.
Amazon opens robotic fulfillment center in Connecticut
Amazon opened a robotics fulfillment center in Windsor, Connecticut, where workers will process orders alongside bots.
The 3.8 million square-foot facility will have “thousands of robotic systems such as mobile robots and robotic handling systems that help employees deliver for customers everyday,” an Amazon spokesperson told Supply Chain Dive.
More than 2,000 employees will work at the facility, which primarily handles smaller shipments such as books, electronics and toys. The company began processing and delivering customer orders in November 2022, according to a press release.
Toyota’s Latest Concept Car: The LQ, Redefining the Relationship Between Driver and AI
Toyota’s latest electric LQ concept car satisfies the “huмan need to Ƅe engaged eмotionally” with an on-Ƅoard artificial intelligence agent naмed Yui.
The Toyota LQ is Ƅoth fully electric and equipped with an SAE leʋel four equiʋalent autoмated driʋing systeм, мeaning no huмan interʋention is needed to driʋe the ʋehicle.
Its мain feature howeʋer is the on-Ƅoard AI-powered, interactiʋe agent, called Yui, which proʋides a personalised мoƄility experience Ƅy learning and responding to the driʋer’s eмotional and physical state.
Czinger’s Bonkers New 3D-Printed Hypercar Could Spark an Automaking Revolution
Helmeted and harnessed directly behind my pilot, I prepare for takeoff as the cockpit canopy shuts over us. It could be a scene from Top Gun: Maverick save for the fact that we’re not launching from an aircraft carrier but pulling out of pit lane at the Thermal Club’s track in a final prototype of the Czinger 21C hypercar.
The $2 million, carbon-fiber-bodied, tandem-seat Czinger 21C astounds with specs—1,250 hp, zero to 62 mph in 1.9 seconds, a claimed top speed of 253 mph—and recently blew away the McLaren P1’s production-car track record at Circuit of the Americas by six seconds. But more impressive—seriously—is the hybrid’s build process: The main structural components are designed by Czinger’s proprietary AI software and then 3D-printed. “These structures cannot be made more perfect for the requirements inputted,” says Kevin Czinger, who, along with his son Lukas, cofounded Los Angeles–based Czinger Vehicles. “You could have 1,000 engineers and they would never get to this solution.”
Researchers use generative AI to design novel proteins
Researchers at the University of Toronto have developed an artificial intelligence system that can create proteins not found in nature using generative diffusion, the same technology behind popular image-creation platforms such as DALL-E and Midjourney.
The system will help advance the field of generative biology, which promises to speed drug development by making the design and testing of entirely new therapeutic proteins more efficient and flexible.
“Our model learns from image representations to generate fully new proteins, at a very high rate,” says Philip M. Kim, a professor in the Donnelly Centre for Cellular and Biomolecular Research at U of T’s Temerty Faculty of Medicine. “All our proteins appear to be biophysically real, meaning they fold into configurations that enable them to carry out specific functions within cells.”
Chemists find that metal atoms play key role in fine organic synthesis
A small team of chemists at the Russian Academy of Sciences, has found that metal atoms, not nanoparticles, play the key role in catalysts used in fine organic synthesis. In the study, reported in the Journal of the American Chemical Society, the group used multiple types of electron microscopy to track a region of a catalyst during a reaction to learn more about how it was proceeding.
Prior research has shown that there are two main methods for studying a reaction. The first is the most basic: As ingredients are added, the reaction is simply observed and/or measured. This can be facilitated through use of high-speed cameras. This approach will not work with nanoscale reactions, of course. In such cases, chemists use a second method: They attempt to capture the state of all the components before and after the reaction and then compare them to learn more about what happened.
This second approach leaves much to be desired, however, as there is no way to prove that the objects under study correspond with one another. In recent years, chemists have been working on a new approach: Following the action of a single particle during the reaction. This new method has proven to have merit but it has limitations as well—it also cannot be used for reactions that occur in the nanoworld. In this new effort, the researchers used multiple types of electron microscopy coupled with machine-learning algorithms.
AI could run a million microbial experiments per year, says study
An artificial intelligence system enables robots to conduct autonomous scientific experiments—as many as 10,000 per day—potentially driving a drastic leap forward in the pace of discovery in areas from medicine to agriculture to environmental science.
Reported today in Nature Microbiology, the research was led by a professor now at the University of Michigan.
That artificial intelligence platform, dubbed BacterAI, mapped the metabolism of two microbes associated with oral health —with no baseline information to start with. Bacteria consume some combination of the 20 amino acids needed to support life, but each species requires specific nutrients to grow. The U-M team wanted to know what amino acids are needed by the beneficial microbes in our mouths so they can promote their growth.