Looks like inventory robots wonât be replacing humans in Walmart for now. đ
Iâm a bit sad for the supplier of the robots. But Iâm glad that people will keep their jobs in Walmart.
Bitter Reality
Continue reading “Walmart Is Giving Up on Its Inventory Robots” »
Military observers said the disruptive technologies â those that fundamentally change the status quo â might include such things as sixth-generation fighters, high-energy weapons like laser and rail guns, quantum radar and communications systems, new stealth materials, autonomous combat robots, orbital spacecraft, and biological technologies such as prosthetics and powered exoskeletons.
Speeding up the development of âstrategic forward-looking disruptive technologiesâ is a focus of the countryâs latest five-year plan.
EPFL engineers have developed a computer chip that combines two functionsâlogic operations and data storageâinto a single architecture, paving the way to more efficient devices. Their technology is particularly promising for applications relying on artificial intelligence.
Itâs a major breakthrough in the field of electronics. Engineers at EPFLâs Laboratory of Nanoscale Electronics and Structures (LANES) have developed a next-generation circuit that allows for smaller, faster and more energy-efficient devicesâwhich would have major benefits for artificial-intelligence systems. Their revolutionary technology is the first to use a 2-D material for whatâs called a logic-inâmemory architecture, or a single architecture that combines logic operations with a memory function. The research teamâs findings appear today in Nature.
Until now, the energy efficiency of computer chips has been limited by the von Neumann architecture they currently use, where data processing and data storage take place in two separate units. That means data must constantly be transferred between the two units, using up a considerable amount of time and energy.
The Float is a concept car by Yunchen Chai. It won the design competition hosted by Renault and Central Saint Martins. The participants of the competition had to design a car that emphasized electric power, autonomous driving, and connected technology.
This car uses Meglev technology, is non-directional, and a magnetic belt to attach multiple pods. The Float would even come with an app. This could be the future of car design.
Blizzard president J. Allen Brack said the system has dramatically reduced toxic chat and repeating offenses.
In April 2019, Blizzard shared some insights into how it was using machine learning to combat abusive chat in games like Overwatch. Itâs a very complicated process, obviously, but it appears to be working out: Blizzard president J. Allen Brack said in a new Fireside Chat video that it has resulted in an âincredible decreaseâ in toxic behavior.
Artificial intelligence helps scientists make discoveries, but not everyone can understand how it reaches its conclusions. One UMaine computer scientist is developing deep neural networks that explain their findings in ways users can comprehend, applying his work to biology, medicine and other fields.
Interpretable machine learning, or AI that creates explanations for the findings it reaches, defines the focus of Chaofan Chenâs research. The assistant professor of computer science says interpretable machine learning also allows AI to make comparisons among images and predictions from data, and at the same time, elaborate on its reasoning.
Scientists can use interpretable machine learning for a variety of applications, from identifying birds in images for wildlife surveys to analyzing mammograms.
How do you *feel* about that?
Much of todayâs discussion around the future of artificial intelligence is focused on the possibility of achieving artificial general intelligence. Essentially, an AI capable of tackling an array of random tasks and working out how to tackle a new task on its own, much like a human, is the ultimate goal. But the discussion around this kind of intelligence seems less about if and more about when at this stage in the game. With the advent of neural networks and deep learning, the sky is the actual limit, at least that will be true once other areas of technology overcome their remaining obstructions.
For deep learning to successfully support general intelligence, itâs going to need the ability to access and store much more information than any individual system currently does. Itâs also going to need to process that information more quickly than current technology will allow. If these things can catch up with the advancements in neural networks and deep learning, we might end up with an intelligence capable of solving some major world problems. Of course, we will still need to spoon-feed it since it only has access to the digital world, for the most part.
Continue reading “The Future of AI is Artificial Sentience” »
Woah o,.o!
In recent years, artificial intelligence (AI) tools, including natural language processing (NLP) techniques, have become increasingly sophisticated, achieving exceptional results in a variety of tasks. NLP techniques are specifically designed to understand human language and produce suitable responses, thus enabling communication between humans and artificial agents.
Other studies also introduced goal-oriented agents that can autonomously navigate virtual or videogame environments. So far, NLP techniques and goal-oriented agents have typically been developed individually, rather than being combined into unified methods.
Continue reading “Teaching AI agents to communicate and act in fantasy worlds” »
I highly recommend checking this fantastic look at Deep Blue and the fascinating role chess has played in the ongoing development of artificial intelligence.
After an electrical engineer enters the field of computer chess, his creation captures the attention of the world as he attempts to defeat the world chess champion.
