Enables both DLR researchers and external drone operators to quickly test and develop Unmanned Aircraft Systems in real-life operations, the German Aerospace Center (DLR) reports.
Following the rapid advancement of artificial intelligence (AI) tools, engineers worldwide have been working on new architectures and hardware components that replicate the organization and functions of the human brain.
Most brain-inspired technologies created to date draw inspiration from the firing of brain cells (i.e., neurons), rather than mirroring the overall structure of neural elements and how they contribute to information processing.
Researchers at Tsinghua University recently introduced a new neuromorphic computational architecture designed to replicate the organization of synapses (i.e., connections between neurons) and the tree-like structure of dendrites (i.e., projections extending from the body of neurons).
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A group of physicists wants to use artificial intelligence to prove that reality doesn’t exist. They want to do this by running an artificial general intelligence as an observer on a quantum computer. I wish this was a joke. But I’m afraid it’s not.
Continue reading “AI could prove that reality doesn’t exist, physicists say” »
In this thought-provoking lecture, Prof. Jay Friedenberg from Manhattan College delves into the intricate interplay between cognitive science, artificial intelligence, and ethics. With nearly 30 years of teaching experience, Prof. Friedenberg discusses how visual perception research informs AI design, the implications of brain-machine interfaces, the role of creativity in both humans and AI, and the necessity for ethical considerations as technology evolves. He emphasizes the importance of human agency in shaping our technological future and explores the concept of universal values that could guide the development of AGI for the betterment of society.
00:00 Introduction to Jay Friedenberg.
01:02 Connecting Cognitive Science and AI
02:36 Human Augmentation and Technology.
03:50 Brain-Machine Interfaces.
05:43 Balancing Optimism and Caution in AI
07:52 Free Will vs Determinism.
12:34 Creativity in Humans and Machines.
16:45 Ethics and Value Alignment in AI
20:09 Conclusion and Future Work.
A combined team of roboticists from Stanford University and the Toyota Research Institute has found that adding audio data to visual data when training robots helps to improve their learning skills. The team has posted their research on the arXiv preprint server.
The researchers noted that virtually all training done with AI-based robots involves exposing them to a large amount of visual information, while ignoring associated audio. They wondered if adding microphones to robots and allowing them to collect data regarding how something is supposed to sound as it is being done might help them learn a task better.
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One of the primary goals of the Large Hadron Collider (LHC) experiments is to look for signs of new particles, which could explain many of the unsolved mysteries in physics. Often, searches for new physics are designed to look for one specific type of new particle at a time, using theoretical predictions as a guide. But what about searching for unpredicted – and unexpected – new particles?
Sifting through the billions of collisions that occur in the LHC experiments without knowing exactly what to look for would be a mammoth task for physicists. So, instead of combing through the data and looking for anomalies, the ATLAS and CMS collaborations are letting artificial intelligence (AI) streamline the process.
The World Intellectual Property Organization – @WIPO publishes the “Patent Landscape Report on Generative AI.” https://www.wipo.int/web-publications/patent-landscape-repor…index.html.
- 54,000 GenAI-related inventions (patent families) were filed and more…
Generative AI is booming. It is a cutting-edge technology that is poised to disrupt various economic, social, and cultural sectors, and it extends far beyond simple human-like text generation using chatbots. Drawing on original analysis of patent and scientific data, the WIPO patent landscape report on Generative AI provides a snapshot of the patent situation for GenAI.
Continue reading “Patent Landscape Report — Generative Artificial Intelligence (GenAI)” »
Sophisticated spacecraft often run on shockingly outdated computing systems: consider that the Perseverance rover runs on a PowerPC 750, the processor famous for running on iMacs in the late 1990s.
San Francisco-based Aethero is aiming to bring more powerful computing systems to orbit, and their first payload launches this month on SpaceX’s Transporter-11 rideshare mission. The computer, a small, stackable MVP called AetherNxN that’s built on an Nvidia Orin processor, will be getting extra protection from a new radiation shielding material that the product’s developers, Cosmic Shielding Corporation (CSC), say could help unlock a new era for computing in space.
Today, electronics in space are protected from harmful radiation in two ways. They’re physically shielded, using some combination of materials like aluminum and tantalum, and they’re radiation hardened, which generally means that they’re designed in ways that increase their tolerance to radiation exposure. The AetherNxN computer is rad-hardened, but adding CSC’s shielding “enables us to bring that AI-capable of hardware into space and have it operate under these very hostile conditions,” Aethero cofounder Edward Ge said in a recent interview.
