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The technology was recently demonstrated by the Australian Army, where soldiers operated a Ghost Robotics quadruped robot using the brain-machine interface. Photo supplied by Australian Army. #Graphene

New technology is making mind reading possible with positive implications for the fields of healthcare, aerospace and advanced manufacturing.

Researchers from the University of Technology Sydney (UTS) have developed biosensor technology that will allow you to operate devices, such as robots and machines, solely through thought-control.

Continue reading “Mind-control robots a reality” »

Artificial Intelligence is breaking new barriers by the day. Hundreds of worshippers at St. Paul’s Church in Fürth, Bavaria, Germany recently attended a service, entirely conducted by AI with the sermon being presented by the AI chatbot ChatGPT.

An hour before the service even began, people formed a long queue outside the 19th-century, neo-Gothic building to witness what the AI could deliver.

The chatbot’s sermon majorly focused on themes surrounding leaving one’s past behind, living in the present, not being afraid of death and maintaining faith in Jesus Christ. Notably, four different AI avatars took turns to impart the sermons and lead the service.

AI, machine learning, and ChatGPT may be relatively new buzzwords in the public domain, but developing a computer that functions like the human brain and nervous system—both hardware and software combined—has been a decades-long challenge. Engineers at the University of Pittsburgh are today exploring how optical “memristors” may be a key to developing neuromorphic computing.

Resistors with memory, or memristors, have already demonstrated their versatility in electronics, with applications as computational circuit elements in neuromorphic computing and compact memory elements in high-density data storage. Their unique design has paved the way for in-memory computing and captured significant interest from scientists and engineers alike.

A new review article published in Nature Photonics, titled “Integrated Optical Memristors,” sheds light on the evolution of this technology—and the work that still needs to be done for it to reach its full potential.

Dr. Ben Goertzel shares his thoughts on where we are at the end of 2021, beginning of 2022 — how progress toward AGI looks in retrospect, and looking into the future — updates on the ecosystem…

And the importance of the SingularityNET Community 🥰
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Continue reading “Ben Goertzel — 2021 Reflection and Update on SNET, Ecosystem and Path to AGI” »

For example, scientists have recently emphasized that the physical organization of the Universe mirrors the structure of a brain. Theoretical physicist Sabine Hossenfelder — renowned for her skepticism — wrote a bold article for Time Magazine in August of 2022 titled “Maybe the Universe Thinks. Hear Me Out,” which describes the similarities. Like our nervous system, the Universe has a highly interconnected, hierarchical organization. The estimated 200 billion detectable galaxies aren’t distributed randomly, but lumped together by gravity into clusters that form even larger clusters, which are connected to one another by “galactic filaments,” or long thin threads of galaxies. When one zooms out to envision the cosmos as a whole, the “cosmic web” formed by these clusters and filaments looks strikingly similar to the “connectome,” a term that refers to the complete wiring diagram of the brain, which is formed by neurons and their synaptic connections. Neurons in the brain also form clusters, which are grouped into larger clusters, and are connected by filaments called axons, which transmit electrical signals across the cognitive system.

Hossenfelder explains that this resemblance between the cosmic web and the connectome is not superficial, citing a rigorous study by a physicist and a neuroscientist that analyzed the features common to both, and based on the shared mathematical properties, concluded that the two structures are “remarkably similar.” Due to these uncanny similarities, Hossenfelder speculates as to whether the Universe itself could be thinking.

Unlock the power of synthetic data in AI innovation. Discover its benefits in privacy, scalability, and diversity for advanced machine learning models.

ChatGPT and other generative AI tools have captured the public imagination. Here’s how you can turn a much hyped tool into a productivity boon.

Computer scientists have, for decades, been optimizing how computers sort data to shave off crucial milliseconds in returning search results or alphabetizing contact lists. Now DeepMind, based in London, has vastly improved sorting speeds by applying the technology behind AlphaZero — its artificial-intelligence system for playing the board games chess, Go and shogi — to a game of building sorting algorithms. “This is an exciting result,” said Emma Brunskill, a computer scientist at Stanford University, California.

The system, AlphaDev, is described in a paper in Nature¹, and has invented faster algorithms that are already part of two standard C++ coding libraries, so are being used trillions of times per day by programmers around the world.

Unlike many of his peers in the artificial intelligence community, Andrew Ng isn’t convinced about the dangers of AI.

In a video posted to Twitter this week, Ng, a Stanford University professor and founder of several Silicon Valley AI startups, expressed doubt about the doomsday predictions of other executives and experts in the field.