If we take the mortal danger of the “Tic-Tac” UAP maneuvers literally, we need to believe that “these objects suggest a form of physics we have not yet discovered,” says one sci-fi writer.
Artificial intelligence has been infiltrating our daily workflows and routine tasks for while now. It may be AI working in the background, as with Gemini’s integration across Google products, or you may be engaging more directly with popular content generators such as OpenAI’s ChatGPT and Dall-E. Looming in the not-too-distant future are amped-up virtual assistants.
As if AI itself weren’t futuristic enough, now there’s a whole new leap forward on the horizon: quantum AI. It’s a fusion of artificial intelligence with unconventional and still largely experimental quantum computing into a super-fast and highly efficient technology. Quantum computers will be the muscles, while AI will be the brains.
Here’s a quick breakdown of the basics to help you better understand quantum AI.
Summary: Scientists have successfully reprogrammed astroglia, a type of brain support cell, into neurons that mimic specific interneurons critical for brain function. By modifying the Ascl1 protein, they increased its efficiency in converting astroglia to neuron-like cells, opening new possibilities for regenerative treatments for brain disorders such as epilepsy.
The engineered neurons exhibit high-frequency firing, a signature of certain interneurons essential for regulating brain activity. This work suggests astroglia could serve as a repair mechanism, allowing us to restore lost or damaged brain circuits.
Researchers have developed a new method using the Allen Telescope Array to search for interplanetary radio communication in the TRAPPIST-1 star system.
A new technique allows astronomers to home in on planets beyond our solar system that are in line with each other and with Earth to search for radio signals similar, for example, to ones used to communicate with the rovers on Mars. Penn State astronomers and scientists at the SETI Institute spent 28 hours scanning the TRAPPIST-1 star system for these signs of alien technology with the Allen Telescope Array (ATA). This project marks the longest single-target search for radio signals from TRAPPIST-1. Although the team didn’t find any evidence of extraterrestrial technology, their work introduced a new way to search for signals in the future.
A paper describing the research was accepted for publication in the Astronomical Journal and is available online as a preprint.
The lightbulb illuminated our world, the airplane connected it, and the iPhone put it in our pockets. Here’s the case for tech-optimism.
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The SPINNING project, under the leadership of the Fraunhofer Institute, is pioneering a quantum computer using diamond-based spin photons, promising lower cooling requirements, longer operating times, and lower error rates compared to conventional quantum systems.
This innovative approach leverages the unique properties of diamonds to create stable qubits, aiming for high scalability and fidelity in quantum computing. Recent achievements include the successful demonstration of qubit entanglement over long distances, significantly outperforming traditional quantum computers in error rate and coherence time.
The SPINNING project: innovating with diamond-based technology.
Hot AI trend consists of large behavior models (LBM), which is a combination of generative AI LLMs with behavior-oriented AI walk and talk features. Here’s the scoop.
Google Cloud recently announced a major upgrade to its AI infrastructure, introducing new hardware and software solutions designed to meet the growing demands of artificial intelligence workloads. The centerpiece of these changes is the release of Trillium, Google’s sixth-generation Tensor Processing Unit (TPU).
Compared to its predecessor, the TPU v5e, Trillium delivers over four times the training performance and up to three times the inference throughput. This improvement is accompanied by a 67% increase in energy efficiency.
The new TPU boasts impressive specifications, including double the High Bandwidth Memory (HBM) capacity and Interchip Interconnect (ICI) bandwidth, making Trillium particularly well-suited for handling large language models like Gemma 2 and Llama, as well as compute-intensive inference tasks such as those required by diffusion models like Stable Diffusion XL.
