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Category: robotics/AI – Page 374

Silicon Photonics Brings a Collaborative Lidar-Radar Relationship into View

For decades, end users and systems designers have valued radar technology for its reliability. Especially in adverse weather conditions in which sensors based on other modalities are apt to fail, radar is a dependable technique offering broad application potential.

As a result of this robustness and widespread applicability, radar today is established as a standard sensing system in several high-growth technology sectors. The automotive industry, for example, has been a key driver of radar sensor miniaturization and overall performance improvements. The commercialization of radar for passenger vehicles predates the turn of the century, and radar sensors are also now commonly deployed in advanced driver-assistance systems, including for adaptive cruise control, autonomous emergency braking, and blind-spot assist.

New AI hardware on the horizon thanks to electrically programmable spintronic device

AI transformational impact is well under way. But as AI technologies develop, so too does their power consumption. Further advancements will require AI chips that can process AI calculations with high energy efficiency. This is where spintronic devices enter the equation. Their integrated memory and computing capabilities mimic the human brain, and they can serve as a building block for lower-power AI chips.

Now, researchers at Tohoku University, National Institute for Materials Science, and Japan Atomic Energy Agency have developed a new spintronic device that allows for the electrical mutual control of non-collinear antiferromagnets and ferromagnets. This means the device can switch magnetic states efficiently, storing and processing information with less energy—just like a brain-like AI chip.

The breakthrough can potentially revolutionize AI hardware via high efficiency and low energy costs. The team published their results in Nature Communications on February 5, 2025.

China shaping AI governance mechanism

The development of artificial intelligence has entered a pivotal phase. With groundbreaking advancements in large models such as ChatGPT and Sora, AI is approaching what has been termed as “technological singularity”.The allure of AI’s potential is undeniable, but its immense potential is accompanied by significant risks including deepfakes, frauds and autonomous weapons systems.

The complexities and interconnectedness of AI pose a new global challenge. Hence, building a coordinated global governance framework for AI is no longer optional; it is an urgent necessity.

AI transcends national boundaries, creating both global opportunities and risks that no country alone can manage. Hence, countries across the world need to work together to eliminate the risks.

‘ChatGPT Does 80% Of My Job’ — How AI Enables People To Work Second And Third Jobs

Basically chat gpt can allow people that need to do more jobs can actually do several if not all jobs needed. Also essentially increase ones mental capacity and mental health due to that chat gpt can be almost like an external brain interface that can do nearly any job so that people can make even more money. Also people think this would replace people I believe it augments people like Ironman from marvel comics allowing to do tasks in seconds.#Ironman

A new breed of overemployed workers has emerged, turning to artificial intelligence (AI)-powered language models like ChatGPT to handle a significant portion of their job responsibilities.

“ChatGPT does like 80% of my job,” stated one worker, while another, currently holding down four robot-performed jobs, says, “Five would be overkill.”

As the popularity of AI-powered tools like ChatGPT continues to soar, concerns are growing about the impact on the global job market. With the potential for jobs to be automated and replaced by chatbots, experts are warning of a possible future where human workers become obsolete.

Supercomputer Aurora is now available for all researchers

Aurora, the exascale supercomputer at Argonne National Laboratory, is now available to researchers worldwide, as announced by the system’s operators from the U.S. Department of Energy on January 28, 2025. One of the goals for Aurora is to train large language models for science.

According to official reports, among the world’s fastest supercomputers, there are currently only three systems that reach at least one exaflop. An exaflop is a quintillion (10¹⁸) calculations per second—that’s like a regular calculator computing continuously for 31 billion years, but completing everything in just a single second. Or, to put it briefly: exaflop supercomputers are incredibly fast.

The fastest among the swift three is El Capitan at the Lawrence Livermore National Laboratory with 1.742 exaflops per second under the HPL benchmark (High-Performance Linpack, a standardized test for measuring the computing power of supercomputers). It is followed by Frontier with 1.353 exaflops/s at the Oak Ridge National Laboratory. The trio is completed by Aurora with 1.012 exaflops/s. Incidentally, all three laboratories belong to the U.S. Department of Energy (DOE).

New camera identifies objects at speed of light, can transform robotics

Scientists have developed a new type of compact camera engineered for computer vision. Developed by scientists from the University of Washington and Princeton University, the prototype uses optics for computing and reduces power consumption. It also enables the camera to identify objects at the speed of light.

Their device also represents a new approach to the field of computer vision, a type of artificial intelligence that allows computers to recognize objects in images and video.

Ben Goertzel on DeepSeek And The Path To AGI

In this video, Dr. Ben Goertzel, CEO of SingularityNET, TrueAGI and the Artificial Superintelligence Alliance (ASI Alliance), analyzes DeepSeek LLM as an efficiency advancement rather than an AGI breakthrough. The model’s open-source implementation and technical architecture (mixture of experts and multi-token training) improve accessibility while maintaining performance. This development demonstrates the continued democratization of AI capabilities and may redirect industry focus toward alternative computing architectures and decentralized systems.

0:00 Intro.
00:33 Initial Thoughts on DeepSeek.
01:25 Efficiency Gains and Their Implications.
02:58 Technological Singularity and Rapid Advances.
04:07 DeepSeek’s Underlying Technology.
07:27 Open Source Approach and Its Benefits.
09:58 China’s Role in AI and Open Source.
12:20 Broader Implications for AI and AGI
15:42 Conclusion: The Path to Technological Singularity.

#AGI #Deepseek #AI
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SingularityNET was founded by Dr. Ben Goertzel with the mission of creating a decentralized, democratic, inclusive, and beneficial Artificial General Intelligence (AGI). An AGI is not dependent on any central entity, is open to anyone, and is not restricted to the narrow goals of a single corporation or even a single country.

The SingularityNET team includes seasoned engineers, scientists, researchers, entrepreneurs, and marketers. Our core platform and AI teams are further complemented by specialized teams devoted to application areas such as finance, robotics, biomedical AI, media, arts, and entertainment.

Website: https://singularitynet.io.

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‘AI Will Become Conscious’ — Top Neuroscientist on Artificial Intelligence and Consciousness

Moran Cerf disucssess why we dream, and goes deeper into explaining the different versions of the relevance of dreams in life.

FULL INTERVIEW — • moran cerf: neural implants, hacking…

ABOUT MORAN:
Prof. Moran Cerf is professor of business at Columbia business school. His academic research uses methods from neuroscience to understand the underlying mechanisms of our psychology, behavior changes, emotion, decisions, and dreams.

Learn More About Moran’s Work Here: https://www.morancerf.com.

Read more about my upcoming book here — https://throughconversations.substack…

// Let’s Connect //

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