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Category: robotics/AI – Page 12

The Non-Singular Singularity

Part 1 of the Singularity Series was “Putting Brakes on the Singularity.” That essay looked at how economic and other non-technical factors will slow down the practical effects of AI, and we should question the supposedly immediate move from AGI to SAI (superintelligent AI).

In part 3, I will consider past singularities, different paces for singularities, and the difference between intelligence and speed accelerations.

In part 4, I will follow up by offering alternative models of AI-driven progress.

What comes after agentic AI? This powerful new technology will change everything

Ten years from now, it will be clear that the primary ways we use generative AI circa 2025—rapidly crafting content based on simple instructions and open-ended interactions—were merely building blocks of a technology that will increasingly be built into far more impactful forms.

The real economic effect will come as different modes of generative AI are combined with traditional software logic to drive expensive activities like project management, medical diagnosis, and insurance claims processing in increasingly automated ways.

In my consulting work helping the world’s largest companies design and implement AI solutions, I’m finding that most organizations are still struggling to get substantial value from generative AI applications. As impressive and satisfying as they are, their inherent unpredictability makes it difficult to integrate into the kind of highly standardized business processes that drive the economy.

A look at the next big iteration of the transformative technology.

NVIDIA Unveils ‘Mega’ Omniverse Blueprint for Building Industrial Robot Fleet Digital Twins

According to Gartner, the worldwide end-user spending on all IT products for 2024 was $5 trillion. This industry is built on a computing fabric of electrons, is fully software-defined, accelerated — and now generative AI-enabled. While huge, it’s a fraction of the larger physical industrial market that relies on the movement of atoms. Today’s 10 Read Article

What Comes After the LLM: Human-Centered AI, Spatial Intelligence, and the Future of Practice

In a recent episode of High Signal, we spoke with Dr. Fei-Fei Li about what it really means to build human-centered AI, and where the field might be heading next.

Fei-Fei doesn’t describe AI as a feature or even an industry. She calls it a “civilizational technology”—a force as foundational as electricity or computing itself. This has serious implications for how we design, deploy, and govern AI systems across institutions, economies, and everyday life.

Our conversation was about more than short-term tactics. It was about how foundational assumptions are shifting, around interface, intelligence, and responsibility, and what that means for technical practitioners building real-world systems today.

Spatial computing, wearables and robots: AI’s next frontier

Spatial computing, an emerging 3D-centric computing model, merges AI, computer vision and sensor technologies to create fluid interfaces between the physical and digital. Unlike traditional models, which require people to adapt to screens, spatial computing allows machines to understand human environments and intent through spatial awareness.

Recent trademark filings and product launches show AI companies targeting the physical world with wearables and robots driven by complex spatial computing.

Robots with a collective brain: The revolution of shared intelligence

In a world where automation is advancing by leaps and bounds, collaboration between robots is no longer science fiction. Imagine a warehouse where dozens of machines transport goods without colliding, a restaurant where robots serve dishes to the correct tables, or a factory where robot teams instantly adjust their tasks according to demand.

Advancing earthquake prediction with an unmanned aerial vehicle

Megathrust earthquakes are large earthquakes that occur on faults found along the boundaries between tectonic plates. The Nankai Trough is a megathrust earthquake zone lying off the southwestern coast of Japan, and experts estimate that this zone could generate a potentially devastating (magnitude 8 or 9) large earthquake sometime in the next 30 years. In addition to the direct catastrophic impact of such powerful ground shaking, a seismic event of this magnitude could trigger cascading hazards such as destructive tsunamis.

Developing the technologies for efficient and reliable seafloor monitoring is paramount when considering the potential for socioeconomic harm represented by megathrust earthquakes. Traditionally, seafloor measurements have been obtained using transponder stations located on the seafloor that communicate with satellites via buoys or ocean-going vessels to produce accurate positional information. However, data collection using such systems has problems such as low efficiency and speed.

In a study published in Earth and Space Science, researchers at Institute of Industrial Science, The University of Tokyo, addressed the challenge of acquiring reliable, high-precision, real-time seafloor measurements by constructing a seaplane-type unmanned aerial vehicle (UAV) that can withstand ocean currents and wind. This vehicle is intended for use with the Global Navigation Satellite System-Acoustic (GNSS-A)―a system that uses satellites to determine locations on Earth―to provide a communication link with seafloor transponder stations.

For the first time, researchers at #UTokyo_IIS, quickly and efficiently measure the seafloor down to the centimeter-level using an unmanned aerial vehicle.

Thermodynamic computing system for AI applications

Recent breakthroughs in artificial intelligence (AI) algorithms have highlighted the need for alternative computing hardware in order to truly unlock the potential for AI. Physics-based hardware, such as thermodynamic computing, has the potential to provide a fast, low-power means to accelerate AI primitives, especially generative AI and probabilistic AI. In this work, we present a small-scale thermodynamic computer, which we call the stochastic processing unit. This device is composed of RLC circuits, as unit cells, on a printed circuit board, with 8 unit cells that are all-to-all coupled via switched capacitances. It can be used for either sampling or linear algebra primitives, and we demonstrate Gaussian sampling and matrix inversion on our hardware. The latter represents a thermodynamic linear algebra experiment. We envision that this hardware, when scaled up in size, will have significant impact on accelerating various probabilistic AI applications.

#Repost Nature Publishing

Current digital hardware struggles with high computational demands in applications such as probabilistic AI. Here, authors present a small-scale thermodynamic computer composed of eight RLC circuits, demonstrating Gaussian sampling and matrix inversion, suggesting potential speed and energy efficiency advantages over digital GPUs.

New Graphene Technology Matures Brain Organoids Faster, May Unlock Neurodegenerative Insights

Researchers from University of California San Diego Sanford Stem Cell Institute have developed a novel method to stimulate and mature human brain organoids using graphene, a one-atom-thick sheet of carbon. Published in Nature Communications, the study introduces Graphene-Mediated Optical Stimulation (GraMOS), a safe, non-genetic, biocompatible, non-damaging way to influence neural activity over days to weeks. The approach accelerates brain organoid development — especially important for modeling age-related conditions like Alzheimer’s disease — and even allows them to control robotic devices in real time.

“This is a game-changer for brain research,” said Alysson Muotri, Ph.D., corresponding author, professor of pediatrics, and director of the UC San Diego Sanford Stem Cell Institute Integrated Space Stem Cell Orbital Research Center. “We can now speed up brain organoid maturation without altering their genetic code, opening doors for disease research, brain–machine interfaces and other systems combining living brain cells with technology.”

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