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Category: robotics/AI – Page 7

Google Just Revealed What Comes After AGI And It’s Shocking

Google DeepMind just dropped a massive paper called From AGI to ASI, and the message is bigger than another AI release. The paper argues that AGI may not be the finish line everyone is waiting for. It may be the moment the real race begins. Once human-level AI can be copied, sped up, connected into agent teams, and used to build better AI, the jump after AGI could matter even more than AGI itself.

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📌 What You’ll See:
Google DeepMind’s new From AGI to ASI paper.
SOURCE: https://deepmind.google/research/publ… 2026 framework for tracking progress toward AGI SOURCE: https://blog.google/innovation-and-ai… DeepMind’s approach to AGI safety and security SOURCE: https://deepmind.google/blog/taking-a… Demis Hassabis on AI agents and the road to AGI SOURCE: https://www.axios.com/2026/05/26/deep… The Legg and Hutter paper behind formal machine intelligence SOURCE: https://arxiv.org/abs/cs/0605024 🚨 Why It Matters This is bigger than another AI paper. Google DeepMind is already talking about what happens after AGI. If human-level AI can be copied, sped up, connected, and used to build better AI, then intelligence itself could become an industrial process. #ai #agi #deepmind.
The full technical paper on arXiv.
SOURCE: https://arxiv.org/abs/2606.12683
DeepMind’s earlier framework for measuring AGI progress.
SOURCE: https://deepmind.google/research/publ…
Google’s 2026 framework for tracking progress toward AGI
SOURCE: https://blog.google/innovation-and-ai…
DeepMind’s approach to AGI safety and security.
SOURCE: https://deepmind.google/blog/taking-a…
Demis Hassabis on AI agents and the road to AGI
SOURCE: https://www.axios.com/2026/05/26/deep…
The Legg and Hutter paper behind formal machine intelligence.
SOURCE: https://arxiv.org/abs/cs/0605024

🚨 Why It Matters.
This is bigger than another AI paper. Google DeepMind is already talking about what happens after AGI. If human-level AI can be copied, sped up, connected, and used to build better AI, then intelligence itself could become an industrial process.

#ai #agi #deepmind

Liquid cooling technology for semiconductor chips is 10 times more efficient than previous record

AI data centers are power-hungry. Not only do artificial intelligence computations consume enormous amounts of electricity, but a significant amount of energy is also required to cool the semiconductor chips that heat up during operation. As AI chips continue to deliver higher performance, the amount of heat they generate increases rapidly. As a result, conventional air cooling and external copper heat spreaders are approaching their practical limits. To address this challenge, a KAIST research team has developed an ultra-high-efficiency liquid-cooling technology that cools semiconductor chips from within.

A joint research team led by Professor Sung Jin Kim of the Department of Mechanical Engineering and Professor Ikjin Lee of the School of AI and Computing has developed a highly efficient liquid-cooling technology that directly cools high-heat-flux semiconductor chips using room-temperature water. The researchers achieved this by embedding liquid-cooling channels, thinner than a human hair, directly inside a silicon semiconductor chip. The paper is published in the journal Energy Conversion and Management.

The team successfully maintained the chip temperature below 100° C (212° F) even under extreme heat-generation conditions exceeding 2,000 watts per square centimeter (W/cm2).

Beyond frozen snapshots, protein ‘breathing’ comes into view with combined imaging methods

Advances in structural biology have allowed scientists to determine molecular structures with atomic-level detail, sometimes yielding static snapshots that do not reflect the dynamism of proteins. However, these motions are often crucial for biological function. Researchers from the Institute of Science and Technology Austria (ISTA), together with international collaborators, have now combined several methods to shed light on how proteins “breathe” and how some experimental techniques freeze their motion. The findings—which could boost protein design approaches and improve AI-based structural prediction tools—are published in Nature Chemistry.

Despite serving as structural biology’s central pillar for more than half a century, protein crystallography has yielded static molecular structures—like still frames from a video—far from the buzzing life inside cells.

“How much can these ‘frozen snapshots’ of protein structures really tell us about their true biological functions and bustling molecular environments?” asks Lea Becker, the study’s first author and a Ph.D. student in Professor Paul Schanda’s group at the Institute of Science and Technology Austria (ISTA).

Tiny chip could help cameras spot hidden details

A tiny new chip could give cameras and sensing systems a far sharper view of the world, helping them detect subtle differences in materials and environments that standard color imaging systems cannot see.

In research led by Zhejiang University in collaboration with RMIT University, scientists have demonstrated a new way to build light-analysis capability directly into imaging hardware.

Cameras are highly effective at capturing images, but applications such as machine vision, automated inspection and environmental monitoring depend on understanding different colors and wavelengths of light, not just what something looks like. That information can reveal differences in materials, surface conditions or environmental changes that appear identical to the human eye.

Light-programmed system projects 28-layer 3D images in single shot

Researchers at the UCLA Samueli School of Engineering and CNSI (California NanoSystems Institute), led by Professor Aydogan Ozcan, introduced a snapshot 3D image projection system that integrates a digital encoder with a passive diffractive optical decoder, jointly optimized end-to-end through deep learning. The hybrid architecture projects multiple distinct images onto closely spaced axial planes in a single shot, marking a significant step toward compact, high-fidelity volumetric display technologies. The research is published in the journal Light: Science & Applications.

3D image display technology is essential for next-generation holography, immersive visualization, and augmented and virtual reality (AR/VR) interfaces, where accurate focal cues across depth are critical for natural depth perception and visual comfort. However, dense depth multiplexing in conventional holographic displays remains a challenge: As the axial image planes approach one another in the output volume, diffraction-induced crosstalk rapidly degrades depth selectivity and image fidelity.

A robot is helping an ailing couple stay in their home. Are more to come for an aging population?

After outliving Booker T. Bones, their second service dog, Brenda and Brian Marquis still needed help with some of the more difficult parts of daily life.

They found Robbie, a robot that rolls out of a hallway into their living room several times a day.

“Do you want to exercise now? Please answer yes or no,” the caregiver robot asks 59-year-old Brian Marquis, who has been living with a traumatic brain injury since a 2012 car crash.

Reaching Longevity Escape Velocity by 2029

Are we on the verge of outrunning aging entirely? Renowned futurist and inventor Ray Kurzweil shares his data-driven predictions on the exponential trajectory of artificial intelligence and its near-term impact on human health.

Speaking to a Cosmos conference from his studio, Kurzweil charts the predictable, uninterrupted 80-year history of computing power from early wartime codebreaking machines to modern cloud processors. He explains why the sudden emergence of massive neural networks and \.

Autonomous Immunity Model of Aging And Disease

Aging involves a decline in physiological functions and increased disease susceptibility, with the immune system playing a pivotal role. Recent research reveals that nonimmune structural cells, such as fibroblasts, epithelial cells, and neurons, develop immune-like properties crucial for stress response and tissue integrity. However, with aging, these organized, nonimmune cells in multicellular organisms gradually lose their identity and organization. They may exhibit unicellular properties, acquire macrophage-like characteristics, or enter a state of senescence, contributing to chronic inflammation.

AI-assisted, real-time deep-brain stimulation therapy for walking impairments in Parkinson’s disease

Deep brain stimulation (DBS) has been used for more than three decades to treat motor symptoms of Parkinson’s disease. Today, more than 200,000 patients worldwide have been implanted with these systems, which continuously deliver electrical stimulation to specific deep-brain regions to reduce rigidity and tremor. Yet despite its clinical success, conventional deep brain stimulation remains limited in its ability to address one of the disease’s most disabling symptoms: walking impairments.

Researchers from EPFL and Lausanne University Hospital (CHUV) have developed a new approach, published in Nature Medicine, that adapts DBS in real time to the patient’s mobility in everyday situations. Thanks to artificial intelligence, the system continuously interprets the patient’s activity and adjusts stimulation in real time, improving walking, climbing stairs and even the simple act of standing up.

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