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Category: robotics/AI – Page 334

Ray Kurzweil: The Singularity is Closer than You Think

Words of the prophet.

What happens when AI surpasses human intelligence, accelerating its own evolution beyond our control? This is the Singularity, a moment where technology reshapes the world in ways we can’t yet imagine.
Futurist Ray Kurzweil predicts that by 2045, AI will reach this point, merging with human intelligence through Brain-Computer Interfaces (BCIs) and redefining the future of civilization. But as we move closer to this reality, we must ask: Will the Singularity be humanity’s greatest leap or its greatest risk?
Chapters.
00:00 — 00:48 Intro.
00:48 — 01:51 Technological Singularity.
01:51 — 05:09 Kurzweil’s Predictions and Accuracy.
05:09 — 07:32 The Path to the Singularity.
07:32 — 08:51 Brain-Computer Interfaces (BCIs)
08:51 — 12:14 The Singularity: What Happens Next?
12:14 — 14:14 The Concerns: Are We Ready?
14:14 — 15:11 The Countdown to 2045
The countdown has already begun. Are we prepared for what’s coming?
#RayKurzweil #Singularity #AI #FutureTech #ArtificialIntelligence #BrainComputerInterface

Combining photonic neural networks with distributed acoustic sensing for infrastructure monitoring

Distributed acoustic sensing (DAS) systems represent cutting-edge technology in infrastructure monitoring, capable of detecting minute vibrations along fiber optic cables spanning tens of kilometers. These systems have proven invaluable for applications ranging from earthquake detection and oil exploration to railway monitoring and submarine cable surveillance.

However, the massive amounts of data generated by these systems create a significant bottleneck in processing speed, limiting their effectiveness for real-time applications where immediate responses are crucial.

Machine learning techniques, particularly neural networks, have emerged as a promising solution for processing DAS data more efficiently. While the processing capabilities of traditional electronic computing using CPUs and GPUs have massively improved over the past decades, they still face fundamental limitations in speed and energy efficiency. In contrast, photonic neural networks, which use light instead of electricity for computations, offer a revolutionary alternative, potentially achieving much higher processing speeds at a fraction of the power.

AI food scanner turns phone photos into nutritional analysis

Snap a photo of your meal, and artificial intelligence instantly tells you its calorie count, fat content, and nutritional value—no more food diaries or guesswork.

This futuristic scenario is now much closer to reality, thanks to an AI system developed by NYU Tandon School of Engineering researchers that promises a new tool for the millions of people who want to manage their weight, diabetes and other diet-related health conditions.

The technology, detailed in a paper presented at the 6th IEEE International Conference on Mobile Computing and Sustainable Informatics, uses advanced deep-learning algorithms to recognize food items in images and calculate their nutritional content, including calories, protein, carbohydrates and fat.

Researchers publish blueprint to fuse wireless technologies and AI

When someone is traumatically injured, giving them blood products before they arrive at the hospital—such as at the scene or during emergency transport—can improve their likelihood of survival and recovery. But patients with certain traumatic injuries have better outcomes when administered specific blood components.

University of Pittsburgh School of Medicine and UPMC scientist-surgeons report in Cell Reports Medicine that giving that has been separated from other parts of donated blood improves outcomes in patients with (TBI) or shock, whereas giving unseparated or “whole” blood may be best for patients with traumatic bleeding.

Together, Pitt and UPMC have become home to the largest clinical trials research consortium for early trauma care in the U.S., allowing the research to benefit both soldiers and civilians.

Coffee-making robot breaks new ground for AI machines

An AI-powered robot that can prepare cups of coffee in a busy kitchen could usher in the next generation of intelligent machines, a study suggests.

The research, published in the journal Nature Machine Intelligence, was led by Ruaridh Mon-Williams, a Ph.D. student jointly at the University of Edinburgh, Massachusetts Institute of Technology and Princeton University.

Using a combination of cutting-edge AI, sensitive sensors and fine-tuned motor skills, the robot can interact with its surroundings in more human-like ways than ever before, researchers say.

MicroVQA: A Multimodal Reasoning Benchmark for Microscopy-Based Scientific Research

📣Just announced at [#GTC25](https://www.facebook.com/hashtag/gtc25?__eep__=6&__cft__[0]=AZXGE68SvdjQyRxtqhq57u6xDScMuziTjPrrOj7ic9_n1QMWssMuQdAZ4MLZmg3kpo3u92u-w_Z12HEaFeSJnvxJ_h_dNAloE8I86x4WxG8730kGwR10dtKo0yYVmS4GQdeMF0xu2E5mpp8VTUcHoNIO&__tn__=*NK-R): NVIDIA will be open-sourcing cuOpt, an AI-powered decision optimization engine.

➡️ [ https://nvda.ws/43REYuW](https://nvda.ws/43REYuW open-sourcing this powerful solver, developers can harness real-time optimization at an unprecedented scale for free.

The best-known AI applications are all about predictions — whether forecasting weather or generating the next word in a sentence. But prediction is only half the challenge. The real power comes from acting on information in real time.

That’s where cuOpt comes in.

CuOpt dynamically evaluates billions of variables — inventory levels, factory output, shipping delays, fuel costs, risk factors and regulations — and delivers the best move in near real time.

Unlike traditional optimization methods that navigate solution spaces sequentially or with limited parallelism, cuOpt taps into GPU acceleration to evaluate millions of possibilities simultaneously — finding optimal solutions exponentially faster for specific instances.

It doesn’t replace existing techniques — it enhances them. By working alongside traditional solvers, cuOpt rapidly identifies high-quality solutions, helping CPU-based models discard bad paths faster.

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SABER: Securing Artificial Intelligence for Battlefield Effective Robustness

There is a growing desire to integrate rapidly advancing artificial intelligence (AI) technologies into Department of Defense (DoD) systems. AI may give battlefield advantage by helping improve the speed, quality, and accuracy of decision-making while enabling autonomy and assistive automation.

Due to the statistical nature of machine learning, a significant amount of work has focused on ensuring the robustness of AI-enabled systems at inference time to natural degradations in performance caused by data distribution shifts (for example, from a highly dynamic deployment environment).

However, as early as 2014, researchers demonstrated the ability to manipulate AI given adversary control of the input. Additional work has confirmed the theoretical risks of data poisoning, physically constrained adversarial patches for evasion, and model stealing attacks. These attacks are typically tested in simulated or physical environments with relatively pristine control compared to what might be expected on a battlefield.

Paralyzed man moves robotic arm with his thoughts

Researchers have enabled a man who is paralyzed to control a robotic arm through a device that relays signals from his brain to a computer.

He was able to grasp, move and drop objects just by imagining himself performing the actions.

The device, known as a brain-computer interface (BCI), worked for a record 7 months without needing to be adjusted. Until now, such devices have only worked for a day or two.

The BCI relies on an AI model that can adjust to the small changes that take place in the brain as a person repeats a movement – or in this case, an imagined movement – and learns to do it in a more refined way.

“This blending of learning between humans and AI is the next phase for these brain-computer interfaces,” said the neurologist. “It’s what we need to achieve sophisticated, lifelike function.”

Dr. Catharine Young, Ph.D. — Science, Policy And Advocacy For Impactful Health Ecosystems

Science, Policy And Advocacy For Impactful And Sustainable Health Ecosystems — Dr. Catharine Young, Ph.D. — fmr. Assistant Director of Cancer Moonshot Policy and International Engagement, White House Office of Science and Technology Policy (OSTP)

Dr. Catharine Young, Ph.D. recently served as Assistant Director of Cancer Moonshot Policy and International Engagement at the White House Office of Science and Technology Policy (https://www.whitehouse.gov/ostp/) where she served at OSTP to advance the Cancer Moonshot (https://www.cancer.gov/research/key-i… with a mission to decrease the number of cancer deaths by 50% over the next 25 years.

Dr. Young’s varied career has spanned a variety of sectors including academia, non-profit, biotech, and foreign government, all with a focus on advancing science.

Dr. Young previously served as Executive Director of the SHEPHERD Foundation, where she championed rare cancer research and drove critical policy changes. Her work has also included fostering interdisciplinary collaborations and advancing the use of AI, data sharing, and clinical trial reform to accelerate cancer breakthroughs.

Dr. Young’s leadership in diplomacy and innovation includes roles such as Senior Director of Science Policy at the Biden Cancer Initiative and Senior Science and Innovation Policy Advisor at the British Embassy, where she facilitated international agreements to enhance research collaborations.

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NVIDIA Is About To Drop New AI Chips. Here’s What To Expect At Their GTC Event

All eyes will be on Nvidia’s GPU Technology Conference this week, where the company is expected to unveil its next artificial intelligence chips. Nvidia chief executive Jensen Huang said he will share more about the upcoming Blackwell Ultra AI chip, Vera Rubin platform, and plans for following products at the annual conference, known as the GTC, during the company’s fiscal fourth quarter earnings call.

On the earnings call, Huang said Nvidia has some really exciting things to share at the GTC about enterprise and agentic AI, reasoning models, and robotics. The chipmaker introduced its highly anticipated Blackwell AI platform at last year’s GTC, which has successfully ramped up large-scale production, and made billions of dollars in sales in its first quarter, according to Huang.

Analysts at Bank of America said in a note on Wednesday that they expect Nvidia to present attractive albeit well-expected updates on Blackwell Ultra, with a focus on inferencing for reasoning models, which major firms such as OpenAI and Google are racing to develop.

The analysts also anticipate the chipmaker to share more information on its next-generation networking technology, and long-term opportunities in autonomous cars, physical AI such as robotics, and quantum computing.

In January, Nvidia announced that it would host its first Quantum Day at the GTC, and have executives from D-Wave and Rigetti discuss where quantum computing is headed. The company added that it will unveil quantum computing advances shortening the timeline to useful applications.

The same month, quantum computing stocks tanked after Huang expressed doubts over the technology’s near-term potential during the chipmaker’s financial analyst day at the Consumer Electronics Show, saying useful quantum computers are likely decades away.

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