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Category: robotics/AI – Page 72

A new high-performance quantum processor boasts 105 superconducting qubits and rivals Google’s acclaimed Willow processor.

In the quest for useful quantum computers, processors based on superconducting qubits are especially promising. These devices are both programmable and capable of error correction. In December 2024, researchers at Google Quantum AI in California reported a 105-qubit superconducting processor known as Willow (see Research News: Cracking the Challenge of Quantum Error Correction) [1]. Now Jian-Wei Pan at the University of Science and Technology of China and colleagues have demonstrated their own 105-qubit processor, Zuchongzhi 3.0 (Fig. 1) [2]. The two processors have similar performances, indicating a neck-and-neck race between the two groups.

Quantum advantage is the claim that a quantum computer can perform a specific task faster than the most powerful nonquantum, or classical, computer. A standard task for this purpose is called random circuit sampling, and it works as follows. The quantum computer applies a sequence of randomly ordered operations, known as a random circuit, to a set of qubits. This circuit transforms the qubits in a unique and complex way. The computer then measures the final states of the qubits. By repeating this process many times with different random circuits, the quantum computer records a probability distribution of final qubit states.

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Quantitative phase imaging (QPI) is a microscopy technique widely used to investigate cells. Even though earlier biomedical applications based on QPI have been developed, both acquisition speed and image quality need to improve to guarantee a widespread reception.

Scientists from the Görlitz-based Center for Advanced Systems Understanding (CASUS) at Helmholtz-Zentrum Dresden-Rossendorf (HZDR) as well as Imperial College London and University College London suggest leveraging an optical phenomenon called chromatic aberration—that usually degrades image quality—to produce suitable images with standard microscopes.

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From connectome to computation:
predicting neural function with machine learning.

Janne Lappalainen.
University of Tubingen & Tubingen AI Center.

Presentation and Q&A
At the Carboncopies Foundation February 2025 workshop:

The brain emulation challenge: functionalizing brain data, ground-truthing and the role of artificial data in advancing neuroscience.

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*This video was recorded at Foresight’s Whole Brain Emulation Workshop 2023.*
https://foresight.org/whole-brain-emulation-workshop-2023/

*Niccolò Zanichelli, Università degli Studi di Parma*
What can AI do for Whole Brain Emulation.
https://www.linkedin.com/in/niccol%C3%B2-zanichelli-99a7881a3/

WBE is a potential technology to generate software intelligence that is human-aligned simply by being based directly on human brains. Generally past discussions have assumed a fairly long timeline to WBE, while past AGI timelines had broad uncertainty. There were also concerns that the neuroscience of WBE might boost AGI capability development without helping safety, although no consensus did develop. Recently many people have updated their AGI timelines towards earlier development, raising safety concerns. That has led some people to consider whether WBE development could be significantly speeded up, producing a differential technology development re-ordering of technology arrival that might lessen the risk of unaligned AGI by the presence of aligned software intelligence.

Whether this is a viable strategy depends on.
(1) AGI timelines not being ultra-short.
(2) whether WBE development can be speeded up significantly by a concerted effort, (3) this speedup doesn’t introduce other risks or ethical concerns.

The goals of this workshop is to try to.
(A) review the current state of the art in WBE related technology.
(B) outline plausible development paths and necessary steps for full WBE
© determine whether there is potential for speeding up WBE development.
(D) whether there are strategic, risk or ethical issues speaking against this.

This two-day event invites leading researchers, entrepreneurs, and funders to drive progress. Explore new opportunities, form lasting collaborations, and join us in driving cooperation toward shared long-term goals. Including mentorship hours, breakouts, and speaker & sponsor gathering.

Continue reading “Niccolò Zanichelli | What can AI do for Whole Brain Emulation @ Whole Brain Emulation Workshop 2023” | >

“A good ratio of oxygen to methane is key to combustion,” said Justin Long.

Can methane flare burners be advanced to produce less methane? This is what a recent study published in Industrial & Engineering Chemistry Research hopes to address as a team of researchers from the University of Michigan (U-M) and the Southwest Research Institute (SwRI) developed a methane flare burner with increased combustion stability and efficiency compared to traditional methane flare burners. This study has the potential to develop more environmentally friendly burners to combat human-caused climate change, specifically since methane is a far larger contributor to climate change than carbon dioxide.

For the study, the researchers used a combination of machine learning and novel manufacturing methods to test several designs of a methane flare burner that incorporates crosswinds to simulate real-world environments. The burner design includes splitting the methane flow in three directions while enabling oxygen flow from crosswinds to mix with the methane, enabling a much cleaner combustion. In the end, the researchers found that their design achieves 98 percent combustion efficiency, meaning it produces 98 percent less methane than traditional burners.

“A good ratio of oxygen to methane is key to combustion,” said Justin Long, who is a Senior Research Engineer at SwRI. “The surrounding air needs to be captured and incorporated to mix with the methane, but too much can dilute it. U-M researchers conducted a lot of computational fluid dynamics work to find a design with an optimal air-methane balance, even when subjected to high-crosswind conditions.”

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Technology may one day grant us a Utopia in which virtually all tasks are performed by robots and artificial intelligence. In such a post-scarcity civilization, people may have difficulty finding a purpose to existence. Today we will explore how this may come about, what the consequences of this existential threat might be, and what purposes people may find for themselves in such a future.

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Listen or Download the audio of this episode from Soundcloud: Episode’s Audio-only version:
/ purpose.
Episode’s Narration-only version: / purpose-narration-only.

Credits: post-scarcity civilizations: purpose. ep 140 season 4, episode 26

Writers:
Isaac Arthur.

Editors:

Continue reading “Post-Scarcity Civilizations & Purpose” | >

Jakarta holds the distinction of being the largest capital city among ASEAN countries and ranks as the second-largest metropolitan area in the world, following Tokyo. Despite numerous studies examining the diverse urban land use and land cover patterns within the city, the recent state of urban green spaces has not been adequately assessed and mapped precisely. Most previous studies have primarily focused on urban built-up areas and manmade structures. In this research, the first-ever detailed map of Jakarta’s urban green spaces as of 2023 was generated, with a resolution of three meters. This study employed a combination of supervised classification and evaluated two machine learning algorithms to achieve the highest accuracy possible.

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Abstract: Hallucination is a persistent challenge in large language models (LLMs), where even with rigorous quality control, models often generate distorted facts. This paradox, in which error generation continues despite high-quality training data, calls for a deeper understanding of the underlying LLM mechanisms. To address it, we propose a novel concept: knowledge overshadowing, where model’s dominant knowledge can obscure less prominent knowledge during text generation, causing the model to fabricate inaccurate details. Building on this idea, we introduce a novel framework to quantify factual hallucinations by modeling knowledge overshadowing. Central to our approach is the log-linear law, which predicts that the rate of factual hallucination increases linearly with the logarithmic scale of Knowledge Popularity, Knowledge Length, and Model Size. The law provides a means to preemptively quantify hallucinations, offering foresight into their occurrence even before model training or inference. Built on overshadowing effect, we propose a new decoding strategy CoDa, to mitigate hallucinations, which notably enhance model factuality on Overshadow (27.9%), MemoTrap (13.1%) and NQ-Swap (18.3%). Our findings not only deepen understandings of the underlying mechanisms behind hallucinations but also provide actionable insights for developing more predictable and controllable language models.

From: Yuji Zhang [view email].

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This is automating labor in an entirely new way.

Chinese robotics company UBTech has received over 500 orders for its new industrial humanoid robot, the Walker S1.

The Walker S1, officially launched this week, is already operating in factories, including those of BYD, the world’s largest electric vehicle manufacturer. This robot works alongside unmanned logistic vehicles and smart manufacturing systems, making it one of the first in the world to automate large-scale operations to this extent.

China’s manufacturing sector has faced a growing labor shortage, with a projected gap of 30 million workers by 2025. UBTech aims to reduce human labor in automated factories from 30% to 10% by using robots like the Walker S1, focusing human efforts on high-level tasks such as tool management and collaboration. “The idea is to replace around 20% of the workload with humanoid robots,” said UBTech’s chief brand officer Tan Min, highlighting the need for automation as vocational training programs struggle to meet the demand for skilled workers, while younger graduates increasingly avoid blue-collar jobs.

S partnerships with industry giants like BYD, FAW-Volkswagen, and Foxconn highlight the robot’s broad applications in manufacturing, logistics, and electronics. As labor shortages and safety concerns grow, UBTech’s innovative humanoid robots offer a glimpse into the future of automated factories, promising to transform not only automotive production but also other sectors through large-scale automation. ” + learn more https://www.ubtrobot.com/en/humanoid/products/WalkerS1

Image: UBTech

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In this video, we explore seven astonishing breakthroughs leading us closer to age reversal and longer, healthier lives by 2025. From mapping the complete fruit fly brain for deeper insights into neurobiology, to AI-driven drug discovery breakthroughs by Insilico Medicine, these cutting-edge innovations are changing the way we understand and tackle aging. We’ll also dive into the growing world of microbiome-targeting startups, and Dr. Ben Goertzel’s vision for an AI-driven future where extended longevity and superintelligence converge. Whether you’re interested in the most advanced biotech research, the latest in computational biology, or the promise of AGI to transform healthcare, this video covers the game-changing science that could redefine what it means to grow older.

Stay tuned for expert insights on how these remarkable advancements might help us inch closer to “longevity escape velocity.” Be sure to check the description for links to the studies, articles, and visionary leaders shaping tomorrow’s health landscape.

00:00 intro.
01:25 Dont Die Documentary Cameo.
03:30 Folistatin Gene Therapy.
06:15 Cellular Reprogramming.
09:00 Decentralized Science.
11:50 Human Brain Simulation.
14:53 AI Designed Drugs.
18:08 Microbiome.
21:25 Ben Goertzel AI+Longevity.

Mentioned vids: part 1: the surprising environmental impacts of an aging cure. • the surprising environmental impacts…

Ben Goertzel Interview:
• AGI, SingularityNET, Longevity Escape…

SOURCES:

Continue reading “2025 Age Reversal: 7 Real Innovations To Stop Us Growing Old” | >