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New Methane Flare Tech: Efficiency Plus Combustion Stability

“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.”

Post-Scarcity Civilizations & Purpose

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

Writers:
Isaac Arthur.

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A Very High-Resolution Urban Green Space from the Fusion of Microsatellite, SAR, and MSI Images

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.

The Law of Knowledge Overshadowing: Towards Understanding, Predicting, and Preventing LLM Hallucination

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].

WalkerS1-UBTECH

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

2025 Age Reversal: 7 Real Innovations To Stop Us Growing Old

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:

Introducing Evo 2, a predictive and generative genomic AI for all domains of life

Researchers at the Arc Institute, Stanford University, and NVIDIA have developed Evo 2, an advanced AI model capable of predicting genetic variations and generating genomic sequences across all domains of life.

Testing shows that Evo 2 accurately predicts the functional effects of mutations across prokaryotic and eukaryotic genomes. It also successfully annotated the woolly mammoth genome from raw without a direct training reference, showing an ability to generalize function from the sequence alone.

Current genomic models struggle with predicting functional impacts of mutations across diverse biological systems, particularly for eukaryotic genomes. Machine learning approaches have demonstrated some success in modeling and prokaryotic genomes. The complexity of eukaryotic DNA, with its long-range interactions and regulatory elements, presents more of a challenge.

How AI Is Transforming The Pharmaceutical Industry

AI-powered precision in medicine is helping to enhance the accuracy, efficiency, and personalization of medical treatments and healthcare interventions. Machine learning models analyze vast datasets, including genetic information, disease pathways, and past clinical outcomes, to predict how drugs will interact with biological targets. This not only speeds up the identification of promising compounds but also helps eliminate ineffective or potentially harmful options early in the research process.

Researchers are also turning to AI to improve how they evaluate a drug’s effectiveness across diverse patient populations. By analyzing real-world data, including electronic health records and biomarker responses, AI can help researchers identify patterns that predict how different groups may respond to a treatment. This level of precision helps refine dosing strategies, minimize side effects, and support the development of personalized medicine where treatments are tailored to an individual’s genetic and biological profile.

AI is having a positive impact on the pharmaceutical industry helping to reshape how drugs are discovered, tested, and brought to market. From accelerating drug development and optimizing research to enhancing clinical trials and manufacturing, AI is reducing costs, improving efficiency, and ultimately delivering better treatments to patients.

UBTech breakthrough sees humanoid robots work as a team in car factory

A Shenzhen-based humanoid robot maker said it has deployed “dozens of robots” in an electric vehicle (EV) factory where they work together on complicated tasks, offering a peek into the future of Made-in-China tech as artificial intelligence (AI) and robotics technologies are applied to empower manufacturing.

Hong Kong-listed UBTech Robotics said on Monday that it has completed a test to deploy dozens of its Walker S1 robots in the Zeekr EV factory in the Chinese port city of Ningbo for “multitask” and “multi site” operations.

According to photos and videos provided by UBTech, the human-shaped robots work as a team to complete tasks such as lifting heavy boxes and handling soft materials.

A Self-Balancing Exoskeleton Strides Toward Market

Many people who have spinal cord injuries also have dramatic tales of disaster: a diving accident, a car crash, a construction site catastrophe. But Chloë Angus has quite a different story. She was home one evening in 2015 when her right foot started tingling and gradually lost sensation. She managed to drive herself to the hospital, but over the course of the next few days she lost all sensation and control of both legs. The doctors found a benign tumor inside her spinal cord that couldn’t be removed, and told her she’d never walk again. But Angus, a jet-setting fashion designer, isn’t the type to take such news lying—or sitting—down.

Ten years later, at the CES tech trade show in January, Angus was showing off her dancing moves in a powered exoskeleton from the Canadian company Human in Motion Robotics. “Getting back to walking is pretty cool after spinal cord injury, but getting back to dancing is a game changer,” she told a crowd on the expo floor.