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Category: robotics/AI – Page 43

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” | >

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.

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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.

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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.

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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.

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Meta has unveiled the next iteration of its sensor-packed research eyewear, the Aria Gen 2. This latest model follows the initial version introduced in 2020. The original glasses came equipped with a variety of sensors but lacked a display, and were not designed as either a prototype or a consumer product. Instead, they were exclusively meant for research to explore the types of data that future augmented reality (AR) glasses would need to gather from their surroundings to provide valuable functionality.

In their Project Aria initiative, Meta explored collecting egocentric data—information from the viewpoint of the user—to help train artificial intelligence systems. These systems could eventually comprehend the user’s environment and offer contextually appropriate support in daily activities. Notably, like its predecessor, the newly announced Aria Gen 2 does not feature a display.

Meta has highlighted several advancements in Aria Gen 2 compared to the first generation:

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Softbank Group chief executive officer Masayoshi Son plans to borrow $16 billion to invest in artificial intelligence (AI), the company’s executives told banks last week, The Information tech news Web site reported on Saturday, citing people familiar with the matter.

The Japanese technology investor might borrow another $8 billion early next year, the report added. It was reported in January that Softbank is in talks to invest up to $25 billion in ChatGPT owner OpenAI, as the Japanese conglomerate continues to expand into the sector.

Softbank’s investment would be on top of the $15 billion it has already committed to Stargate, a private sector investment of up to $500 billion for AI infrastructure — funded by Softbank, OpenAI and Oracle Corp — to help the US stay ahead of China and other rivals in the global AI race.

The Information — a tech industry-focused publication headquartered in San Francisco — previously reported that Softbank was planning to invest a total of $40 billion into Stargate and OpenAI, and had begun talks to borrow up to $18.5 billion in financing, backed by its publicly-listed assets.

Separately, Arm Holdings PLC is set to sign a pact next week to establish a base in Malaysia, the Malaysian news agency Bernama reported on Friday, citing Malaysian Prime Minister Anwar Ibrahim. Anwar had a discussion with Arm chief executive officer Rene Haas on Friday, he told reporters in Putrajaya, Malaysia. Son also took part in the meeting, he said.

(https://open.substack.com/pub/remunerationlabs/p/softbank-gr…Share=true)

This would be on top of the $15 billion SoftBank has already committed to Stargate.

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Brain creates summaries while reading.

Unlike artificial language models, which process long texts as a whole, the human brain creates a “summary” while reading, helping it understand what comes next.

In recent years, (LLMs) like ChatGPT and Bard have revolutionized AI-driven text processing, enabling machines to generate text, translate languages, and analyze sentiment. These models are inspired by the human brain, but key differences remain.

A new Technion-Israel Institute of Technology study, published in Nature Communications, explores these differences by examining how the spoken texts. The research, led by Prof. Roi Reichart and Dr. Refael Tikochinski from the Faculty of Data and Decision Sciences. It was conducted as part of Dr. Tikochinski’s Ph.D., co-supervised by Prof. Reichart at Technion and Prof. Uri Hasson at Princeton University.

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