Lifeboat Foundation: Safeguarding Humanity
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Category: robotics/AI – Page 731

In 1993, acclaimed sci-fi author and computer scientist Vernor Vinge made a bold prediction – within 30 years, advances in technology would enable the creation of artificial intelligence surpassing human intelligence, leading to “the end of the human era.”

Vinge theorized that once AI becomes capable of recursively improving itself, it would trigger a feedback loop of rapid, exponential improvements to AI systems. This hypothetical point in time when AI exceeds human intelligence has become known as “the Singularity.”

While predictions of superhuman AI may have sounded far-fetched in 1993, today they are taken seriously by many AI experts and tech investors seeking to develop “artificial general intelligence” or AGI – AI capable of fully matching human performance on any intellectual task.

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Chinese company Fourier Intelligence says it plans to manufacture 100 of its GR-1 general-purpose humanoid robots by the end of 2023, making the remarkable promise that they’ll be able to carry nearly their own weight. They also have a unique focus.

Fourier seems to specialize mainly in rehabilitation technologies; its RehabHub platform offers a series of integrated physical therapy devices for treating various issues, from wrist strength games to hand and finger grip training, all the way up to lower-body exoskeletons for training people to walk, sit, stand, balance and climb stairs.

As such, the GR-1 humanoid project, launched back in 2019, might seem a little out of left field. But on the other hand, a lower-body physical therapy exoskeleton probably uses a lot of the same hardware, and needs to solve a lot of the same problems, as a robot’s legs.

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Speak, an English language learning platform backed by OpenAI’s startup investment fund, the OpenAI Startup Fund, today announced that it raised $16 million in a Series B-2 funding round led by angel investor Lachy Groom.

The co-founders of Dropbox, Drew Houston and Arash Ferdowsi, also participated in Speak’s tranche, which brings the startup’s total raised to $63 million. CEO Connor Zwick says that it’ll be used to support Speak’s launch in more markets, including in the U.S. by the end of the year. (Speak is currently live in around 20 countries including Japan, Taiwan, Germany, France, Brazil and Mexico.)

“It’s been incredible to see that the learning experience we spent years honing in a single market, South Korea, has proven to resonate with almost no modifications needed in markets and cultures across the globe,” Zwick said in a press release. “Looking ahead, we plan on bringing our AI-powered tutor to most major markets around the world by the end of this year, and are gearing up for a launch in the U.S., offering English speakers the ability to learn other languages.”

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AI helps implants work better, preventing diseases before they happen despite immune system challenges.

Imagine your body had an implant that could continuously monitor the occurrence of diseases and infections and immediately release medications to prevent them. Wouldn’t that be ideal, especially for patients who suffer from conditions like heart failure, diabetes, and asthma?

You’d be surprised to know that such implants do exist, but the human body doesn’t allow them to work. Our immune system recognizes such devices as foreign substances.

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The AI won 15 of the 25 races against humans and led the fastest time on the track by more than half a second.

Researchers at the University of Zurich in Switzerland have developed an artificial intelligence (AI) system that can not only fly drones but also beat human counterparts who are champions, according to a press release published in Nature.

This is a major milestone for machine intelligence, which can lead to further development of other systems, such as self-driving vehicles and aircraft.

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We believe artificial intelligence has the power to save the world —and that a thriving open source ecosystem is essential to building this future.

Thankfully, the open source ecosystem is starting to develop, and we are now seeing open source models that rival closed-source alternatives. Hundreds of small teams and individuals are also working to make these models more useful, accessible, and performant.

These projects push the state of the art in open source AI and help provide a more robust and comprehensive understanding of the technology. They include: instruction-tuning base LLMs; removing censorship from LLM outputs; optimizing models for low-powered machines; building novel tooling for model inference; researching LLM security issues; and many others.

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Large language models (LLMs) are ushering in a revolutionary era with their remarkable capabilities. From enhancing everyday applications to transforming complex systems, generative AI is becoming an integral part of our lives.

However, the surge in demand for AI-powered solutions exposes a critical challenge: the scarcity of computational resources required to meet the growing appetite for logic and voice-based interfaces. This scarcity leads to a pressing need for cost-efficient platforms that can support the development and deployment of LLMs.

Industrializing AI software development will require transforming the processes for developing, deploying and maintaining AI systems from a research or ad-hoc approach into a structured, systematic and scalable industrial process. By focusing on cloud cost optimization and platform engineering, businesses can foster growth, profitability, and innovation in the field of AI.

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High-speed drone racing has just had a shocking “Deep Blue” moment, as an autonomous AI designed by University of Zurich researchers repeatedly forced three world champion-level pilots to eat its dust, showing uncanny precision in dynamic flight.

If you’ve ever watched a high-level drone race from the FPV perspective, you’ll know how much skill, speed, precision and dynamic control it takes. Like watching Formula One from the driver’s perspective, or on-board footage from the Isle of Man TT, it’s hard to imagine how a human brain can make calculations that quickly and respond to changing situations in real time. It’s incredibly impressive.

When Deep Blue stamped silicon’s dominance on the world of chess, and AlphaGo established AI’s dominance in the game of Go, these were strategic situations, in which a computer’s ability to analyze millions of past games and millions of potential moves and strategies gave them the edge.

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