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Category: robotics/AI – Page 482

Radical Plan to Stop ‘Doomsday Glacier’ Melting to Cost $50 Billion.

Working on these next-gen intelligent AIs must be a freaky experience. As Anthropic announces the smartest model ever tested across a range of benchmarks, researchers recall a chilling moment when Claude 3 realized that it was being evaluated.

Anthropic, you may recall, was founded in 2021 by a group of senior OpenAI team members, who broke away because they didn’t agree with OpenAI’s decision to work closely with Microsoft. The company’s Claude and Claude 2 AIs have been competitive with GPT models, but neither Anthropic nor Claude have really broken through into public awareness.

That could well change with Claude 3, since Anthropic now claims to have surpassed GPT-4 and Google’s Gemini 1.0 model on a range of multimodal tests, setting new industry benchmarks “across a wide range of cognitive tasks.”

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A group of Tohoku University researchers has developed a theoretical model for a high-performance spin wave reservoir computing (RC) that utilizes spintronics technology. The breakthrough moves scientists closer to realizing energy-efficient, nanoscale computing with unparalleled computational power.

Details of their findings were published in npj Spintronics on March 1, 2024.

The brain is the ultimate computer, and scientists are constantly striving to create neuromorphic devices that mimic the brain’s processing capabilities, , and its ability to adapt to neural networks. The development of neuromorphic computing is revolutionary, allowing scientists to explore nanoscale realms, GHz speed, with low energy consumption.

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The new hardware reimagines AI chips for modern workloads and can run powerful AI systems using much less energy than today’s most advanced semiconductors, according to Naveen Verma, professor of electrical and computer engineering. Verma, who will lead the project, said the advances break through key barriers that have stymied chips for AI, including size, efficiency and scalability.

Chips that require less energy can be deployed to run AI in more dynamic environments, from laptops and phones to hospitals and highways to low-Earth orbit and beyond. The kinds of chips that power today’s most advanced models are too bulky and inefficient to run on small devices, and are primarily constrained to server racks and large data centers.

Now, the Defense Advanced Research Projects Agency, or DARPA, has announced it will support Verma’s work, based on a suite of key inventions from his lab, with an $18.6 million grant. The DARPA funding will drive an exploration into how fast, compact and power-efficient the new chip can get.

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The rapid advancement of deep learning algorithms and generative models has enabled the automated production of increasingly striking AI-generated artistic content. Most of this AI-generated art, however, is created by algorithms and computational models, rather than by physical robots.

Researchers at Universidad Complutense de Madrid (UCM) and Universidad Carlos III de Madrid (UC3M) recently developed a deep learning-based model that allows a humanoid robot to sketch pictures, similarly to how a human artist would. Their paper, published in Cognitive Systems Research, offers a remarkable demonstration of how robots could actively engage in creative processes.

“Our idea was to propose a robot application that could attract the scientific community and the general public,” Raúl Fernandez-Fernandez, co-author of the paper, told Tech Xplore. “We thought about a task that could be shocking to see a robot performing, and that was how the concept of doing art with a humanoid robot came to us.”

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AI isn’t nearly as popular with the global populace as its boosters would have you believe.

As Axios reports based on a new poll of 32,000 global respondents from the consultancy firm Edelman, public trust is already eroding less than 18 months into the so-called “AI revolution” that popped off with OpenAI’s release of ChatGPT in November 2022.

“Trust is the currency of the AI era, yet, as it stands, our innovation account is dangerously overdrawn,” Justin Westcott, the global technology chair for the firm, told Axios. “Companies must move beyond the mere mechanics of AI to address its true cost and value — the ‘why’ and ‘for whom.’”

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When will AI match and surpass human capability? In short, when will we have AGI, or artificial general intelligence… the kind of intelligence that should teach itself and grow itself to vastly larger intellect than an individual human?

According to Ben Goertzel, CEO of SingularityNet, that time is very close: only 3 to 8 years away. In this TechFirst, I chat with Ben as we approach the Beneficial AGI conference in Panama City, Panama.

We discuss the diverse possibilities of human and post-human existence, from cyborg enhancements to digital mind uploads, and the varying timelines for when we might achieve AGI. We talk about the role of current AI technologies, like LLMs, and how they fit into the path towards AGI, highlighting the importance of combining multiple AI methods to mirror human intelligence complexity.

We also explore the societal and ethical implications of AGI development, including job obsolescence, data privacy, and the potential geopolitical ramifications, emphasizing the critical period of transition towards a post-singularity world where AI could significantly improve human life. Finally, we talk about ownership and decentralization of AI, comparing it to the internet’s evolution, and envisages the role of humans in a world where AI surpasses human intelligence.

00:00 Introduction to the Future of AI
01:28 Predicting the Timeline of Artificial General Intelligence.
02:06 The Role of LLMs in the Path to AGI
05:23 The Impact of AI on Jobs and Economy.
06:43 The Future of AI Development.
10:35 The Role of Humans in a World with AGI
35:10 The Diverse Future of Human and Post-Human Minds.
36:51 The Challenges of Transitioning to a World with AGI
39:34 Conclusion: The Future of AGI.

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