Lifeboat Foundation

Musk says Grok 2 ‘should exceed current AI on all metrics,’ though Grok 3 is waiting in the wings.

Richie Etwaru is Co-founder & CEO at Mobeus. He’s also a former CTO, CDO & CIO at Fortune 500 firms in Financial Services and Healthcare.

Although generative artificial intelligence (GenAI) has been making headlines, another of today’s most tantalizing and controversial topics is the concept of artificial general intelligence (AGI). The idea of AGI —a machine with “the ability to understand, learn, and apply knowledge across a wide range of tasks,” much like a human—has captured the imaginations of scientists, entrepreneurs and science fiction writers alike. However, despite the allure of creating such a machine, a growing body of evidence suggests that AGI will never be realized.

Human intelligence is fundamentally collective and constantly evolving. As individuals, we contribute to a vast pool of knowledge that grows exponentially over time. This collective intelligence isn’t merely the sum of all human knowledge but a complex, interconnected web of ideas, insights and innovations that continuously build upon one another. I’m deliberately excluding human instincts from the dialogue, as this requires another article.

Scientists hooked up brain tissue to a neural interface, allowing it to pass on instructions to a humanoid robot body.

WASHINGTON — Turion Space, an Irvine, California-based startup, has secured a $1.9 million contract from SpaceWERX, the U.S. Space Force’s technology arm, to develop an autonomous spacecraft docking and maneuvering system. The contract aims to advance technologies for engaging uncooperative space objects and facilitating the deorbit of inactive satellites.

Ryan Westerdahl, Turion’s co-founder and CEO, said in an interview that the company is focusing on in-space mobility and non-Earth imaging. Turion launched its first satellite, Droid.001, a 32-kilogram spacecraft designed for space situational awareness, in June 2023. Data from this satellite is being integrated into the Space Force’s Unified Data Library.

Westerdahl revealed plans for a demonstration as early as 2026, featuring a Droid mothership hosting “micro-Droid” satellites equipped with the capturing device being developed under the SpaceWERX contract. The micro-Droid, partly funded by NASA, will use grapplers to capture debris objects.

Thermodynamic computing has the potential to revolutionize AI and machine learning by harnessing thermal fluctuations for faster, more efficient, and lower power computing systems Questions to inspire discussion What is the future revolution in computing? —The future revolution in computing is harnessing thermal fluctuations for physics-based computing systems.

With the rapid advancement of artificial intelligence, unmanned systems such as autonomous driving and embodied intelligence are continuously being promoted and applied in real-world scenarios, leading to a new wave of technological revolution and industrial transformation. Visual perception, a core means of information acquisition, plays a crucial role in these intelligent systems. However, achieving efficient, precise, and robust visual perception in dynamic, diverse, and unpredictable environments remains an open challenge.

In open-world scenarios, intelligent systems must not only process vast amounts of data but also handle various extreme events, such as sudden dangers, drastic light changes at tunnel entrances, and strong flash interference at night in driving scenarios.

Traditional visual sensing chips, constrained by the “power wall” and “bandwidth wall,” often face issues of distortion, failure, or high latency when dealing with these scenarios, severely impacting the stability and safety of the system.

Brighter with Herbert.

Xin Chan, Xiaoyang Wang, Dian Yu, Haitao Mi, Dong Yu Tencent AI Lab Science June 2024 https://huggingface.co/papers/2406.

We propose a novel persona-driven data synthesis methodology that leverages various perspectives within a…

Join the discussion on this paper page.

Humans learn differently than machines face_with_colon_three

This paper introduces ‘prospective configuration’, a new principle for learning in neural networks, which differs from backpropagation and is more efficient in learning and more consistent with data on neural activity and behavior.