Lifeboat Foundation

Taichi could potentially make artificial general intelligence a reality.

Researchers at Tsinghua University in China have developed a revolutionary new artificial intelligence (AI) chip that uses light instead of electricity to process data.

Researchers have developed a highly energy-efficient photonic AI chip called Taichi, which could accelerate the development of advanced computing solutions.

In a promising step towards the evolution of next-generation electric vehicles (EV), Chinese car maker IM Motors has launched a car that features a version of solid-state batteries.

The battery pack, dubbed “Lightyear” by IM, is the primary power source for the company’s flagship L6 Lightyear Max, priced at approximately ¥330,000 (equivalent to US$45,600).

Continue reading “Chinese automaker launches world’s first EV with ‘semi-solid-state’ battery” »

The highest-level Hidra chip will power Apple’s highest-end desktop, the Mac Pro. To give you an idea of how powerful the chip might be, Apple is working to support the Mac Pro with 512 GB RAM. Unlike Intel’s processor, which allows additional memory to be added later, Apple Silicon is more deeply integrated into the processor, and therefore, the RAM options will have come from Apple itself.

With the M4 chip nearing production, Apple could unveil its new and updated Mac lineup later this year and follow it up with releases through 2025, the Bloomberg report added.

A newer lineup also gives the Cupertino-based company an opportunity to join the league of tech giants working on AI. Compared to Microsoft and Google, which have already released their AI-powered products, Apple has been a laggard in the AI space.

The robot is controlled by a neural network trained in deep reinforcement learning via simulation.

Students at ETH Zurich are creating a robot that can move around in extremely low gravity by hopping like a human.

Continue reading “Spacehopper: Three-legged jumping robot to study asteroids in space” »

The design is intended to provide more computing power, bandwidth, and memory capacity to the chips. Initially, Meta aimed to perform inference functions such as ranking and generating responses to user prompts. Meta plans to use the chips for more intense operations, such as training AI models using large data sets.

A shift to its chips could help Meta save millions in energy costs every year, alongside the billions needed in capital expenditure to buy chips from Nvidia.

Meta isn’t the only tech company looking to design and build its own AI chips. Legacy chipmaker Intel, which has lagged in catering to industry requirements for AI chips, also announced its new Gaudi chips at an event on Tuesday.

“A crucial question we constantly face is how much we can curve the signal and over what distance,” acknowledges Mittleman. “We have initial estimations, but a more precise understanding is necessary.”

This research, supported by the National Science Foundation and the Air Force Office of Scientific Research, represents a significant step towards a future powered by terahertz communication. By bending the limitations of current technologies, researchers are paving the way for a new era of seamless and high-bandwidth wireless connectivity.

Tesla CEO Elon Musk — who has an abysmal track record for making predictions — is predicting that we will achieve artificial general intelligence (AGI) by 2026.

“If you define AGI as smarter than the smartest human, I think it’s probably next year, within two years,” he told Norway wealth fund CEO Nicolai Tangen during an interview this week, as quoted by Reuters.

The mercurial billionaire also attempted to explain why his own AI venture, xAI, has been falling behind the competition. According to Musk, a shortage of chips was hampering his startup’s efforts to come up with the successor of Grok, a foul-mouthed, dad joke-generating AI chatbot.

J. V. Neumann, Zur Theorie der Gesellschaftsspiele, 1928. Proved the existence of equilibrium in 2 players’ zero-sum games.

The birth of game theory.

The modern concept of Nash equilibrium is instead defined in terms of mixed strategies, where players choose a probability distribution over possible pure strategies (which might put 100% of the probability on one pure strategy; such pure strategies are a subset of mixed strategies). The concept of a mixed-strategy equilibrium was introduced by John von Neumann and Oskar Morgenstern in their 1944 book The Theory of Games and Economic Behavior, but their analysis was restricted to the special case of zero-sum games. They showed that a mixed-strategy Nash equilibrium will exist for any zero-sum game with a finite set of actions.^[13] The contribution of Nash in his 1951 article “Non-Cooperative Games” was to define a mixed-strategy Nash equilibrium for any game with a finite set of actions and prove that at least one (mixed-strategy) Nash equilibrium must exist in such a game. The key to Nash’s ability to prove existence far more generally than von Neumann lay in his definition of equilibrium. According to Nash, “an equilibrium point is an n-tuple such that each player’s mixed strategy maximizes his payoff if the strategies of the others are held fixed. Thus each player’s strategy is optimal against those of the others.” Putting the problem in this framework allowed Nash to employ the Kakutani fixed-point theorem in his 1950 paper to prove existence of equilibria. His 1951 paper used the simpler Brouwer fixed-point theorem for the same purpose.^[14]

Continue reading “Nash equilibrium” »

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