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Category: robotics/AI – Page 881

Twice As Powerful: Next-Gen AI Chip Mimics Human Brain for Power Savings

Hussam Amrouch has developed an AI-ready architecture that is twice as powerful as comparable in-memory computing approaches. As reported in the journal Nature, the professor at the Technical University of Munich (TUM) applies a new computational paradigm using special circuits known as ferroelectric field effect transistors (FeFETs). Within a few years, this could prove useful for generative AI, deep learning algorithms, and robotic applications.

The basic idea is simple: unlike previous chips, where only calculations were carried out on transistors, they are now the location of data storage as well. That saves time and energy.

“As a result, the performance of the chips is also boosted,” says Hussam Amrouch, a professor of AI processor design at the Technical University of Munich (TUM).

New Techniques From MIT and NVIDIA Revolutionize Sparse Tensor Acceleration for AI

Complimentary approaches — “HighLight” and “Tailors and Swiftiles” — could boost the performance of demanding machine-learning tasks.

Researchers from MIT

MIT is an acronym for the Massachusetts Institute of Technology. It is a prestigious private research university in Cambridge, Massachusetts that was founded in 1861. It is organized into five Schools: architecture and planning; engineering; humanities, arts, and social sciences; management; and science. MIT’s impact includes many scientific breakthroughs and technological advances. Their stated goal is to make a better world through education, research, and innovation.

The Illusion of Understanding: MIT Unmasks the Myth of AI’s Formal Specifications

Some researchers see formal specifications as a way for autonomous systems to “explain themselves” to humans. But a new study finds that we aren’t understanding.

As autonomous systems and artificial intelligence become increasingly common in daily life, new methods are emerging to help humans check that these systems are behaving as expected. One method, called formal specifications, uses mathematical formulas that can be translated into natural-language expressions. Some researchers claim that this method can be used to spell out decisions an AI will make in a way that is interpretable to humans.

Research Findings on Interpretability.

The Impact of AI on Medical Records — The Medical Futurist

You requested a video exploring the future of medical records, and your wish is our command!

We’re aware that administrative tasks are often the bane of a physician’s work, contributing significantly to burnout. So, let’s embark on a journey together to discover how the future might unfold, and whether artificial intelligence has the potential to lighten this heavy burden.

Using AI to optimize for rapid neural imaging

Connectomics, the ambitious field of study that seeks to map the intricate network of animal brains, is undergoing a growth spurt. Within the span of a decade, it has journeyed from its nascent stages to a discipline that is poised to (hopefully) unlock the enigmas of cognition and the physical underpinning of neuropathologies such as in Alzheimer’s disease.

At its forefront is the use of powerful electron microscopes, which researchers from the MIT Computer Science and Artificial Intelligence Laboratory (CSAIL) and the Samuel and Lichtman Labs of Harvard University bestowed with the analytical prowess of machine learning. Unlike traditional electron microscopy, the integrated AI serves as a “brain” that learns a specimen while acquiring the images, and intelligently focuses on the relevant pixels at nanoscale resolution similar to how animals inspect their worlds.

“SmartEM” assists connectomics in quickly examining and reconstructing the brain’s complex network of synapses and neurons with nanometer precision. Unlike traditional electron microscopy, its integrated AI opens new doors to understand the brain’s intricate architecture. “SmartEM: machine-learning guided electron microscopy” has been published on the pre-print server bioRxiv.

Nvidia CEO Jensen Huang says his AI powerhouse is ‘always in peril’ despite a $1.1 trillion market cap: ‘We don’t have to pretend…we feel it’

Nvidia is on a tear.

But “there are no companies that are assured survival,” Huang warned Thursday at the Harvard Business Review’s Future of Business event.

Nvidia in its 30-year history has faced several existential threats, which helps explain why Huang recently told the Acquired podcast that “nobody in their right mind” would start a company. For example, it almost went bankrupt in 1995 after its first chip, the NV1, failed to attract customers. It had to lay off half its employees before the success of its third chip, the RIVA 128, saved it a few years later.

“We have the benefit of building the company from the ground up and having not-exaggerated circumstances of nearly going out of business a handful of times,” Huang said this week, as Observer reported. “We don’t have to pretend the company is always in peril. The company is always in peril, and we feel it.”

Humane’s AI Pin up close

We spent 90 minutes with the pin and its founders at Humane’s SF offices.

A few hours after this morning’s big unveil, Humane opened its doors to a handful of press.

A few hours after this morning’s big unveil, Humane opened its doors to a handful of press. Located in a nondescript building in San Francisco’s SoMa neighborhood, the office is home to the startup’s hardware design teams.

An office next door houses Humane’s product engineers, while the electrical engineering team operates out of a third space directly across the street. The company also operates an office in New York, though the lion’s share of the 250-person staff are located here in San Francisco.

Today, much of the space is occupied by a series of demo stations (with a strict no filming policy), where different AI Pins are laid out in various state of undress, exposing their external machinations. Prior to attending these, however, Humane’s co-founders stand in front of a small group of chairs, flanking a flat screen that lays out the company’s vision.

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