Loser: Still Waiting For Nanotube Memory Chip

Nantero’s alternative to flash memory has reached its sell-by date

5 min read
illustration of chip inside an hourglass
Illustration: Bryan Christie Design

Back in October 2001, a Woburn, Mass., start-up called Nantero said it was going to supplant flash memory chips. Business journalists took note: flash memory was then a US $7.8 billion market, and it was growing fast. Even more alluring, Nantero’s technology, based on carbon nanotubes, seemed to be the opening salvo in the nano­technology revolution those journalists had been promising their readers for years.

Nantero called its prospective product the NRAM, the N standing for “Nanotube-based/Nonvolatile.” The company’s publicity people painted a picture of a computer freed from its last moving part—the hard drive—and thus capable of booting up instantly and surviving hard knocks.

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Posits, a New Kind of Number, Improves the Math of AI

The first posit-based processor core gave a ten-thousandfold accuracy boost

4 min read
Squares with 0s and 1s form a colorful brain shape and blue background.
Hiroshi Watanabe/Getty Images

Training the large neural networks behind many modern AI tools requires real computational might: For example, OpenAI’s most advanced language model, GPT-3, required an astounding million billion billions of operations to train, and cost about US $5 million in compute time. Engineers think they have figured out a way to ease the burden by using a different way of representing numbers.

Back in 2017, John Gustafson, then jointly appointed at A*STAR Computational Resources Centre and the National University of Singapore, and Isaac Yonemoto, then at Interplanetary Robot and Electric Brain Co., developed a new way of representing numbers. These numbers, called posits, were proposed as an improvement over the standard floating-point arithmetic processors used today.

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AI Matches Doctors in Screening  for Tuberculosis

TB is the second-leading cause of death by an infectious disease, behind only COVID-19

4 min read
image of chest x-ray
Getty Images

A killer could be stopped cold—or at least be limited in its deadly toll—thanks to AI.

Apart from COVID-19, tuberculosis (TB) is the leading cause of death by an infectious disease worldwide, despite being largely preventable and treatable. While the World Health Organization (WHO) recommends using chest X-rays to help identify likely cases of TB, many health-care centers lack adequate radiologists to interpret these X-rays. In a study published on 6 September in the journal Radiology, researchers at Google along with colleagues from India, South Africa, and Zambia showed that their deep-learning algorithm could identify cases of TB from chest X-rays as well as radiologists could.

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Introduction to Peer-to-Peer Streaming and GPU Processing in Data Acquisition Systems

Learn about the basics and benefits of peer-to-peer streaming and GPU post-processing in data acquisition systems

1 min read
Teledyne

Real-time digital signal processing is a vital part of many of today's data acquisition systems, and affordable graphics processing units (GPUs) offer a great complement to onboard field-programmable gate arrays (FPGAs).

Join Teledyne SP Devices for an introductory webinar about the basics and benefits of peer-to-peer streaming and GPU post-processing in data acquisition systems.

Register now for this free webinar!

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