Lifeboat Foundation

Artificial intelligence is a superior lifeform that humans are creating, and many AI researchers have outlined various scenarios in which this technology can pose an existential risk to humanity that could result in the literal end of the world.

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Engineers in Japan just shattered the world record for the fastest internet speed, achieving a data transmission rate of 319 Terabits per second (Tb/s), according to a paper presented at the International Conference on Optical Fiber Communications in June. The new record was made on a line of fibers more than 1,864 miles (3,000 km) long. And, crucially, it is compatible with modern-day cable infrastructure.

A team of researchers at Duke University and their collaborators have uncovered the atomic mechanisms that make a class of compounds called argyrodites attractive candidates for both solid-state battery electrolytes and thermoelectric energy converters.

The discoveries—and the machine learning approach used to make them—could help usher in a new era of energy storage for applications such as household battery walls and fast-charging electric vehicles.

The results appeared online May 18 in the journal Nature Materials.

May 22 (Reuters) — Nvidia Corp (NVDA.O) on Monday said it has worked with the U.K.’s University of Bristol to build a new supercomputer using a new Nvidia chip that would compete with Intel Corp (INTC.O) and Advanced Micro Devices Inc (AMD.O).

Nvidia is the world’s top maker of graphics processing units (GPUs), which are in high demand because they can be used to speed up artificial intelligence work. OpenAI’s ChatGPT, for example, was created with thousands of Nvidia GPUs.

But Nvidia’s GPU chips are typically paired with what is called a central processing unit (CPU), a market that has been dominated by Intel and AMD for decades. This year, Nvidia has started shipping its own competing CPU chip called Grace, which is based on technology from SoftBank Group Corp-owned (9984.T) Arm Ltd.

Errors are the Achilles’ heel of quantum computation, cropping up at random and threatening to rui.

Meta has created an AI language model that (in a refreshing change of pace) isn’t a ChatGPT clone. The company’s Massively Multilingual Speech (MMS) project can recognize over 4,000 spoken languages and produce speech (text-to-speech) in over 1,100. Like most of its other publicly announced AI projects, Meta is open-sourcing MMS today to help preserve language diversity and encourage researchers to build on its foundation. “Today, we are publicly sharing our models and code so that others in the research community can build upon our work,” the company wrote. “Through this work, we hope to make a small contribution to preserve the incredible language diversity of the world.”

Speech recognition and text-to-speech models typically require training on thousands of hours of audio with accompanying transcription labels. (Labels are crucial to machine learning, allowing the algorithms to correctly categorize and “understand” the data.) But for languages that aren’t widely used in industrialized nations — many of which are in danger of disappearing in the coming decades — “this data simply does not exist,” as Meta puts it.

Meta used an unconventional approach to collecting audio data: tapping into audio recordings of translated religious texts. “We turned to religious texts, such as the Bible, that have been translated in many different languages and whose translations have been widely studied for text-based language translation research,” the company said. “These translations have publicly available audio recordings of people reading these texts in different languages.” Incorporating the unlabeled recordings of the Bible and similar texts, Meta’s researchers increased the model’s available languages to over 4,000.

Seattle-based startup Jetoptera is designing vertical take-off and landing (VTOL) vehicles with bladeless propulsion systems — potentially making the future of urban flight quiet, safer, and faster.

The challenge: The proportion of the global population living in cities is expected to increase from 50% today to nearly 70% by 2050, meaning our already crowded urban streets are likely to become even more congested.

On Wednesday, Google displayed how Bard, its new AI robot, could be used to write up job listings from a simple one line prompt. Microsoft has demonstrated how a ChatGPT-powered tool can write entire articles in Word.

“There are a tonne of sales representatives doing a lot of banal work to compose prospecting emails,” says Rob Seaman, a senior vice president at workplace messaging company Slack, which is working with OpenAI to embed ChatGPT into its app as a kind of digital co-worker.

New AI tools may remove some of the most tedious aspects of such roles. But based on past evidence, technology also threatens to create a whole new class of menial roles.

Metalenses migrate to smartphones.

Metalenz came out of stealth mode in 2021, announcing that it was getting ready to scale up production of devices. Manufacturing was not as big a challenge as design because the company manufactures metasurfaces using the same materials, lithography, and etching processes that it uses to make integrated circuits.

In fact, metalenses are less demanding to manufacture than even a very simple microchip because they require only a single lithography mask as opposed to the dozens required by a microprocessor. That makes them less prone to defects and less expensive. Moreover, the size of the features on an optical metasurface are measured in hundreds of nanometers, whereas foundries are accustomed to making chips with features that are smaller than 10 nanometers.