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Intel Enters the Quantum Computing Horse Race With 12-Qubit Chip

But before quantum physics revolutionizes computing, Intel and rivals will have to learn how to make vastly more powerful machines.

Intel has built a quantum processor called Tunnel Falls that it will offer to research labs hoping to make the revolutionary computing technology practical.

The Tunnel Falls processor, announced Thursday, houses 12 of the fundamental data processing elements called qubits. It’s a major step in the chipmaker’s attempt to develop quantum computing hardware it hopes will eventually surpass rivals.

Intel, unlike most of its rivals, makes its qubits from individual electrons housed in computer chips that are cousins to those that power millions of PCs. The company is lagging behind. Rivals like IBM, Google, Quantinuum and IonQ have been offering quantum computers for years, but Intel believes tying its fortunes to conventional chip technology will ultimately enable faster progress.

«To me, it’s natural to use the tools already developed rather than having to develop new tools,» said Jim Clarke, director of quantum computing hardware at Intel Labs. Intel makes its own quantum computing chips at its D1 fab in Oregon.

You won’t buy your own quantum computer, but they could affect your life very directly. Among those investing in the technology are financial services companies seeking more profitable investments, materials science researchers hoping for better batteries, pharmaceutical companies trying to design better drugs and governments trying to crack adversaries’ encrypted communications.

Those challenges are out of reach of conventional computers, but quantum computing has the potential to tackle them by taking advantage of the weird physics of the ultrasmall. Today’s quantum computers aren’t generally practical, and the full promise of the technology remains years away, but physicists and engineers have made steady progress year after year.

Intel, an expert in large-scale manufacturing, hopes to help speed things along by building many quantum chips, which it calls quantum processing units, or QPUs. The University of Maryland, one of the centers benefiting from a US government program to accelerate quantum computing progress, will use Intel machines.

The quantum computing race

One notable feature of quantum computing is the tremendous variety of approaches. Intel is using electrons, storing data with a quantum mechanical property called spin that’s analogous to the two directions a top can spin. IBM and Google are using small electrical circuits of superconducting materials. IonQ and Quantinuum manipulate charged atoms stored in a trap. Other approaches involve neutral atoms and even that most fleeting of particles, the photon.

At a sufficiently small scale, quantum mechanics dominates physics and anything can become a qubit, quantum computing pioneer and MIT researcher Seth Lloyd said in an earlier interview. «It’s a question of whether you can massage them in the right way to convince them to compute.»

In other words, quantum computing isn’t a horse race like in the traditional computer chip market. It’s more like a horse pitted against a falcon, a motorcycle and an Olympic sprinter.

Intel likes its approach. Tunnel Falls is in manufacturing today, but the company very soon will «tape out» its successor, meaning the design is finished, and it’s begun designing the model after that, Clarke said. Twelve qubits is a tiny fraction of what’s needed for useful quantum computers, but Intel started with a simple approach designed for fast improvement and sustained progress over the years required to make serious quantum computers.

A tiny Intel Tunnel Falls quantum computer chip perched on a fingertip A tiny Intel Tunnel Falls quantum computer chip perched on a fingertip

Intel’s Tunnel Falls quantum computer test chip perched on a fingertip

Intel

«The next big milestone is when we have a few thousand qubits,» a quantity that will let quantum computer engineers correct the frequent errors that plague qubit operations, Clarke said. «That’s probably three, four years, maybe five years away,» Clarke said. «And it’s probably the early 2030s or mid-2030s before we have a million cubits that are going to change the world.»

And Intel is engineering not just the QPUs, but the crucial data links that link each qubit to the outside world. Today’s quantum computers often look like high-tech chandeliers, with gleaming metal communication conduits looping down toward the processor, but that bulky design won’t work with thousands or millions of qubits, and Intel believes its control chips and chip interconnect technology will be necessary parts of an overall system.

Plenty of competitors

Intel is unusual in selecting photons housed in computer circuits for its quantum computing foundation. One of its biggest rivals, IBM, already offers multiple 127-qubit quantum computers for research and commercial use, with a 433-qubit machine up and running.

«We have a plan to get this out to hundreds of thousands of qubits using superconducting qubits,» said Jerry Chow, leader of IBM’s quantum computing hardware effort. IBM is working on quantum computer chips with a flock of code names — Egret, Heron, Condor, Crossbill — that are designed to prove out new technologies to reduce errors and improve the qubit-to-qubit connections that are central to the machines.

And it’s making progress. On Wednesday, it secured a coveted spot on the cover of the journal Nature for research showing its 127-qubit Eagle quantum computing chip can surpass conventional machines in simulating the materials physics that produce effects like magnetism.

Intel tried and rejected the supercomputing qubit approach, Clarke said. Its spin qubits are a million times smaller than a superconducting circuit, letting the company fit 25,000 of them on each 300mm silicon wafer that transits through its chip fabrication plant, called a fab. When Intel finds a problem building quantum chips, it figures out how to adapt the qubit to traditional chip manufacturing, not vice versa.

Disagreement with Intel’s approach

Such arguments haven’t persuaded others. Google is sticking with superconducting qubits.

«Superconducting qubits lead in critical metrics. We are confident they are the leading technology for the future of quantum supercomputers,» Google said in a statement, pointing to their processing speed and progress toward error correction to keep calculations on track longer. «We see a clear path to scale our technology to large-scale, error-corrected machines of general use.»

And IonQ Chief Executive Peter Chapman believes Intel’s approach is too inflexible for practical, large-scale quantum computers. His company is developing ion trap machines that scoot charged atoms around, letting different qubits interact with each other for computation. Fixing qubits onto the surface of a chip drastically complicates computations, he said.

«What worked in computing in the past — silicon-based processors — is not the right solution for the age of quantum,» Chapman said.

The deep disagreements about the best approach will perhaps be resolved as the machines evolve and grow larger. Intel’s plans rely on its manufacturing advantage, tapping into its experience building some of the most complicated electronics devices on the planet.

«Not everybody has a fab like this in their back pocket,» Clarke said.

Technologies

How Much Energy Do Your AI Prompts Consume? Google Just Shared Its Gemini Numbers

Current measurements of AI’s impact aren’t telling the full story. Google has offered a new method it hopes to standardize.

The explosion of AI tools worldwide is increasing exponentially, but the companies that make these tools often don’t express their environmental impact in detail. 

Google has just released a technical paper detailing measurements for energy, emissions and water use of its Gemini AI prompts. The impact of a single prompt is, it says, minuscule. According to its methodology for measuring AI’s impact, a single prompt’s energy consumption is about the equivalent of watching TV for less than 9 seconds. 

That’s quite in a single serving, except when you consider the variety of chatbots being used, with billions of prompts easily sent every day. 

On the more positive side of progress, the technology behind these prompts has become more efficient. Over the past 12 months, the energy of a single Gemini text prompt has been reduced by 33x, and the total carbon footprint has been reduced by 44x, Google says. According to the tech giant, that’s not unsubstantial, and it’s a momentum that will need to be maintained going forward.

Google did not immediately respond to CNET’s request for further comment.

Google’s calculation method considers much more

The typical calculation for the energy cost of an AI prompt ends at the active machine it’s been run on, which shows a much smaller per-prompt footprint. But Google’s method for measuring the impact of a prompt purportedly spans a much wider range of factors that paint a clearer picture, including full-system dynamic power, idle machines, data center overhead, water consumption and more.

For comparison, it’s estimated that only using the active TPU and GPU consumption, a single Gemini prompt uses 0.10 watt-hours of energy, 0.12 milliliters of water and emits 0.02 grams of carbon dioxide equivalent. This is a promising number, but Google’s wider methodology tells a different story. With more considerations in place, a Gemini text prompt uses 0.24Wh of energy, 0.26mL of water and emits 0.03 gCO2e — around double across the board. 

Will new efficiencies keep up with AI use?

Through a multilayered series of efficiencies, Google is continually working on ways to make AI’s impact less burdensome, from more efficient model architectures and data centers to custom hardware. 

With smarter models, use cases and tools emerging daily, those efficiencies will be critical as we immerse ourselves deeper in this AI reality. 

For more, you should stop using ChatGPT for these things.

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Technologies

Vivo Launches Mixed-Reality Headset, an Apple Vision Pro Competitor

Vivo Vision has many of the same design elements as Apple’s VR/AR, but is only available in China, for now.

Look-alikes of Apple products often pop up in China, and mixed-reality headsets have now joined the party. Chinese smartphone maker Vivo has introduced the Vivo Vision, a headset mixing both AR and VR, and it bears many similarities to the Apple Vision Pro.

The company announced the Vivo Vision Discovery Edition at its 30th anniversary celebration in Dongguan, China, saying it’s «the first MR product developed by a smartphone manufacturer in China, positioning Vivo as the first Chinese company to operate within both the smartphone and MR product sectors.»

The Vivo Vision, currently only an in-store experience in mainland China, has a curved glass visor, an aluminum external battery pack and downward-pointing cameras like the Vision Pro. But it also has some differences — an 180-degree panoramic field of view and a much lighter weight at 398 grams (versus the Vision Pro’s 650 grams).

CNET asked Vivo if it plans to sell the Vivo Vision to non-China markets, but the company did not immediately respond.

The Vivo Vision runs on OriginOS Vision, Vivo’s mixed-reality operating system. It supports 3D video recording, spatial photos and audio, and a 120-foot cinematic screen experience. 

The starting cost in China will be $1,395 (converted to US dollars), compared to the Vision Pro at $3,500.

Even if the Vivo Vision came to the consumer market in the US, it might not matter much to Apple’s bottom line. The Vision Pro hasn’t been a big seller, likely because of the price tag. Still, the headset market is expected to grow quickly over the next several years, and Apple is already working on new versions of the Vision Pro, including one that’s more affordable than the original. 

Jon Rettinger, a tech influencer with more than 1.65 million YouTube subscribers, says he’s not overly enthusiastic about VR/AR just yet. «It’s heavy, invasive and without a must-have use case,» Rettinger told CNET. «If the technology can go from goggles to glasses, I think we’ll see a significant rise. But if the current form factors stay, it will always be niche.

The YouTuber loves that the technology exists, but still doesn’t use it. «The honeymoon wore off. Aside from some gaming and content viewing, it’s still cumbersome, and I tend to go back to my laptop,» he said. 

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Technologies

Today’s NYT Strands Hints, Answers and Help for Aug. 22 #537

Here are hints and answers for the NYT Strands puzzle for Aug. 22, No. 537.

Looking for the most recent Strands answer? Click here for our daily Strands hints, as well as our daily answers and hints for The New York Times Mini Crossword, Wordle, Connections and Connections: Sports Edition puzzles.


Today’s NYT Strands puzzle has a fun theme, especially if you have ever read Agatha Christie books or played a few rounds of the board game Clue. If you need hints and answers, read on.

I go into depth about the rules for Strands in this story. 

If you’re looking for today’s Wordle, Connections and Mini Crossword answers, you can visit CNET’s NYT puzzle hints page.

Read more: NYT Connections Turns 1: These Are the 5 Toughest Puzzles So Far

Hint for today’s Strands puzzle

Today’s Strands theme is: Whodunit?

If that doesn’t help you, here’s a clue: Solve the crime

Clue words to unlock in-game hints

Your goal is to find hidden words that fit the puzzle’s theme. If you’re stuck, find any words you can. Every time you find three words of four letters or more, Strands will reveal one of the theme words. These are the words I used to get those hints but any words of four or more letters that you find will work:

  • REST, POEM, SOUR, SOURS, DIAL, HOLE, VOLE, ROLE, ROLES, VOLES, HOLES, DEEM, GAIT, SAME

Answers for today’s Strands puzzle

These are the answers that tie into the theme. The goal of the puzzle is to find them all, including the spangram, a theme word that reaches from one side of the puzzle to the other. When you have all of them (I originally thought there were always eight but learned that the number can vary), every letter on the board will be used. Here are the nonspangram answers:

  • HEIR, LOVER, RIVAL, SPOUSE, STRANGER, DETECTIVE

Today’s Strands spangram

Today’s Strands spangram is ITSAMYSTERY, with all the answers being characters common to mystery novels. To find it, look for the I that’s the farthest left letter on the top row, and wind down.

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