(Roughly) Daily

Posts Tagged ‘Grace Hopper

“Quantum computation is … nothing less than a distinctly new way of harnessing nature”*…

As the tools in the world around us change, the world– and we– change with them. The onslaught of AI is the change that seems to be grabbing most of our mindshare these days… and with reason. But there are, of course, other changes (in biotech, in materials science, et al.) that are also going to be hugely impactful.

Today, a look at the computing technology stalking up behind AI: quantum computing. As enthusiasts like David Deutsch (author of the quote above) argue, it can have tremendous benefits, perhaps especially in our ability to model (and thus better understand) our reality.

But quantum computing will, if/when it arrives, also present huge challenges to us as individuals and as societies– perhaps most prominently in its threat to the ways in which we protect our systems and our information: We’ve felt pretty safe for decades, secure in the knowledge that we could lose passwords to phising or hacks, but that it would take the “classical” computers we have 1 billion years to break today’s RSA-2048 encryption. A quantum computer could crack it in as little as a hundred seconds.

The technology has been “somewhere on the horizon” for 30 years… so not something that has seemed urgent to confront. But progress has accelerated; a recent Google paper reports on a programming and architectural breakthrough that greatly reduces the computing resources necessary to break classical cryptography… putting the prospect of “Q-Day” (the point at which quantum computers become powerful enough to break standard encryption methods (RSA, ECC), endangering global digital security) much closer, which would put everything from crypto-wallets to our e-banking accounts at risk.

Charlie Wood brings us up to speed…

Some 30 years ago, the mathematician Peter Shor took a niche physics project — the dream of building a computer based on the counterintuitive rules of quantum mechanics — and shook the world.

Shor worked out a way for quantum computers to swiftly solve a couple of math problems that classical computers could complete only after many billions of years. Those two math problems happened to be the ones that secured the then-emerging digital world. The trustworthiness of nearly every website, inbox, and bank account rests on the assumption that these two problems are impossible to solve. Shor’s algorithm proved that assumption wrong.

For 30 years, Shor’s algorithm has been a security threat in theory only. Physicists initially estimated that they would need a colossal quantum machine with billions of qubits — the elements used in quantum calculations — to run it. That estimate has come down drastically over the years, falling recently to a million qubits. But it has still always sat comfortably beyond the modest capabilities of existing quantum computers, which typically have just hundreds of qubits.

However, two different groups of researchers have just announced advances that notably reduce the gap between theoretical estimates and real machines. A star-studded team of quantum physicists at the California Institute of Technology went public with a design for a quantum computer that could break encryption with only tens of thousands of qubits and said that it had formed a company to build the machine. And researchers at Google announced that they had developed an implementation of Shor’s algorithm that is ten times as efficient as the best previous method.

Neither company has the hardware to break encryption today. But the results underscore what some quantum physicists had already come to suspect: that powerful quantum computers may be years away, rather than decades. “If you care about privacy or you have secrets, then you better start looking for alternatives,” said Nikolas Breuckmann, a mathematical physicist at the University of Bristol, who did not work on either of the papers.

While the new results may provide a jolt for the policymakers and corporations that guard our digital infrastructure, they also signal the rapid progress that physicists have made toward building machines that will let them more thoroughly explore the quantum world.

“We’re going to actually do this,” said Dolev Bluvstein, a Caltech physicist and CEO of the new company, Oratomic…

[Wood unpacks the history of the development of the technology and explores the challenges that remain; he concludes…]

… If any group succeeds at building a quantum computer that can realize Shor’s algorithm, it will mark the end an era — specifically, the “Noisy Intermediate Scale Quantum” era, as Preskill dubbed the pre-error-correction period in a 2018 paper. Each researcher has a vision for what to pursue first with a machine in the new “fault-tolerant” era.

[Robert] Huang said he would start by running Shor’s algorithm, just to prove that the device works. After that, he said he would try to use it to speed up machine learning — an application to be detailed in coming work.

Most of the architects building quantum computers, whether at Oratomic or other startups, are physicists at heart. They’re interested in physics, not cryptography. Specifically, they’re interested in all the things a computer fluent in the language of quantum mechanics could teach them about the quantum realm, such as what sort of materials might become superconductors even at warm temperatures. Preskill, for his part, would like to simulate the quantum nature of space-time.

The Caltech group knows it has years of work ahead before any of its dreams have a chance of coming true. But the researchers can’t wait to get started. “Pick a cooler life quest than building the world’s first quantum computer with your friends!” said a jubilant Bluvstein, reached by phone shortly before their paper went live, before rushing off to celebrate…

Eminently worth reading in full: “New Advances Bring the Era of Quantum Computers Closer Than Ever,” from @walkingthedot.bsky.social in @quantamagazine.bsky.social.

* David Deutsch, The Fabric of Reality

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As we prepare, we might take a moment to appreciate just how vastly and deeply the legacy systems challenged by quantum computing run, recalling that on this date in 1959 Mary Hawes, a computer scientist for the Burroughs Corporation held a meeting of computers users, manufacturers, and academics at the University of Pennsylvania aimed at creating a common business oriented programming language. At the meeting, representative Grace Hopper suggested that they ask the Department of Defense to fund the effort to create such a language. Also attending was Charles Phillips who was director of the Data System Research Staff at the DoD and was excited by the possibility of a common language streamlining their operations. He agreed to sponsor the creation of such a language. This was the genesis of what would eventually become the COBOL language.

To this day COBOL is still the most common programming language used in business, finance, and administrative systems for companies and governments, primarily on mainframe systems, with around 200 billion lines of code still in production use… all of which are in question and/or at risk in a world of quantum computing.

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“I like to think (it has to be) of a cybernetic ecology where we are free of our labors and joined back to nature, returned to our mammal brothers and sisters”*…

A.I. pioneer Dario Amodei with a positive scenario for artificial intelligence…

I think and talk a lot about the risks of powerful AI. The company I’m the CEO of, Anthropic, does a lot of research on how to reduce these risks. Because of this, people sometimes draw the conclusion that I’m a pessimist or “doomer” who thinks AI will be mostly bad or dangerous. I don’t think that at all. In fact, one of my main reasons for focusing on risks is that they’re the only thing standing between us and what I see as a fundamentally positive future. I think that most people are underestimating just how radical the upside of AI could be, just as I think most people are underestimating how bad the risks could be.

In this essay I try to sketch out what that upside might look like—what a world with powerful AI might look like if everything goes right. Of course no one can know the future with any certainty or precision, and the effects of powerful AI are likely to be even more unpredictable than past technological changes, so all of this is unavoidably going to consist of guesses. But I am aiming for at least educated and useful guesses, which capture the flavor of what will happen even if most details end up being wrong. I’m including lots of details mainly because I think a concrete vision does more to advance discussion than a highly hedged and abstract one…

How AI could transform the world for the better: “Machines of Loving Grace,” from @DarioAmodei. Eminently worth reading in full…

A (similarly positive, but slightly more focused) piece from a team at Deepmind: “AI for Science.”

Apposite (if not opposite): “Shoggoths amongst us,” from Henry Farrell, and an earlier (R)D, “We ceased to be the lunatic fringe. We’re now the lunatic core.”

See also: “AI Isn’t Your God—But It Might Be Your Intern.”

* Richard Brautigan, “All Watched Over By Machines Of Loving Grace” (the source of Amodei’s title)

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As we ponder the perplexities of progress, we might send carefully-calculated birthday greetings to Grace Brewster Murray Hopper; she was born on this date in 19o6.  A seminal computer scientist and Rear Admiral in the U.S. Navy, “Amazing Grace” (as she was known to many in her field) was one of the first programmers of the Harvard Mark I computer (in 1944), invented the first compiler for a computer programming language, and was one of the leaders in popularizing the concept of machine-independent programming languages– which led to the development of COBOL, one of the first high-level programming languages.

Hopper also (inadvertently) contributed one of the most ubiquitous metaphors in computer science: she found and documented the first computer “bug” (in 1947).

She has both a ship (the guided-missile destroyer USS Hopper) and a super-computer (the Cray XE6 “Hopper” at NERSC) named in her honor.

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Written by (Roughly) Daily

December 9, 2024 at 1:00 am

“One thing I’ve learned over time is, if you hit a golf ball into water, it won’t float”*…

Happy New Year!

In the spirit of Tom Whitwell’s lists, Jason Kottke‘s collection of learnings from 2023-gone-by…

Purple Heart medals that were made for the planned (and then cancelled) invasion of Japan in 1945 are still being given out to wounded US military personnel.

The San Francisco subway system still runs on 5 1/4-inch floppies.

Bottled water has an expiration date — it’s the bottle not the water that expires.

Multicellular life developed on Earth more than 25 separate times.

Horseshoe crabs are older than Saturn’s rings.

Ernest Hemingway only used 59 exclamation points across his entire collection of works.

MLB broadcaster Vin Scully’s career lasted 67 seasons, during which he called a game managed by Connie Mack (born in 1862) and one Julio Urías (born in 1996) played in.

Almost 800,000 Maryland licence plates include a URL that now points to an online casino in the Philippines because someone let the domain registration lapse.

Dozens more at: “52 Interesting Things I Learned in 2023.”

* Arnold Palmer

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As we live and learn, we might spare a thought for Grace Brewster Murray Hopper; she died on this date in 1992.  A seminal computer scientist and Rear Admiral in the U.S. Navy, “Amazing Grace” (as she was known to many in her field) was one of the first programmers of the Harvard Mark I computer (in 1944), invented the first compiler for a computer programming language, and was one of the leaders in popularizing the concept of machine-independent programming languages– which led to the development of COBOL, one of the first high-level programming languages.

Hopper also (inadvertently) contributed one of the most ubiquitous metaphors in computer science: she found and documented the first computer “bug” (in 1947).

She has both a ship (the guided-missile destroyer USS Hopper) and a super-computer (the Cray XE6 “Hopper” at NERSC) named in her honor.

Source

Written by (Roughly) Daily

January 1, 2024 at 1:00 am

“The brain is a wonderful organ; it starts working the moment you get up in the morning and does not stop until you get into the office”*…

For as long as humans have thought, humans have thought about thinking. George Cave on the power and the limits of the metaphors we’ve used to do that…

For thousands of years, humans have described their understanding of intelligence with engineering metaphors. In the 3rd century BCE, the invention of hydraulics popularized the model of fluid flow (“humours”) in the body. This lasted until the 1500s, supplanted by the invention of automata and the idea of humans as complex machines. From electrical and chemical metaphors in the 1700s to advances in communications a century later, each metaphor reflected the most advanced thinking of that era. Today is no different: we talk of brains that store, process and retrieve memories, mirroring the language of computers.

I’ve always believed metaphors to be helpful and productive in communicating unfamiliar concepts. But this fascinating history of cognitive science metaphors shows that flawed metaphors can take hold and limit the scope for alternative ideas. In the worst case, the EU spent 10 years and $1.3 billion building a model of the brain based on the incorrect belief that the brain functions like a computer…

Thinking about thinking, from @George_Cave in @the_prepared.

Apposite: “Finding Language in the Brain.”

* Robert Frost

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As we cogitate on cognition, we might send carefully-computed birthday greetings to Grace Brewster Murray Hopper.  A seminal computer scientist and Rear Admiral in the U.S. Navy, “Amazing Grace” (as she was known to many in her field) was one of the first programmers of the Harvard Mark I computer (in 1944), invented the first compiler for a computer programming language, and was one of the leaders in popularizing the concept of machine-independent programming languages– which led to the development of COBOL, one of the first high-level programming languages.

Hopper also (inadvertently) contributed one of the most ubiquitous metaphors in computer science: she found and documented the first computer “bug” (in 1947).

She has both a ship (the guided-missile destroyer USS Hopper) and a super-computer (the Cray XE6 “Hopper” at NERSC) named in her honor.

 source

Written by (Roughly) Daily

December 9, 2022 at 1:00 am

“Reality is frequently inaccurate”*…

Machine learning and what it may teach us about reality…

Our latest paradigmatic technology, machine learning, may be revealing the everyday world as more accidental than rule-governed. If so, it will be because machine learning gains its epistemological power from its freedom from the sort of generalisations that we humans can understand or apply.

The opacity of machine learning systems raises serious concerns about their trustworthiness and their tendency towards bias. But the brute fact that they work could be bringing us to a new understanding and experience of what the world is and our role in it…

The world is a black box full of extreme specificity: it might be predictable but that doesn’t mean it is understandable: “Learn from Machine Learning,” by David Weinberger (@dweinberger) in @aeonmag.

(image above: source)

* Douglas Adams, The Restaurant at the End of the Universe

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As ruminate on the real, we might send carefully-computed birthday greetings to Grace Brewster Murray Hopper.  A seminal computer scientist and Rear Admiral in the U.S. Navy, “Amazing Grace” (as she was known to many in her field) was one of the first programmers of the Harvard Mark I computer (in 1944), invented the first compiler for a computer programming language, and was one of the leaders in popularizing the concept of machine-independent programming languages– which led to the development of COBOL, one of the first high-level programming languages.

Hopper also found and documented the first computer “bug” (in 1947).

She has both a ship (the guided-missile destroyer USS Hopper) and a super-computer (the Cray XE6 “Hopper” at NERSC) named in her honor.

 source