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Jack Vaughan

Reporter’s Notebook – At MIT Tech Review Future Compute 2023: Navigating the straits of semis

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[May 9, 2023 ] – When the US last year announced new export rules on advanced chips,  the role of semiconductors in modern foreign affairs reached a new zenith. The chips have assumed the stature of oil in today’s geopolitics and depriving China of the chips now seems a strategic objective.

Unease has only grown with the appearance of the ChatGPT AI Large Language Model, which is a chip-hungry, power-guzzling presence ready to take over the world, to hear networks of experts and Cassandras tell it. Just as unsettling are Chinese maneuvers around Taiwan, a crucial center of global chip production.

Such activity formed a partial backdrop for the MIT Technology Review’s recent Future Compute 2023 conference at the Cambridge, Mass. Campus. Semiconductor issues were probed in a Q&A session featuring Chris Miller, Tufts University lecturer and author.

Miller said the semiconductor has taken on an outsized role in strategizing on China, and that the focus now is both on economics and defense.

”China spends as much money importing chips each year as importing oil,” he said. “You can’t understand the structure of the world economy without putting semiconductors at the center of your analysis.”

This is increasingly true for economic issues, Miller continued. Semiconductors that drive computers and embedded systems are top of mind when defense ministries and intelligence agencies think about future procurements.

“What they know is that over the past half century one of the key forces that’s transformed the way militaries fight has been computing power,” according to Miller, who traced the developments leading to the present predicament in “Chip War: The Fight for the World’s Most Critical Technology,” a recent noteworthy [Financial Times Book of the Year 2022] look at semiconductor industry history and its ever-shifting role in the larger body politic.

“Chip War” is described by a New York Times reviewer as something of a nonfiction thriller in which ‘pocket-protector men’ at Fairchild Semiconductor and Intel  tamed the raw transistor, fashioned the Integrated Circuit, outdid the Soviet Union, and left a war weary Europe in the dust as they formed what’s now Silicon Valley. Many of those developments bear review as governments’ and companies’ take on present complexities.

The complexities include more seemingly modest products than high-end processors, Miller indicated. Simpler chips that complement the hot processers grow in importance as well.

“The entire electronics supply chain is actually beginning to shift. It’s not only at the chip level, it’s also electronics assembly and simpler components,” Miller said, adding that a reduction in China’s level of server assembly has led to a major increase in Mexico’s market share in that field.

The also point emergence of new market dynamics as large companies take on design of their own chips, which could be spurred for a wider range of companies as US Chips Act R&D funding addresses the need for less expensive chip design processes.

A qubit for your thoughts

Infant quantum computing looms as an adjacent technology where geopolitical ambitions may play out.

China, the US the EU, and countries such as Australia, Singapore, and Canada now devote research monies to pursue such quantum efforts. They stir this new ground at the same time they test the limits of Moore’s Law – the perceived dead end for further large-scale silicon chip integration, which Tuft’s Miller cites as a fundamental challenge facing the chip industry.

However, quantum technology is still-raw technology – the quantum researchers on the main are still found toiling at the qubit level with lab rigs and signal scopes – that is, the quantum equivalent of the lone transistor work that preceded development of the Integrated Circuit.

A high-point of the Future Compute 2023 agenda for me was a visit to MIT’s Engineering Quantum Systems Group’s labs. Smart people are working hard on this frontier technology. And, with notable exceptions, there is knowledge sharing going on.

But, in a conference panel on quantum at the event, the impression emerged that quantum computing needed a large-scale working version of a quantum computer before the international competition for quantum computing would reach a less-sanguine stage akin to that the advanced CPU, GPU, NPU and network processing chips now experience.

For his part, at Future Compute, Chris Miller hesitated somewhat in responding to an audience question on quantum computing.

“I struggle to say anything that intelligent on quantum computing, both because I’m really not an expert in computing, but also because there’s a chip industry that I can study and I know how to talk about, whereas quantum computing is still a prospective industry,” he said. “We all hope it will materialize but it hasn’t materialized in a practical form.”

My take

Global chip wars must be viewed in the context of a real war underway in Ukraine. It has exposed the pivotal role of new technology in the exercise of war, as well as the vulnerability of the supply chains that feed modern commerce. It’s also pushed diplomacy to the sidelines, narrowing the opportunity for maneuver in the semiconductor straits.

Reporter’s Notebook: At Quantum.Tech 2023 in Boston

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[Boston/May 2, 2023] — Its mainstream profile is a bit more modest than in recent years, but quantum computing today continues to inch forward, promising future breakthroughs based on the stranger properties of electrons, atoms, ions and photons.

Quantum computing advocates project a time when the binary-state bits of classical computing are surpassed – or complemented, in the case of the more forgiving futurists — by quantum qubits capable of handling multiple states. And venture funding is active. McKinsey estimates in 2022 investors put $2.35 billion into quantum tech start-ups. Recent weeks have seen investments on several continents. These include:

*Dell Technologies Capital announcing funding a $12M seed extension investment in Quantum Source, an Israel-based company pursing photonic quantum technologies;

*Molten Ventures, Altair, the National Security Strategic Investment Fund and others announcing a $16.5 million round for UK-based Riverlane, which creates software and hardware to address the problem of galloping error rates as machines scale up their qubit counts – a basic but incomplete measure of quantum processing; and

*Funding by ParticleX for Quantier, an off-shoot of Hong Kong University of Science and Technology, said to fashion laser lights to control atoms at room temperature.

The activity of governments in such funding is common and understandable. For them the risk of misspent money is outweighed by the risk of other countries gaining a potentially key technological edge.

The startups need funding, but also increasingly need to find immediate use cases, as the difficulties facing some quantum pioneers highlights. D-Wave and Rigetti Computing, both of which turned to SPAC vehicles to ply the public markets, have found themselves with somewhat curtailed money ramps, as disclosed in recent financial reports.

But enthusiasm is still strong, as witnessed at last week’s Quantum.Tech 2023 conference here. Emergent themes held that this is a global phenomenon important to nation states of all sizes, that qubit counts matter less than qubit quality, and that vendors and users alike are looking to move past the present era of noisy intermediate-scale quantum (NISQ) computing – that is to create more capable qubits in greater numbers.

Quantum computing scorecards are more than ever a jumble of types, as small labs come forward with completely different approaches to basic quantum computing processes. Where not that long ago superconducting and trapped-ion approaches were the main game, processing modalities  based on photonics, neutral atoms, and silicon-based spin methods now vie for attention.

Marathona est, non sprint

Manfred Rieck, VP, Individual Software Development, Deutsche Bahn, sees quantum efforts feeding other advanced computing efforts. He spoke at the Boston event on quantum computing, picturing it as the next part of multinationals’ tech stacks that may also include AI, IoT, big data and digital twins.

He suggested, for example, that quantum computers could help in building fine-grain simulations for digital twins that design and operate transportation in the future, speaking with us in an interview.

Rieck marks progress of late, as quantum efforts combining the work of both physicists and computer scientists move out of the university, and into industry.

Moreover, he sees the struggles of some quantum players as a natural thing that happens with quantum-tech startups.

“I think companies are coming in and going out of the game and sometimes it works and sometimes not. At the same time, you see more and more interest in what happens in large industries,” he said. For vendors and buyers alike, he advised, the focus should be less on ‘quantum’ and more on business benefits.

As part of that, customers will look to companies that have long-term management skills to complement their belief in quantum computing’s radical promise.

One notion Rieck disavows is that quantum computing is entering a down phase, one some liken to the season of “winter.” He prefers the runner’s analogy – the quantum journey is a marathon, not a sprint, he told Quantum Tech attendees.

Hybridization erit belli

For Florian Neukart, who was deeply involved in some early Volkswagen AG quantum work, hybridization is the next step. Hybridization combines quantum computing along with classical high-performance computing, according to Neukart, who now serves as chief product officer at Terra Quantum, which provides “Quantum as a Service” in the form of algorithmic, hardware and security offerings.

“When we say hybrid, it means combining these two efficiently using an operating system using hybrid algorithms that sit on top,” said Neukart, who took part in a panel discussion on quantum’s path to commercialization at Quantum Tech 2023.

The growth in approaches based on hybrids can be drowned out by the quantum technology community’s natural preoccupation with quantum processing chips. But they bear watching.

“For the current era, where the quantum computing devices are error-prone and not perfect, or as big as we want them to be, hybridization will be a strategy, and it will carry on into the future,” he  told us. Examples of hybridization in action are recently developed quantum algorithms St. Gallen, Switzerland-based Terra Quantum undertook with German specialty chemical firm Evonik Industries to improve fluid mixing simulations and shape optimization for production parts of mixers.

Neukart agrees with the contention that quantum computing’s near future will be more influenced by computer science community members than in the past.

“People in classical high-performance computing really know how to scale systems, how to operate these systems cost effectively,” he said. That same community also is familiar with the work involved in integrating new algorithms into an existing environment – which is also among the many hurdles the quantum computing crew is now facing.

Hortus curae tuae

A software platform intended to put quantum processing in the hands of a broad group of users is the objective of Austin, Texas-based Strangeworks. At the Boston event, the five-year-old company highlighted updates to its platform said to allow  subject matter experts to  access “a marketplace of pre-packaged applications for everything from optimization and kernel alignment to variational quantum eigensolvers and neural networks.”

This comes after recent completion of a $24-million funding round led by Hitachi Ventures, with investments from IBM, Raytheon, and others.

“We’ve added abstraction layers to make it easier for subject matter experts – and everybody else – to take advantage of these tools. Below them, developers can open up pre-packaged applications and change the parameters,” Strangeworks founder and CEO William ‘whurley’ Hurley told us at Quantum Tech 2023.

We asked how does Hurly gauge the progress or lack of progress with quantum computing today.

“The fact is, is these machines are useful today,” he responded. “They work for material design, a lot of chemistry problems. Finance is starting to really get its legs. But they don’t match anywhere near the hype the industry has put out about them.”

And, he’s not averse to the term ‘quantum winter.’ Hurley said a challenging economic climate can strengthen an industry now desperately in search of skilled talent.

“We are entering –  whether anybody wants to say or not – a quantum winter, and this is a good thing. Everybody associates a quantum winter, or a downturn in funding, or whatever,  as this big, dramatic event,” he said. “In reality, it’s kind of like pruning your rosebush, or taking care of your garden.” – Jack Vaughan

The March of the Language Models

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[April 17, 2023] – Had the opportunity to speak with Forrester Analyst Ronan Curran recently for a VentureBeat article. Of course, the topic was ChatGPT, generative AI, and Large Language Models.

His counsel was both optimistic and cautionary – a good summation of the bearings IT decision makers should set as they begin yet another tango with a new technology meme.

A handy summarizer-paraphraser tells me that Curran told VentureBeat that it would be a mistake to underestimate the technology, although it is still difficult to critically examine the many potential use cases for generative AI.

Yes, such applies to each technical challenge – every day. And it bears repeating as each new technology whispers or yells that the fundamental rules no longer apply – and yet they do.

Looking back on my conversation with Curran, I find insight in what some would say is obvious. The large language models are … large! And, as Curran told me, because they are large, they cost a lot to compute and train. This reminds us, as others have, that the LLM should be viewed like polo or horse racing – as a game for the rich.

Why do we say game for the rich? On one level, the LLM era stacks up as megacloud builders’ battle, albeit with aspects of the playground grudge match. Microsoft leader Satya Nadella, who had the thankless task of competing with Google on the search front, almost seems to chortle: “This new Bing will make Google come out and dance, and I want people to know that we made them dance.”

For the cloud giants, the business already had aspects of a war of attrition, as they staked data center regions across the globe. The folks at Semianalysis.com have taken a hard stab at estimating a day in the life of an LLM bean counter, and they suggest a “model indicating that ChatGPT costs $694,444 per day to operate in compute hardware costs.” Of course, these are back of the envelope estimates – and the titans that host LLMs will look to engineer savings.

The new LLM morning summons to mind a technology that  consumed  much attention not so long ago: Big Data. The magic of Hadoop had a difficult time jumping from the likes of Google, Facebook and Netflix to the broader market. Maybe Big Data should have been named ‘Prodigious Data’ – because that would have offered fairer warning to organizations that had to gather such data, administer it, and come up with clever and profitable use cases.

“What is Big Data good for?” was a common question, even in its heyday. Eventually the answer was “machine learning”.

Much of Big Data remained in the realm of the prototype. In the end, it was a step forward for enterprise analytics. Successes and failures alike came under the banner of prototyping. Clearly, experimentation is where we are now with ChatGPT.

The more interesting future for more people may lie in outcomes with small language models, Forrester’s Curran told me. These will succeed or fail on a use case by use case basis.

As industry observer Benedict Evans writes in “ChatGPT and the Imagenet moment,” ChatGPT feels like a step-change forward in the evolution of machine learning. It falls something short of sentience. There is potential but there are plenty of questions to answer before its arc can be well gauged.  [eof]

Read “Forrester: Question generative AI uses before experimentation” – VentureBeat Feb 24, 2023
https://venturebeat.com/ai/forrester-question-generative-ai-uses-before-experimentation/

Read “ChatGPT and the Imagenet moment” – ben-evans.com Dec 14, 2022
https://www.ben-evans.com/benedictevans/2022/12/14/ChatGPT-imagenet

The Inference Cost Of Search Disruption – Large Language Model Cost Analysis – Semianalysis.com Feb 9, 2023
https://www.semianalysis.com/p/the-inference-cost-of-search-disruption

“Mythical Man-Month” Author Frederick Brooks, at 91

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[Dec 20, 2022] – Noting here the passing at 91 last month of Frederick Brooks, director of some of IBM’s most important mainframe-era programming projects. He was a key figure in establishing the idea that software projects should be intelligently engineered and organized.

He helped as much as anyone to move the mysterious art of tinkering with computer code toward a profession capable of repeatable results. “The Mythical Man-Month,” his 1975 distillation of years of development management, became a common reference work in many a developer’s desk library.

La Brea Tar Pits – Huntington Library.

Working at IBM in the 1950s and 1960s, and spearheading development of the vaunted IBM/360, Brooks gave a lie to notions that were bedrock in hardware-software projects, and came up with a few notable inventions as well.

Especially, he is credited with IBM’s decision to settle on an eight-bit byte. This allowed the systems to handle both text and numerals. Strange to think there was a time when machines were dedicated either to text handling or numerical calculation, but it was so!

He oversaw the development of systems that could be offered with an expandable range of processor and memory equipment at different price points, thus entering the development era of “platform” over “product.”

Brooks studied and found some surprising truths about complex software and projects – the most telling: That projects slow down at a greater rate when leaders add people as a project gets closer to completion.

He also saw the dangerous lure technology offers in the form of “The Silver Bullet” that promises a sudden tech- or organizational-style breakthrough.

With these and other observations, Brooks help build a philosophical underpinning for structured analysis, a school of thinking that held sway for software during an era of big projects marked especially by NASA’s Apollo program.

Ed Yourdon, Ivar Jacobsen, Tom DeMarco and others would take Brooks’ work into the 1990s. Like him, they realized it’s not just about “the code” – that the culture of the organization can play a more dominant role.

Brooks paved the path forward with emphasis on requirements gathering. But he foresaw the tarpit that beckoned with any search for the greatest schema perfection ahead of actually getting the project going.

He conveyed this without embracing the extreme that says “Fail Fast,” and he did it as always with a measure of humor. It’s right there in the title for one of “The Mythical Man-Month” chapters: “Plan to Throw One Away.”

Some of Brooks’ musings do echo another era. I don’t think we have Man Months anymore – mythical or other. Unquestionably too, team programmers have gained much more responsibility over the years, so Brooks’ emphasis on the manager wears thin [Heck, a whole era of development sprang from gritty JavaScript developers who found a way around obstacles their managers took for granted as their ‘lot in life.’]

But managers, at the end of the day, bear the greatest responsibility for the software project. Technology acumen is just a table stake. Their communications and organization skills must be stellar, as Brooks indicates when he writes:

The Tower of Babel was perhaps the first engineering fiasco, but it was not the last. Communication and its consequent, organization, are critical for success. The techniques of communication and organization demand from the manager much thought and as much experienced confidence as the software technology itself. – From The Mythical Man-Month.

Is software engineering really a profession? The question will continue to be asked, and Brooks work will likely ever be part of that discussion.

Coda: My days as a software project manager were brief – about a year. [After which my colleagues welcomed me back to editorial and told me they thought I’d been crazy ever to leave.] What I learned building web sites was that, no matter what you think your problem is, it is probably a project management problem. I owe that to Brooks. As expressed in his thoughtful and very often bemused writings, Brooks’ thinking on the topic informed my and many others’ efforts to ‘ship the darn thing’. – Jack Vaughan, 2022

Bankman-Fried and Web Site Scrubbing: Brief Comment

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Briefly – On the Ballad of Sam Bankman-Fried – Worthwhile article considers, often sympathetically, some downsides in the trend toward ‘corporate journalism’. Specifically: A fawning PR piece on the young champion of Effective Altruism. One of several issues discussed: The important role the Web plays in creating “an immutable public record for other journalists and historians.” IMHO this is a point not to be forgotten!

All this said, I’d add that journalism generally did not shine altogether too brightly here -although LA Times and others were digging into what was going on as Bankman-Fried plied Washington’s Corridors of Power in the late Summer.

Everyone likes a good story, including writers. But the writers earn their credit by exercising some skepticism, especially of good stories that may turn out to be too good to be true.

https://www.bloomberg.com/news/newsletters/2022-11-14/sequoia-ftx-profile-of-sam-bankman-fried-sbf-was-a-face-plant [Possible pay wall.]