Monthly Archives: January 2022

AI Supercomputers, An Inquiry

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When I was young, the word, ‘supercomputer’ evoked images of powerful, intelligent systems, filling the cavities of mountains with their humming electronic menace.

Science fiction encouraged this view, which is as far from the (still impressive, yet grounded) reality of supercomputing as the Earth is from some distant galaxy. The distance between marketing hype and actually existing machines is like that: vast and unbridgeable, except in dreams.

Which brings me to this Verge story, posted on 24 January, 2022:

Social media conglomerate Meta is the latest tech company to build an “AI supercomputer” — a high-speed computer designed specifically to train machine learning systems. The company says its new AI Research SuperCluster, or RSC, is already among the fastest machines of its type and, when complete in mid-2022, will be the world’s fastest.

“Meta has developed what we believe is the world’s fastest AI supercomputer,” said Meta CEO Mark Zuckerberg in a statement. “We’re calling it RSC for AI Research SuperCluster and it’ll be complete later this year.”

Verge: https://www.theverge.com/2022/1/24/22898651/meta-artificial-intelligence-ai-supercomputer-rsc-2022

The phrase, “AI supercomputer” is obviously designed to sell the idea that this supercomputer, unlike others, is optimized for AI. And to give the devil his due, the fact it’s reportedly composed of NVIDIA game processing units, which, since the mid 2000’s have found extensive use powering tasks such as building large language models, gives some amount of credibility to the claim.

Some, but not as much as it might seem. Consider this hyperventilating article:

“Mind boggling”

This is clearly the tone Meta (and others) is hoping to cultivate via the use of ‘AI supercomputer’ as a descriptor. The assumption is that if enough computational power is thrown at the task of building machine learning models, those models will, in some not sharply defined way, reach unprecedented heights of…well, one isn’t sure.

Are ever larger machine learning models a sure indicator of remarkable progress? Two papers, “On the Dangers of Stochastic Parrots: Can Language Models Be Too Big?” and “No News is Good News: A Critique of the One Billion Word Benchmark” suggest the answer is no. These papers are focused on Natural Language Processing (NLP) models and it’s suggested that Meta will be building models for its Second Life warmed over ‘Metaverse’ effort. Even so, there appears to be a point at which ever larger models fail to produce hoped for results.

Supercomputers: Our Old Drinking Buddies

Schematic of Typical Supercomputing Infrastructure from ResearchGate

The category, ‘supercomputer’, created to describe a class of tightly integrated, high performance computational platforms, has existed for over 60 years. The first supercomputers were developed for nuclear research (weapons and energy) at Lawrence Livermore Labs in the US at the height of the Cold War (maybe we should call it Cold War Classic) and have also been applied to demanding tasks such as modeling the Earth’s climate. It’s a venerable technology with clearly defined parameters such as the use of symmetric multiprocessing. In all these decades, no supercomputer has managed to exhibit intelligence or plot our demise, except in fiction.

Adding ‘AI’ to the mix doesn’t change that reality since ever larger statistical pattern matching techniques do not cognition make. Oh and Meta’s claim is that these types of supercomputing data centers will, in addition to serving as development platforms, also host the haunted cartoon castle they call the “Metaverse’.

Considering this statement from Intel we have reason to doubt this too.

On Niceness as a Tactical Failure

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Attentive readers will note that this blog is primarily focused on dissecting and highlighting the political economy and social impact of what’s called ‘Artificial Intelligence’ and allied fields (such as supposedly autonomous robots).

Till now, crypto, in all its fetidness, has escaped comment on these virtual pages. Well, ‘needs must’ as the old saying goes: the increasingly loud chorus of people – some of whom are well-intentioned techies – either singing the praises of crypto, NFTs, web3 etc. or, offering a lukewarm response to the threat this poses of, ‘something good might happen’ compels me to put fingers to keyboard.

More precisely though, this thread on Twitter provided the framework for a proper response:

In contrast to Marco’s clear declaration, which reflects my own view, there was this thread, in which Anil Dash presented the idea that, even though there are lots of ‘bad people’ involved in the space, there are also good people and these good people are trying to carve out a good space (for, in this case, artists using NFTs):

One of the most common maladies of our age is a belief – more appropriate in children than adults – that the problem with societies is the presence of ‘bad people’ who, being bad, spend their time, like villians in a Bond movie, imagining bad things to do and not as a function or emergent property of the society itself that enables these bad people. Normally, I’d insert a bit about the materialist analysis of capitalism but I’ll let that go for a later post.

There’s a wealth of evidence that the entire point of the crypto space is the realization of libertarian fantasies – the removal of constraints that protect those who’re considered weak or foolish (no need for deposit guarantees, now there are smart contracts!).

The presence of people with good intentions in this space (whether as software developers, activists or what have you) only serves to provide visual cover for the grift; indeed, this is how grifts function: earnest people are required. You, an earnest person hoping to do good things, suppress your knowledge of all the problems – the fundamental, baked into the cake problems – thinking that your niceness is a tactic for change.

This is an abdication of, as Hannah Arendt put it, your duty to think.

It’s time for us to abandon niceness for a solid and consistent application of principle, openly state who our adversaries are and vigorously resist their propaganda.

The first step is to stop fooling ourselves that our niceness is a tactic.