Category: Web/Tech

The case against the import of GPT-3

From an email from Agustin Lebron, noting that I will impose no further indentation:

“One thing that’s worth noting:

The degree of excitement about GPT-3 as a replacement for human workers, or as a path to AGI, is strongly inversely correlated with:

(a) How close the person is to the actual work. If you look at the tweets from Altman, Sutskever and Brockman, they’re pumping the brakes pretty hard on expectations.
(b) How much the person has actually built ML systems.

It’s a towering achievement to be able to train a system this big. But to me it’s clearly a dead-end on the way to AGI:

– The architecture itself is 3 years old: https://arxiv.org/abs/1706.03762. It is not an exaggeration to say that GPT-3’s architecture can be described as “take that 2017 paper and make 3 numbers (width, # layers, # heads) much bigger”. The fact that there hasn’t been any improvement in architecture in 3 years is quite telling.

– In the paper itself, the authors clearly say they’re quite near fundamental limits in being able to train an architecture like this. GPT-3 isn’t a starting point, it’s an end-point.

– If you look at more sober assessments (http://lacker.io/ai/2020/07/06/giving-gpt-3-a-turing-test.htmlhttps://minimaxir.com/2020/07/gpt3-expectations/), without the tweet selection bias, it starts to look less impressive.

– Within my fairly heterogeneous circle of ML-expert friends, there’s little disagreement about dead-end-ness.

The most interesting thing about GPT-3 is the attention and press that it’s gotten. I’m still not sure what to make of that, but it’s very notable.

Again, it’s incredibly impressive and also piles of fun, but I’m willing to longbet some decent money that we’re not replacing front-end devs with attention-layer-stacks anytime soon.”

I remain bullish, but it is always worth considering other opinions.

GPT-3, etc.

Here is an email from a reader, I do not really have an opinion of my own yet.  Please note I will not indent any further:

“I wanted to draw your attention to something. Are you familiar with “AI Dungeon,” text-based RPG “open world” game running on GPT-2 / GPT-3?  Here’s the author’s discussion on medium, or you can play the GPT-2 version for free to get a sense of it directly.

But what I really want to draw your attention to is players who are using custom prompts to open up dialogs with GPT-3 about non-game things.

This result is particularly impressive:  https://www.reddit.com/r/slatestarcodex/comments/hrx2id/a_collection_of_amazing_things_gpt3_has_done/fy7i7im/

( Following that string of posts is a little hampered by reddit’s format; here are the posts in order: part 1,  part 2,  part 3)

If the author is to be believed, they’ve had GPT-3 / “Dragon”:

1. write code
2. act as a pharmacology tutor
3. write poetry
4. translate english, french, chinese (the instruction to “balance the intent of the author with artistic liberty” is particularly interesting)

It’s hard to excerpt, I’d recommend reading the whole thing if you have time.

Here’s another user’s eloquent conversation about the experience of being an AI, using a similar mechanism (screencap images of the convo, part 1 and part 2 ), with a sample prompt if you want to converse with GPT-3 yourself via AI Dungeon.

I am increasingly convinced that Scott Alexander was right that NLP and human language might boostrap a general intelligence. A rough criteria for AGI might be something like (i) pass the Turing test, and (ii) solve general problems; the GPT-3-AI-Dungeon examples above appear to accomplish preliminary versions of both.

GPT was published in June 2018, GPT-2 in February 2019, GPT-3 in May 2020.

As best I can tell GPT -> GPT2 was ~10x increase in parameters over ~8 months, and GPT2 -> GPT3 was ~100x increase of parameters over ~14 months. Any number of naive projections puts a much more powerful release happening over the next ~1-2yrs, and I also know that GPT-3 isn’t necessarily the most powerful NLP AI (perhaps rather the most popularly known.)

When future AI textbooks are written, I could easily imagine them citing 2020 or 2021 as years when preliminary AGI first emerged,. This is very different than my own previous personal forecasts for AGI emerging in something like 20-50 years…

p.s. One of the users above notes that AI Dungeon GPT-3 (“Dragon”) is a subscription service, something like ~$6 a week. MIE.”

What should I ask Matt Yglesias?

I will be doing a Conversation with him, based in part on his new forthcoming book One Billion Americans: The Case for Thinking Bigger.  While I have not yet read it, I strongly expect it will be excellent.

And to be clear, this will be the conversation with Matt I want to have, not the one that you might think you wish to hear.

So what should I ask?

What is the future of the intellectual right?

That is the topic of my latest Bloomberg column.  I suggest it will take three major forms, namely anti-China, pro-internet as a communications medium (as an offset to left-wing media), and dislike of the Left, most of all the latter.  Note these are predictions rather than normative claims about what should happen.  Here is one excerpt:

Last and perhaps most significant, the intellectual right will dislike the left. It pretty much does already, but the antagonism will grow. Opposition to political correctness and cancel culture, at least in their left-wing versions, will become the most important defining view. As my colleague Bryan Caplan succinctly put it four years ago: “Leftists are anti-market. … Rightists are anti-leftist.”

The intensity of this dislike will mean that, within right-wing circles, free speech will prosper. As long as you take care to signal your dislike of the left, you will be allowed to hold many other heterodox views without being purged or penalized.

If you are on the Left, note that it does not suffice to dislike the Right, you have to dislike most parts of the Left as well (why is that? Can you model this?).

I also consider social conservatism, libertarianism, communitarianism, and Sam’s Club Republicanism as possible alternative directions for the intellectual Right.  The entire column repays careful study.

Megan McArdle on Patrick Collison on China

By the time someone gets to be chief executive of a successful firm, they have generally been trained out of saying anything surprising in public. So I was positively astonished Monday when I saw Patrick Collison, the CEO of payments firm Stripe, tweet that “As a US business (and tech) community I think we should be significantly clearer about our horror at, and opposition to, the atrocities being committed by the Chinese government against its own people.”

On first read, that sentiment might seem banal. Of course we should clearly oppose China’s intensifying political repression. But is easier to list American business leaders who have cravenly excused the inexcusable than to name those such as Collison, who have been brave enough to state the obvious. When it comes to China’s human rights abuses, the position of the American business community is prone…

“It must be possible,” Collison tells me, “to acknowledge the basic facts — for example, that concentration camps and forced sterilization programs are reprehensible evils. If it becomes de facto unacceptable to do so, as part of some kind of self-perpetuating silence, it really seems to me that that’s a positive feedback loop that we should hurry to break.”

There is much more at the link, definitely recommended.

Big tech and universal telecommuting

It has gone great so far, but I don’t think it is socially optimal to be doing this forever.  Here is my latest Bloomberg column on that topic, 2x the usual length, excerpt:

If Twitter, Facebook and other tech companies shift toward everyone working from home, it will mean less reliance on esprit de corps and morale to ensure performance, and more management using direct financial incentives and project- and output-based monitoring. Virtual tools can help organize teams, but they simply can’t replicate the intellectual frisson of “gathering the smart people” together, and this could damage performance and innovation.

And:

There is some evidence that when employees work at a distance, they don’t put in extra hours or extend themselves for the benefit of co-workers. That probably means a better work-life balance for many people, but perhaps also inferior performance from a lot of companies over the longer haul.

This move away from workplace morale as a motivator will help self-starter employees, but it may not be good for tech labor overall. In essence, without a local workplace ethos, it is easier to commoditize labor, view workers as interchangeable and fire people. The distinction between protected full-time employees and outsourced, freelance and contract workers weakens. A company can make the offer of, “If you hand in your project, we pay you,” to virtually any worker around the world, many of whom might accept lower wages for remote roles.

Bringing new workers on board is an especially difficult problem for this model.  In the short run, of course, that is a minor concern but over time it grows.

Keller Scholl and Robin Hanson on automation

25 simple job features explain over half the variance in which jobs are how automated.

The strongest job automation predictor is: Pace Determined By Speed Of Equipment.

Which job features predict job automation how did not change from 1999 to 2019.

Jobs that get more automated do not on average change in pay or employment.

Labor markets change more often due to changes in demand, relative to supply.

That is all from their newly published paper on the topic.

Emergent Ventures prize winners, third cohort

I am happy to announce two further winners of the Emergent Ventures prizes to fight Covid-19.

The first is to Statnews.com for their excellent and intelligent reporting on public health, including the coronavirus, with the latter articles being ungated.

This is not only a prize for past achievement, but also resources to allow them to continue into the future.  As most of you know, journalism is a highly precarious enterprise these days.

And to be clear, this is a one-time prize and it involves absolutely no editorial control or influence over what they publish.

Here is a recent NYT article on Statnews.com.  the headline reads: “The Medical News Site that Saw the Coronavirus Coming Months Ago.”

The second winner is Tina White and Covid Watch, for their work on track and trace apps, you will note that Tina and her group were earlier winners of a (smaller) Emergent Ventures fellowship.  This is an Early Response prize, for their critical and timely work to boost the quality of these apps and to make them more privacy-friendly and more palatable to civil liberties concerns.  Here is some coverage:

This App Protects Privacy While Tracing Covid-19 Infections

Here is the second cohort of prize winners, here is the first cohort.  And here is an update from Celine, from Curative Inc., from the very first cohort of winners:

Emergent Ventures is pleased to have been their very first funder, and to have consummated the entire grant process, including the wire of funds (at the time critical for materials purchase), in less than 24 hours.

The general lesson still has yet to sink in

Apple Store’s Temperature Checks May Violate EU Privacy Rules, Says German Data Protection Office

Of course they do.  And yes, I know that is a small thing, and furthermore temperature checks may not even be effective.

The general point is this: you cannot over the longer run have a society based on such inflexible rules of adjustment.  For decades it may seem possible, due to underlying stasis, but eventually the truth will be revealed.  No single anecdote will be so convincing, and it will take a long time for the failures to pile up.  And in the meantime this will breed disrespect for the more valuable laws.

My Conversation with Adam Tooze

Tinges of Covid-19, doses on financial crises, but mostly about economic history.  Here is the audio and transcript.  Here is the summary:

Adam joined Tyler to discuss the historically unusual decision to have a high-cost lockdown during a pandemic, why he believes in a swoosh-shaped recovery, portents of financial crises in China and the West, which emerging economies are currently most at risk, what Keynes got wrong about the Treaty of Versailles, why the Weimar Republic failed, whether Hitler was a Keynesian, the political and economic prospects of various EU members, his trick to writing a lot, how Twitter encourages him to read more, what he taught executives at BP, his advice for visiting Germany, and more.

Here is one excerpt:

And:

Tooze’s discussion of his own career and interests, toward the end, is hard to excerpt but for me the highlight of the conversation.  He also provided the best defense of Twitter I have heard.

Definitely recommended.

A critique of contact-tracing apps

Here are some relevant criticisms from Soltani, Calo, and Bergstrom:

Studies suggest that people have on average about a dozen close contacts a day—incidents involving direct touch or a one-on-one conversation—yet even in the absence of social distancing measures the average infected person transmits to only 2 or 3 other people throughout the entire course of the disease. Fleeting interactions, such as crossing paths in the grocery store, will be substantially more common and substantially less likely to cause transmission. If the apps flag these lower-risk encounters as well, they will cast a wide net when reporting exposure. If they do not, they will miss a substantive fraction of transmission events. Because most exposures flagged by the apps will not lead to infection, many users will be instructed to self-quarantine even when they have not been infected. A person may put up with this once or twice, but after a few false alarms and the ensuing inconvenience of protracted self-isolation, we expect many will start to disregard the warnings.

And:

At least as problematic is the issue of false negatives—instances where these apps will fail to flag individuals as potentially at risk even when they’ve encountered someone with the virus. Smartphone penetration in the United States remains at about 81 percent—meaning that even if we had 100 percent installation of these apps (which is extremely unlikely without mandatory policies in place), we would still only see a fraction of the total exposure events (65 percent according to Metcalf’s Law). Furthermore, people don’t always have their phones on them.

And:

There is also a very real danger that these voluntary surveillance technologies will effectively become compulsory for any public and social engagement. Employers, retailers, or even policymakers can require that consumers display the results of their app before they are permitted to enter a grocery store, return back to work, or use public services—is as slowly becoming the norm in China, Hong Kong, and even being explored for visitors to Hawaii.

 

Taken with the false positive and “griefing” (intentionally crying wolf) issues outlined above, there is a real risk that these mobile-based apps can turn unaffected individuals into social pariahs, restricted from accessing public and private spaces or participating in social and economic activities. The likelihood that this will have a disparate impact on those already hardest hit by the pandemic is also high. Individuals living in densely populated neighborhoods and apartment buildings—characteristics that are also correlated to non-white and lower income communities—are likelier to experience incidences of false positives due their close proximity to one another.

In another study:

Nearly 3 in 5 Americans say they are either unable or unwilling to use the infection-alert system under development by Google and Apple, suggesting that it will be difficult to persuade enough people to use the app to make it effective against the coronavirus pandemic, a Washington PostUniversity of Maryland poll finds.

And here are skeptical remarks from Bruce Schneier.

I also have worried about how testing and liability law would interact.  If the positive cases test as positive, it may be harder for businesses and schools to reopen, because they did not “do enough” to keep the positive cases out, or perhaps the businesses and the schools are the ones doing the testing in the first place.  Whereas under a lower-testing “creative ambiguity” equilibrium, perhaps it is easier to think in terms of statistical rather than known lives lost, and to proceed with some generally beneficial activities, even though of course some positive cases will be walking through the doors.

I wonder if there also is a negative economic effect, over the longer haul, simply by making fear of the virus more focal in people’s minds.  The plus of course is simply that contact tracing does in fact slow down the spread of the virus and allows resources to be allocated to individuals and areas of greatest need.

Washington Post covers Fast Grants

Here is the opening:

Economist Tyler Cowen first sounded the alarm that America is unprepared for a pandemic in 2005, when he wrote a paper outlining ways the country should respond and, for a few years, ran a blog focused on the possibility of an avian flu outbreak.

Fifteen years later, as a novel coronavirus brings Cowen’s fears into reality, the George Mason University professor is trying to fix what he and others view as a structural problem impeding the scientific response to the crisis: the months-long application and review process scientists must endure to get their research funded.

Here is the full story by Will Hobson.  Recommended.