Category: Web/Tech

Marc Andreessen on AI safety and AI for the world

So far I have explained why four of the five most often proposed risks of AI are not actually real – AI will not come to life and kill us, AI will not ruin our society, AI will not cause mass unemployment, and AI will not cause an ruinous increase in inequality. But now let’s address the fifth, the one I actually agree with: AI will make it easier for bad people to do bad things.

In some sense this is a tautology. Technology is a tool. Tools, starting with fire and rocks, can be used to do good things – cook food and build houses – and bad things – burn people and bludgeon people. Any technology can be used for good or bad. Fair enough. And AI will make it easier for criminals, terrorists, and hostile governments to do bad things, no question.

This causes some people to propose, well, in that case, let’s not take the risk, let’s ban AI now before this can happen. Unfortunately, AI is not some esoteric physical material that is hard to come by, like plutonium. It’s the opposite, it’s the easiest material in the world to come by – math and code.

The AI cat is obviously already out of the bag.

Here is the full essay, self-recommending…

Apple Vision Pro is receiving strong reviews

But none of them had the advantages that Apple brings to the table with Apple Vision Pro. Namely, 5,000 patents filed over the past few years and an enormous base of talent and capital to work with. Every bit of this thing shows Apple-level ambition. I don’t know whether it will be the “next computing mode,” but you can see the conviction behind each of the choices made here. No corners cut. Full-tilt engineering on display.

The hardware is good — very good — with 24 million pixels across the two panels, orders of magnitude more than any headsets most consumers have come into contact with. The optics are better, the headband is comfortable and quickly adjustable and there is a top strap for weight relief. Apple says it is still working on which light seal (the cloth shroud) options to ship with it when it releases officially but the default one was comfortable for me. They aim to ship them with varying sizes and shapes to fit different faces. The power connector has a great little design, as well, that interconnects using internal pin-type power linkages with an external twist lock…

If you have experience with VR at all then you know that the two big barriers most people hit are either latency-driven nausea or the isolation that long sessions wearing something over your eyes can deliver.

Apple has mitigated both of those head on. The R1 chip that sits alongside the M2 chip has a system-wide polling rate of 12ms, and I noticed no judder or framedrops. There was a slight motion blur effect used in the passthrough mode but it wasn’t distracting. The windows themselves rendered crisply and moved around snappily.

Here is more from TechCrunch.  The highly reliable Ben Thompson is extremely enthusiastic as well.  I will definitely buy it.

Evidence from Italy’s ChatGPT Ban

We analyse the effects of the ban of ChatGPT, a generative pre-trained transformer chatbot, on individual productivity. We first compile data on the hourly coding output of over 8,000 professional GitHub users in Italy and other European countries to analyse the impact of the ban on individual productivity. Combining the high-frequency data with the sudden announcement of the ban in a difference-in-differences framework, we find that the output of Italian developers decreased by around 50% in the first two business days after the ban and recovered after that. Applying a synthetic control approach to daily Google search and Tor usage data shows that the ban led to a significant increase in the use of censorship bypassing tools. Our findings show that users swiftly implement strategies to bypass Internet restrictions but this adaptation activity creates short-term disruptions and hampers productivity.

That is from a recent paper by David Kreitmeir and Paul A. Raschky.  Via Pradyumna Shyama Prasad.

Paul Krugman on AI

Like previous leaps in technology, this will make the economy more productive but will also probably hurt some workers whose skills have been devalued. Although the term “Luddite” is often used to describe someone who is simply prejudiced against new technology, the original Luddites were skilled artisans who suffered real economic harm from the introduction of power looms and knitting frames.

But this time around, how large will these effects be? And how quickly will they come about? On the first question, the answer is that nobody really knows. Predictions about the economic impact of technology are notoriously unreliable. On the second, history suggests that large economic effects from A.I. will take longer to materialize than many people currently seem to expect.

…Large language models in their current form shouldn’t affect economic projections for next year and probably shouldn’t have a large effect on economic projections for the next decade. But the longer-run prospects for economic growth do look better now than they did before computers began doing such good imitations of people.

Here is the full NYT column, not a word on the Doomsters you will note.  Could it be that like most economists, Krugman has spent a lifetime studying how decentralized systems adjust?  Another factor (and this also is purely my speculation) may be that Krugman repeatedly has announced his fondness for “toy models” as a method for establishing economic hypotheses and trying to grasp their plausibility.  As I’ve mentioned in the past, the AGI doomsters don’t seem to do that at all, and despite repeated inquiries I haven’t heard of anything in the works.  If you want to convince Krugman, not to mention Garett Jones, at least start by giving him a toy model!

Where the AI extinction warning goes wrong

There is so much to say about this one, in my view it has been counterproductive for all those worried about AI safety.  Here is one excerpt from my latest Bloomberg column:

Sometimes publicity stunts backfire. A case in point may be the one-sentence warning issued this week by the Center for AI Safety: “Mitigating  the risk of extinction from AI should be a global priority alongside other societal-scale risks such as pandemics and nuclear war.”

…The first problem is the word “extinction.” Whether or not you think the current trajectory of AI systems poses an extinction risk — and I do not — the more you use that term, the more likely the matter will fall under the purview of the national security establishment. And its priority is to defeat foreign adversaries. The bureaucrats who staff the more mundane regulatory agencies will be shoved aside.

US national security experts are properly skeptical about the idea of an international agreement to limit AI systems, as they doubt anyone would be monitoring and sanctioning China, Russia or other states (even the UAE has a potentially powerful system on the way). So the more people say that AI systems can be super-powerful, the more national-security advisers will insist that US technology must always be superior. I happen to agree about the need for US dominance — but realize that this is an argument for accelerating AI research, not slowing it down.

A second problem with the statement is that many of the signers are important players in AI developments. So a common-sense objection might go like this: If you’re so concerned, why don’t you just stop working on AI? There is a perfectly legitimate response — you want to stay involved because you fear that if you leave, someone less responsible will be put in charge — but I am under no illusions that this argument would carry the day. As they say in politics, if you are explaining, you are losing.

The geographic distribution of the signatories will also create problems. Many of the best-known signers are on the West Coast, especially California and Seattle. There is a cluster from Toronto and a few from the UK, but the US Midwest and South are hardly represented. If I were a chief of staff to a member of Congress or political lobbyist, I would be wondering: Where are the community bankers? Where are the owners of auto dealerships? Why are so few states and House districts represented on the list?

I do not myself see the AI safety movement as a left-wing political project. But if all you knew about it was this document, you might conclude that it is. In short, the petition may be doing more to signal the weakness and narrowness of the movement than its strength.

Then there is the brevity of the statement itself. Perhaps this is a bold move, and it will help stimulate debate and generate ideas. But an alternative view is that the group could not agree on anything more. There is no accompanying white paper or set of policy recommendations. I praise the signers’ humility, but not their political instincts.

Again, consider the public as well as the political perception. If some well-known and very smart players in a given area think the world might end but make no recommendations about what to do about it, might you decide just to ignore them altogether? (“Get back to me when you’ve figured it out!”) What if a group of scientists announced that a large asteroid was headed toward Earth. I suspect they would have some very specific recommendations, on such issues as how to deflect the asteroid and prepare defenses.

Do read the whole thing.  You will note that my arguments do not require any particular view of AGI risk, one way or the other.  I view this statement as a mistake from all points of view, except perhaps for the accelerationists.

Why I am not entirely bullish on brain-computer interface

I agree that miracles may well be possible for disabled individuals, but I am less certain about their more general applicability.  Here is one excerpt from my latest Bloomberg column:

Another vision for this technology is that the owners of computers will want to “rent out” the powers of human brains, much the way companies rent out space today in the cloud. Software programs are not good at some skills, such as identifying unacceptable speech or images. In this scenario, the connected brains come largely from low-wage laborers, just as both social media companies and OpenAI have used low-wage labor in Kenya to grade the quality of output or to help make content decisions.

Those investments may be good for raising the wages of those people. Many observers may object, however, that a new and more insidious class distinction will have been created — between those who have to hook up to machines to make a living, and those who do not.

Might there be scenarios where higher-wage workers wish to be hooked up to the machine? Wouldn’t it be helpful for a spy or a corporate negotiator to receive computer intelligence in real time while making decisions? Would professional sports allow such brain-computer interfaces? They might be useful in telling a baseball player when to swing and when not to.

The more I ponder these options, the more skeptical I become about large-scale uses of brain-computer interface for the non-disabled. Artificial intelligence has been progressing at an amazing pace, and it doesn’t require any intrusion into our bodies, much less our brains. There are always earplugs and some future version of Google Glass.

The main advantage of the direct brain-computer interface seems to be speed. But extreme speed is important in only a limited class of circumstances, many of them competitions and zero-sum endeavors, such as sports and games.

Nonetheless I am glad to the FDA is allowing Neuralink’s human trials to proceed — I would gladly be proven wrong.

The international competition heats up

Chinese startup MiniMax, working on AI solutions similar to that of Microsoft-backed OpenAI’s ChatGPT, is close to completing a fundraising of more than $250 million that will value it at about $1.2 billion, people familiar with the matter said.

The deal comes amid a global AI buzz kicked off by ChatGPT that has spread to China, shoring up stocks in artificial intelligence firms and prompting a flurry of domestic companies, such as Alibaba (9988.HK), Huawei (HWT.UL), and Baidu (9888.HK), to announce rival products.

Here is the link.  And here is a Chinese professor from Fudan, critical of all the money being poured into LLM research in China, comparing it to Mao’s Great Leap Forward.

You have to be very critical of all sources from China, no matter what they say.  Still, in terms of expected value I know what is the correct bet here, namely that China is a current and very active competitor in this arena, even if they are behind America so far.

Then there is the open source model Falcon, which is receiving very good reviews from multiple sources, such as this:

If you don’t already know, Falcon is from…the UAE.  Get the picture?

My excellent Conversation with Seth Godin

Here is the audio, video, and transcript from a very good session.  Here is part of the episode summary:

Seth joined Tyler to discuss why direct marketing works at all, the marketing success of Trader Joe’s vs Whole Foods, why you can’t reverse engineer Taylor Swift’s success, how Seth would fix baseball, the brilliant marketing in ChatGPT’s design, the most underrated American visual artist, the problem with online education, approaching public talks as a team process, what makes him a good cook, his updated advice for aspiring young authors, how growing up in Buffalo shaped him, what he’ll work on next, and more.

Here is one excerpt:

COWEN: If you were called in as a consultant to professional baseball, what would you tell them to do to keep the game alive?

GODIN: [laughs] I am so glad I never was a consultant.

What is baseball? In most of the world, no one wants to watch one minute of baseball. Why do we want to watch baseball? Why do the songs and the Cracker Jack and the sounds matter to some people and not to others? The answer is that professional sports in any country that are beloved, are beloved because they remind us of our parents. They remind us of a different time in our lives. They are comfortable but also challenging. They let us exchange status roles in a safe way without extraordinary division.

Baseball was that for a very long time, but then things changed. One of the things that changed is that football was built for television and baseball is not. By leaning into television, which completely terraformed American society for 40 years, football advanced in a lot of ways.

Baseball is in a jam because, on one hand, like Coke and New Coke, you need to remind people of the old days. On the other hand, people have too many choices now.

And another:

COWEN: What is the detail you have become most increasingly pessimistic about?

GODIN: I think that our ability to rationalize our lazy, convenient, selfish, immoral, bad behavior is unbounded, and people will find a reason to justify the thing that they used to do because that’s how we evolved. One would hope that in the face of a real challenge or actual useful data, people would say, “Oh, I was wrong. I just changed my mind.” It’s really hard to do that.

There was a piece in The Times just the other day about the bibs that long-distance runners wear at races. There is no reason left for them to wear bibs. It’s not a big issue. Everyone should say, “Oh, yeah, great, done.” But the bib defenders coming out of the woodwork, explaining, each in their own way, why we need bibs for people who are running in races — that’s just a microcosm of the human problem, which is, culture sticks around because it’s good at sticking around. But sometimes we need to change the culture, and we should wake up and say, “This is a good day to change the culture.”

COWEN: So, we’re all bib defenders in our own special ways.

GODIN: Correct! Well said. Bib Defenders. That’s the name of the next book. Love that.

COWEN: What is, for you, the bib?

GODIN: I think that I have probably held onto this 62-year-old’s perception of content and books and thoughtful output longer than the culture wants to embrace, the same way lots of artists have held onto the album as opposed to the single. But my goal isn’t to be more popular, and so I’m really comfortable with the repercussions of what I’ve held onto.

Recommended, interesting throughout.  And here is Seth’s new book The Song of Significance: A New Manifesto for Teams.

It was just a simulation run…designed to create that problem

Please don’t be taken in by the b.s.!  The rapid and uncritical spread of this story is a good sign of the “motivated belief” operating in this arena.  And if you don’t already know the context here, please don’t even bother to try to find out, you are better off not knowing.  There may be more to this story yet — context is that which is scarce — but please don’t jump to any conclusions until the story is actually out and confirmed.

Funny how people accuse “the AI” of misinformation, right?

Addendum: Here is a further update, apparently confirming that the original account was in error.

The art of prompting is just at its beginning

And here are some results for Minecraft.  I would like to see confirmations, but these are credible sources and this is all quite important if true.

Playing repeated games with Large Language Models

They are smart, but not ideal cooperators it seems, at least not without the proper prompts:

Large Language Models (LLMs) are transforming society and permeating into diverse applications. As a result, LLMs will frequently interact with us and other agents. It is, therefore, of great societal value to understand how LLMs behave in interactive social settings. Here, we propose to use behavioral game theory to study LLM’s cooperation and coordination behavior. To do so, we let different LLMs (GPT-3, GPT-3.5, and GPT-4) play finitely repeated games with each other and with other, human-like strategies. Our results show that LLMs generally perform well in such tasks and also uncover persistent behavioral signatures. In a large set of two players-two strategies games, we find that LLMs are particularly good at games where valuing their own self-interest pays off, like the iterated Prisoner’s Dilemma family. However, they behave sub-optimally in games that require coordination. We, therefore, further focus on two games from these distinct families. In the canonical iterated Prisoner’s Dilemma, we find that GPT-4 acts particularly unforgivingly, always defecting after another agent has defected only once. In the Battle of the Sexes, we find that GPT-4 cannot match the behavior of the simple convention to alternate between options. We verify that these behavioral signatures are stable across robustness checks. Finally, we show how GPT-4’s behavior can be modified by providing further information about the other player as well as by asking it to predict the other player’s actions before making a choice. These results enrich our understanding of LLM’s social behavior and pave the way for a behavioral game theory for machines.

Here is the full paper by Elif Akata, et.al.

Two Podcasts

Two podcasts I have enjoyed recently, First, The Social Radars, headed by Jessica Livingston and Carolynn Levy, co-founder and managing director of Y Combinator respectively. Jessica and Carolynn bring a lot of experience and trust with them so the entrepreneurs they interview open up about the realities of startups. Here is a great interview with David Lieb, creator of Google Photos and before that the highly successful failure, Bump.

I’ve also enjoyed the physician brothers Daniel and Mitch Belkin at The External Medicine Podcast. Here’s a superb primer on drug development from the great Derek Lowe.

ChatGPT as marketing triumph

That is the topic of my latest Bloomberg column, here is one excerpt:

Consider the name itself, ChatGPT. Many successful tech products have happy, shiny, memorable names: Instagram, Roblox, TikTok. Someone comes up with the name, perhaps in a brainstorming session, and then it is taken to the broader world. With luck, it will prove sticky and continue to invoke a warm glow.

ChatGPT, as a name, does not have a comparably simple history. Originally the service was GPT-2, then GPT-3. GPT-3.5 was then released, and ChatGPT was announced in November 2022. ChatGPT-3.5 was cumbersome, and by that point it was running the risk of becoming obsolete numerically. So ChatGPT became the popular moniker. When GPT-4 was released in March, there was the chance to switch to just GPT-4 and treat ChatGPT as a kind of interim brand, connected with the 3.5 edition, but no — ChatGPT it is.

I still prefer to call it GPT-4, to make it clear which version of the service I am using. GPT-3.5 remains available for free and is widely used, and so my inner persnickety nag feels the two should not be confused. But they are confused, and almost everyone (present company excluded) just says ChatGPT. Again, this is not textbook marketing, but users seem fine with it.

At this point, you might be wondering what that GPT stands for. It is “Generative Pre-Trained Transformer.” How many of its users could tell you that? How many of its users could explain what it means? I can imagine a marketing team sitting around a conference table insisting that GPT is too opaque and just won’t do.

But at OpenAI, software engineers and neural net experts are the dominant influences. So Americans get a name that has not been heavily market-tested and does not necessarily fit well into an advertising slogan. Maybe they like it, especially if they are sick of more and more of the economy being run by marketers.

There is more at the link.  The part of GPT-4 that comes across as “focus group tested” — the neutering of Sydney and the like — is also the part that is not entirely popular, even if it is politically wise.

Ho hum

And trained on The New Testament, I might add, a text which exists in a great number of languages.