Category Archives: Web Article Review

a new “grand bargain” for the Middle East

When I first heard about a conceptual “grand bargain” under the Obama administration, the general idea was normalization of relations between the U.S., Iran, and Israel in exchange for Iran giving up its nuclear weapons program (maybe in exchange for a well monitored nuclear power program) and Israel allowing the creation of a Palestinian state. This obviously didn’t happen.

Before these ideas, there were smaller actual bargains including peace between Israel and most of its neighbors under Carter, and movement toward a Palestinian state under Clinton.

Before the October 2023 Hamas attack on Israel, the latest idea was a formal normalization of (already de facto?) diplomatic relations between Israel and Saudi Arabia, possibly in exchange for nuclear power for Saudi Arabia. Iran was left out of this, and in fact it seemed to be the solidification of an anti-Iran block. The Palestinians were also left out of this, as far as I know. So now it seems to me that Biden is proposing a return to this deal that was already essentially made, and trying to add some progress toward a Palestinian state in the mix. It doesn’t seem that likely to me, at least until a new generation of leadership takes over in Israel, and unless/until Biden gets re-elected or a new generation of leadership takes over in the U.S.

It seems to me that the “grand” bargain is getting smaller and more cynical all the time. Still, one thing we can count on is the passage of time, and new leadership eventually taking over in all countries involved. One can hope for a brighter picture 5-10 years down the line. Hoping for a brighter picture by November 2024 seems a bit wishful to me.

what’s new with super-sonic flight

NASA and Lockheed Martin claim to have a prototype supersonic jet whose sonic boom sounds “like a car door slamming heard from inside”. This could open the door to commercial supersonic flight over populated areas. Well, we don’t even have commercial super-sonic flight over the oceans at the moment, which would be helpful to long-haul travelers. The article doesn’t say when this might happen, but it doesn’t sounds soon. The article does mention that there is at least one other company working on a supersonic passenger jet which “it hopes” could be “in the air” (for testing presumably?) “later this year”.

my first take on the 2024 U.S. presidential election

With the Iowa Republican caucus in the books as I write this (Tuesday, January 16, 2024), stuff is starting to get real.

It seems like barring unforeseen major developments, we are headed for another Biden vs. Trump election. In the absence of any other information, I would just say look at what happened last time. Biden won pretty handily, and really nothing major has changed in any rational sense, except that there hasn’t been a recession, war, or pandemic (that has affected the vast majority of the U.S. public significantly). What there has been is inflation, and not just inflation but inflation following a long period of no inflation in many voters’ living memories. And that seems to me to be the one thing making the difference for Biden. There is just nothing else that makes sense to me.

Anyway, tiresome as it gets, we know it comes down to the “battleground states”. There were three states in 2020 with a voting margin of less than 1% (Arizona, Georgia, Wisconsin), two within 1-2% (North Carolina and Pennsylvania), and two within 2-3% (Michigan and Nevada). That’s it – no, Florida and Ohio were not close. 7 states that matter out of 50 and some territories. I got these numbers from CNN.

Sure, it’s early to start looking at state-level general election polls. Sure, there are all sorts of problems with polls. Sure, other candidates could theoretically be nominated. Sure, third party candidates could affect the race. But the numbers below are at least averages of several polls over a period of time which might smooth out at least some biases, and they paint a consistent and deeply worrying picture for Biden at this stage.

STATE2020 RESULTMost Recent Real Clear Politics Poll Average (as of 1/16/24)
ArizonaBiden +0.4%Not Available
GeorgiaBiden +0.3%Trump +6.6%
WisconsinBiden +0.6%Not Available
North CarolinaTrump +1.3%Not Available
PennsylvaniaBiden +1.2%Trump +0.3%
MichiganBiden +2.8%Trump +5.3%
NevadaBiden +2.4%Trump +5.4%

I’ll try to update this from time to time. If I were much smarter, I would try to automate it. Well, I would like to think I am smart enough to figure that out, but it is just not close to the top of my project list.

AI “coscientist”

The idea of computers and robots greatly accelerating the rate of progress in chemical and drug research is not science fiction.

Autonomous chemical research with large language models

Transformer-based large language models are making significant strides in various fields, such as natural language processing1,2,3,4,5, biology6,7, chemistry8,9,10 and computer programming11,12. Here, we show the development and capabilities of Coscientist, an artificial intelligence system driven by GPT-4 that autonomously designs, plans and performs complex experiments by incorporating large language models empowered by tools such as internet and documentation search, code execution and experimental automation. Coscientist showcases its potential for accelerating research across six diverse tasks, including the successful reaction optimization of palladium-catalysed cross-couplings, while exhibiting advanced capabilities for (semi-)autonomous experimental design and execution. Our findings demonstrate the versatility, efficacy and explainability of artificial intelligence systems like Coscientist in advancing research.

Nature

It seems to me that the speed limit here is not anything imposed by the computers and robots, but your ability to measure progress and give the computers and robots feedback. With chemicals, you could tell the robots to find a combination of compounds that will do XYZ, where XYZ is something you can measure like an amount of energy or a color. With drugs, your issue could be how to test the results to see if they are working. If you test them on a computer model, your ability to measure depends on how good the computer model is. Let’s say you wanted to breed a super-intelligent mouse. There should be ways to measure the intelligence of a mouse. So you could take 100 mice test them all, find the two smartest and create a new batch of 100 embryos from the smartest male and female (or maybe at some point gender is no longer a limitation?). Now you have to wait for those 100 embryos to grow up to the point you can repeat the process. The limiting step here would be how long it takes the mice to develop to the point they can be tested. If they could somehow be tested at the embyro stage, maybe you could create a thousand generations of mouse directed mouse evolution in a matter of hours or days? Well, then, you can let the super-intelligent mice design the next round of robots.

“if there’s one thing we don’t want here in South America it’s war”

This seems like a sensible quote from President Lula of Brazil. But countries that threaten to or actually nationalize lucrative industries controlled by U.S. based companies (Cuba, Iran, and Iraq come to mind) have a tendency to get invaded by the U.S. I know next to nothing about the politics of South America, but I do know the U.S. establishment has been itching for a fight with Venezuela’s Nicolas Maduro for quite a while, so this seems like it would be a huge self-inflicted wound for a country already going through a lot of turmoil. And the world clearly does not need another war on another continent right now. Hopefully cooler heads will prevail.

Q (the AI)

“Q star” is very badly named, in my view, given the “Q anon” craze it has absolutely nothing to do with. Then again, the idea of an AI building an online cult with human followers does not seem all that far fetched.

Anyway, Gizmodo has an interesting article. Gizmodo does not restrict itself to traditional journalistic practices, such as articles free of profanity.

Some have speculated that the program might (because of its name) have something to do with Q-learning, a form of machine learning. So, yeah, what is Q-learning, and how might it apply to OpenAI’s secretive program? …

Finally, there’s reinforced learning, or RL, which is a category of ML that incentivizes an AI program to achieve a goal within a specific environment. Q-learning is a subcategory of reinforced learning. In RL, researchers treat AI agents sort of like a dog that they’re trying to train. Programs are “rewarded” if they take certain actions to affect certain outcomes and are penalized if they take others. In this way, the program is effectively “trained” to seek the most optimized outcome in a given situation. In Q-learning, the agent apparently works through trial and error to find the best way to go about achieving a goal it’s been programmed to pursue.

What does this all have to do with OpenAI’s supposed “math” breakthrough? One could speculate that the program that managed (allegedly) to do simple math operations may have arrived at that ability via some form of Q-related RL. All of this said, many experts are somewhat skeptical as to whether AI programs can actually do math problems yet. Others seem to think that, even if an AI could accomplish such goals, it wouldn’t necessarily translate to broader AGI breakthroughs.

Gizmodo

My sense is that AI breakthroughs are certainly happening. At the same time, I suspect the commercial hype has gotten ahead of the technology, just like it did for every previous technology from self-driving cars to virtual reality to augmented reality. Every one of these technologies reached a fever pitch where companies were racing to roll out products to consumers ahead of competitors. Because they rush, the consumer applications don’t quite live up to the hype, the hype bubble bursts, and then the technology seems to disappear for a few years. Of course, it doesn’t disappear at all, but rather disappears from headlines and advertisements for a while. Behind the scenes, it continues to progress and then slowly seeps back into our lives. As the real commercial applications arrive and take over our daily lives, we tend to shrug.

So I would keep an eye out on the street for the technologies whose hype bubbles burst a handful of years ago, and I would expect the current AI hype to follow a similar trend. Look for the true AI takeover in the late 2020s (if I remember correctly, close to when when Ray Kurzweil predicted 30-odd years ago???)

The Sierra Madre

This is a weird story. In the South China Sea, there is a Philippines ship that ran aground on a shoal in 1999. Sailors from that country have occupied the ship ever since, and are regularly resupplied while being bombarded by the Chinese navy using things other than guns, like water cannons and lasers.

That month, the Sierra Madre ran aground at Second Thomas Shoal, a small reef in what was then disputed territory, about 120 miles off the coast of Palawan island. A second ship did the same at another shoal later that year. Beijing suspected that Manila was using the beached ships to create outposts.

Philippine officials initially played coy, saying that they meant to repair the Sierra Madre but were having trouble finding the materials, while the other ship was eventually towed away. Yet, more than two decades later, the Sierra Madre remains grounded, a rusted dieselpunk monolith interrupting an otherwise pristine swath of tropical waters. A small group of sailors crews it; they pick their way through its slightly listing steel skeleton as they monitor the area for incursions. Their rotations generally last two months but can stretch up to five. Carlos referred to these tours as a “test of sanity…”

Beijing blatantly ignores this ruling. When the Philippines delivers supplies for the sailors on board the Sierra Madre via small boats escorted by coast-guard ships, Chinese ships attempt to block them. In early August, the Chinese coast guard used water cannons to prevent Philippine boats from reaching the outpost. A second attempt later that month was successful, as was one in September, when a U.S. reconnaissance aircraft flew overhead.

Atlantic

The U.S., of course, feels the need to get involved in all this. Not by being a voice of reason, but by ramping up tensions and threats of violence.

“useful principles”

Here is an interesting blog post called “30 useful principles“. I would agree that the majority of them are useful. Anyway, here are a few ideas and phrases that caught my interest. I’ll try to be clear when I am quoting versus paraphrasing or adding my own interpretation.

  • “When a measure becomes a goal, it ceases to be a good measure.” Makes sense to me – measuring is necessary, but I have found that people who are actually doing things on the ground need an understanding of the fundamental goals, or else things will tend to drift over time and no longer be aimed at the fundamental goals.
  • “A man with a watch knows what time it is. A man with 2 watches is never sure.” A good way to talk about the communication of uncertainty. Measuring and understanding uncertainty is critical in science and decision making, but how we communicate it requires a lot of careful thought to avoid unintended consequences. Decisions are often about playing the odds, and sometimes giving decision makers too much information on uncertainty leads to no decisions or delayed decisions, which are themselves a type of decision, and not the type that is likely to produce desirable results. Am I saying we should oversimplify and project an inflated sense of certainty when talking to the public and decision makers? and is this a form of manipulation? Well, sort of and sometimes yes to both these questions.
  • “Reading is the basis of thought.” Yes, this is certainly true for me, and it is even true that the writing process is an important part of thoroughly thinking something through. This is why we may be able to outsource the production of words to AI, but this will not be a substitute for humans thinking. And if we don’t exercise our thinking muscles, we will lose them over time and we will forget how to train the next generation to develop them. So if we are going to outsource thinking and problem solving to computers, let’s hope they will be better at it than we ever were. A better model would be computer-aided decision making, where the computers are giving humans accurate and timely information about the likely consequences of our decisions, but in the end we are still applying our judgment and values in making those decisions.
  • “punishing speech—whether by taking offence or by threatening censorship—is ultimately a request to be deceived.” It’s a good idea to create incentives for people to tell the truth and provide accurate information, even if it is information people in leadership positions don’t want to hear. Leaders get very out of touch if they don’t do this.
  • “Cynicism is not a sign of intelligence but a substitute for it, a way to shield oneself from betrayal & disappointment without having to do or think.” I don’t know that cynical or “realistic” people lack raw intelligence on average, but they certainly lack imagination and creativity. The more people have trouble imagining that things can change, the more it becomes a self-fulfilling prophecy that things will not change.
  • “One death is a tragedy, a million is a statistic.” I’m as horrified by pictures of dying babies in a hospital in a war zone as anyone else, but it also raises my propaganda flag. Who is trying to manipulate me with these images and why? What else is going on at the same time that I might also want to pay attention to?

Taiwan’s 2024 election

There is an important election taking place in 2024 that affects people far beyond the borders of the country where it takes place. I’m talking, of course, about Taiwan. Well, the three (?) sides don’t even agree on what the borders of the country are, so we could start there.

Far be it from me to express any opinions about the politics of Taiwan. But it is worth watching because it affects relations between Taiwan and (Peoples Republic of) China, and this potentially affects everyone. The idea of a full-frontal invasion of Taiwan has always seemed far-fetched to me. It seems more likely to me that there would be some form of subversion, election interference (like we saw BOTH the U.S. and Russia do in Ukraine), confusion about who is in charge, shadowy paramilitary forces (Russia in Ukraine), etc.

I’ve always thought Taiwan must have the best counter-intelligence in the world. It must be a bit like Cold War Germany, where the two antagonist sides basically look identical and speak the same language. Only there is a lot of economic interaction, free information flow, at least some travel, and the two sides are not as far apart culturally as, say, Cold Water era Germany and today’s North and South Korea. (In the latter case, the two sides might look and speak similarly, the comparison ends there – certainly no free flow of information, travel, and very little economic interaction, so it is hard to imagine how North Korea could place spies effectively in South Korea). So how does Taiwan manage to secure its elections and keep its government from being a nest of spies? But somehow, they seem to manage this on an ongoing basis.

“Our Megathreatened Age”

The “Megathreats” according to Nouriel Roubini are that “economic, monetary, and financial threats are rising and interacting in dangerous ways with various other social, political, geopolitical, environmental, health, and technological developments.”

This is a long article with a lot in it, but one thing I always like to puzzle over is how real-world phenomena translate to money and financial markets. One advantage of understanding this would be to find numbers provided by financial markets that translate back to the real world, and in an ideal case maybe these could even serve as early warnings when things are really about to go seriously wrong. Anyway, this article doesn’t have all the answers, only clues, but here are a few:

  • energy and food costs – this is fairly obvious, although short-term noise may obscure any useful predictive ability
  • labor costs – tells us something about demographics and population structure
  • public debt servicing costs – maybe a more useful thing to think about than just the size of the debt or deficit, because it tells us something about the size of the debt, interest rates, and inflation together, and it can be compared to tax revenues and/or a society’s overall productive capacity. This in turn tells us something about limits to (economic) growth and the ability of a society to weather potential shocks.
  • military spending on conventional and unconventional weapons – not exactly public information, but there are some sources out there, and this tells us something both about overall global risk and about government’s priorities and ability to solve other problems
  • climate change adaptation and mitigation spending, and gap between actual spending and what is needed to meet the agreed targets – not sure exactly how to measure this, but people must be trying. We could compare this spending with measured results to get some sense of efficiency, and again it tells us something about government priorities and ability to solve long-term problems. Roubini compares climate spending to reconstruction after a war, which I find interesting: “Though a surge of investment in reconstruction can produce an economic expansion, the country is still poorer for having lost a large share of its wealth. The same is true of climate investments. A significant share of the existing capital stock will have to be replaced, either because it has become obsolete or because it has been destroyed by climate-driven events.”
  • “unfunded implicit liabilities” to deal with pandemic preparedness. Again, seems hard to measure but people are undoubtedly trying.
  • “To prevent populist regimes from coming to power and pursuing reckless, unsustainable economic policies, liberal democracies will need to spend heavily to reinforce their social safety nets – as many are already doing.” Well, not the U.S. so much. At least we are not doubling down on this, and the political cost of advocating it seems high while opposing it seems to appeal to many voters.
  • Retirement pension and health care spending, actual and estimated gap with what is needed.
  • long-term government bond rates, and “risk premia on public bonds” – tells us something about perceived risk that a government can keep up with its obligations long-term
  • mix of foreign currency reserves held by governments – somewhat obscure, but again a measure of risk that governments can meet their obligations and solve their societal problems
  • We can always measure fun things like poverty, inequality, and migration, and of course “stagflation” which I would define as real GDP growth net of inflation.

Taken together, what all this suggests to me is an analysis of government budgets, financial markets, and some demographic/migration data to see where various governments’ priorities lie relative to what their priorities probably should be to successfully address long-term challenges, and their likely ability to bounce back from various types and magnitudes of shock. You could probably develop some kind of risk index at the national and global levels based on this. And then what would you do with it? If you were a rational government, you could choose policies that reduce it. Maybe you turn everything over to the AIs and ask them to figure it out.