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Both are about embedding tokens (words or sub-words) in a vector space. Both rely on the same fundamental principle to learn this space: tokens that appear together end up close together in the embedding space. The distance function used to compare tokens is the same in both cases: cosine distance. Even the dimensionality of the embedding space is similar: on the order of 10e3 or 10e4.

Fast forward ten years \u2014 we are now in the age of LLMs. On the surface, modern LLMs couldn\u2019t seem any further from the primitive word2vec model. They generate perfectly fluent language \u2014 a feat word2vec was entirely incapable of \u2014 and seem knowledgeable about any topic. And yet, they actually have a lot in common with good old word2vec.

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They\u2019re not quite the kind of programs you\u2019re used to dealing with, mind you. You might be thinking of deterministic Python programs \u2014 series of symbolic statements processing data step by step. That\u2019s not it. Instead, these vector programs are highly non-linear functions that map the latent embedding space unto itself. Analogous to word2vec\u2019s magic vectors, but far more complex.

Now, keep in mind that the LLM-as-program-database analogy is only a mental model \u2014 there are other models you can use. A more common one, but less illuminating, is to think of LLMs as autoregressive text generators that output one of the most likely word sequences that could follow your prompt given the training data distribution \u2014 i.e. focusing on the task that LLMs were optimized on. You\u2019ll understand LLMs better if you keep in mind a diversity of ways to model what they do \u2014 hopefully you\u2019ll find this new one useful.

If LLMs actually understood what you told them, there would be no need for this search process, since the amount of information conveyed about your target task does not change whether your prompt uses the word \u201Crewrite\u201D instead \u201Crephrase\u201D, or whether you prefix your prompt with \u201Cthink steps by steps\u201D. Never assume that the LLM \u201Cgets it\u201D the first time \u2014 keep in mind that your prompt is but an address in an infinite ocean of programs, all captured as a by-product of organizing tokens into a vector space via an autoregressive optimization objective.

I think that it is a very classic event in the very classic bubble-bursting part of the short-term debt cycle (which lasts about seven years, give or take about three) in which the tight money to curtail credit growth and inflation leads to a self-reinforcing debt-credit contraction that takes place via a domino-falling-like contagion process that continues until central banks create easy money that negates the debt-credit contraction, thus producing more new credit and debt, which creates the seeds for the next big debt problem until these short-term cycles build up the debt assets and liabilities to the point that they are unsustainable and the whole thing collapses in a debt restructuring and debt monetization (which typically happens about once every 75 years, give or take about 25 years).

To put this in context and think about how this will likely play out, I find it useful to go to my archetypical debt cycles dynamic that I cover more comprehensively in my book Principles for Navigating Big Debt Crises than I can cover here. I am linking to the PDF version available for free here and will summarize in this Observations.

The really big problem will come when there is too much of this money printing to provide creditors with adequate real returns, which will lead them to start selling their debt assets, which will substantially worsen the supply/demand balance. With the enormous size of US debt assets and liabilities outstanding, plus lots more to come, there is a high risk that the supply of government debt will be much larger than the demand for it, which will cause too-high real interest rates for the markets and the economy, leading to debt and economic pain that will eventually lead the Federal Reserve to switch from raising interest rates and selling debt (QT) to lowering interest rates and buying debt (QE). This will lead real rates to fall, which will lead to a high risk that there will be more selling of debt assets because of the bad real returns that these debt assets are providing. While people are now not thinking about the next interest rate cut and QE of the Fed, we should because the timing of these is probably less than about a year away and that will have big effects. I think that there is a good chance that it will produce a big decline in the value of money. So, it looks likely to me that the financial/economic picture over the next year or two will be tough.

A recent YouGov survey asked Americans about their knowledge, beliefs, and opinions of the American Civil War. Majorities of Americans claim to have some knowledge about the American Civil War, believe that slavery was the primary issue that led to the war, and identify the North as the winner. While there are variations in opinion based on age, race, and political affiliation, there's a general consensus about the need for young people to learn a great deal about the Civil War in school.

An overwhelming majority of Americans (91%) claim to have at least some knowledge about the Civil War, with 21% saying they know a lot about it and 70% saying they know a little. Only 9% say they know nothing at all. Men (29%) are twice as likely as women (15%) to say they have a lot of knowledge about the Civil War.

Americans' experiences learning about the Civil War growing up were more varied: A majority of Americans (64%) say they learned at least a fair amount about the war in school, while 31% say they learned not much or nothing about it. Only 12% say they learned a great deal.

There is more consensus about how much students today should learn about the Civil War in school: 79% say they should learn at least a fair amount, including 40% who say they should learn a great deal. Black Americans (51%) are more likely than white Americans (40%) to say this.

Do Americans believe that the legacy of slavery continues to impact American society? One in five (22%) say slavery has a great deal of influence on American society today and 34% say it has a fair amount; 35% think it has not much influence or none at all. Black Americans (46%) are more than twice as likely as white Americans (19%) to say slavery continues to have a great deal of influence.

While most Americans support of teaching about the Civil War and slavery in schools, there is more division on other actions that involve the war's history. By 50% to 39%, Americans strongly or somewhat support removing the Confederate flag from state flags, license plates, and other official symbols. Fewer support than oppose two other proposals: removing Confederate monuments (39% support, 50% oppose) and changing the names of streets, schools, and other public buildings that are named after Confederate leaders (38%, 52%). Support for these is lower in the South than in the other major regions.

But only recently did I see the wider paragraph, which I think offers a perceptive and challenging focusing of the lens of the line, which simultaneously invites a wide-angle view of its truthfulness. 2351a5e196