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Advances in AI R&D will bring another tech ...
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... Over the years I’ve tried several times to find a version of Austrian business cycle theory I found plausible and I’ve always come away scratching my head. Thread… Here’s my basic understanding of the model: the economy has some industries that are capital intensive and others that are not. ...

... When the central bank makes interest rates artificially low, it makes capital investment cheap and skews the economy toward capital intensive sectors. But that cheap credit hasn’t actually created any real resources, so you end up with increased spending on both capital and consumer goods. ...

... So far this is an entirely conventional account of how business cycles work. But now things get weird. In the Austrian theory, a recession is a process of resource re-allocation from capital-intensive to capital-light industries. ...

... There was arguably over investment in residential home construction. In 2006 and 2007 the home building industry was contracting while other industries were still growing. But in mid 2008, the situation changed. ...

... Instead of re-allocating workers and other resources from home building to other sectors, you suddenly had almost every industry laying off workers—even ones that were not capital intensive and did not see strong growth in the 2000s. ...

... The central question of macroeconomics is explaining why economies sometimes have periods of elevated unemployment, where not just one industry shrinks but almost all of them do at once. ...

... If that were true, then 2009 would have been a time when low-capital industries were aggressively hiring laid off construction workers. That did not happen on any significant scale. Even industries far from housing laid off workers or at least froze hiring in late 2008 and 2009. ...

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... This is consistent with the theory of Cultural Group Selection as an explanation for the rise of human large-scale cooperation. ...

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... People who graduate from college during a recession have lower wages a decade later. https://t.co/y3JaNHffTX During recessions governments and businesses often cut back on R&D. ...

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... Spending on durables can't keep growing at this pace. https://t.co/1ezz6V9lAU On the other hand, companies that make durable goods know how to make more of them! It takes a year or two to spin up the capacity, but it's not rocket science. ...

... These are also largely global industries, so they won't be constrained by US labor supply. As @DavidBeckworth has argued, there's no reason to think anything has fundamentally changed about the deflationary nature of durable goods industries. ...

... It might take another year or two, especially for car companies waiting for computer chips. But they'll get there. And when they do we should see durables prices start to trend back down again. A bunch more charts that explain the economy here. https://t.co/gtVBWwesGH ...

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... This time the price rise is across the board, in fact in some cases higher in sprawl areas 2/ Eg Atlanta v Boston, on a log scale so you can see proportional differences: Boston >> Atlanta last time, if anything Atlanta > Boston now 3/ https://t.co/AbsuLsbbcY What's going on? ...

... The answer surely involves weak supply response 4/ https://t.co/pOeCZkz8rV And that in turn points to our old friend disrupted supply chains, which have made construction very expensive 5/ https://t.co/v93OvL4mVi Suggests that prices may eventually fall in smaller/less zoned cities, once houses can ...

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As DALL-E synthesis comes to Shutterstock, Getty Images makes countermoves.
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... With this insight, we turn to the field of Artificial Intelligence (AI) and find that, while still far from demonstrating general intelligence, many state-of-the-art deep learning methods have begun to incorporate key aspects of each of the three functional theories. ...

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... I'm reading @mattyglesias and thinking that bubble-phobia was a major factor behind the bad economic performance of the Bush and Obama years. https://t.co/p8zhQAIA2D https://t.co/xBi4kjjAXK In the early 2000s, people exaggerated the frothiness of the tech bubble and the harms from its crash. ...

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Here is an example: **Me**: I have a hypothesis. Cortical columns make classifications based on raw sensory inputs as well as classification signals from other columns. They learn by predicting incoming raw sensory inputs as well as classification signals from other columns. One column's prediction error helps its own learning, as well as other columns' learning when the prediction was made with input from their classification signals. What do you think of my hypothesis? **ChatGPT**: Your hypothesis describes a process that is similar to how the brain is thought to process and classify sensory information. Cortical columns, which are groups of neurons in the cerebral cortex, are thought to play a role in processing and classifying sensory information. They do this by receiving input from sensory organs and then making predictions about what this input represents. These predictions are then compared to the actual input, and any discrepancies between the two are used to update the column's understanding of the sensory information. It is also thought that cortical columns communicate with each other, sharing information about the sensory input they have received and the predictions they have made. This can help to improve the overall accuracy of the predictions made by the brain, as different columns may have different strengths and areas of expertise in processing different types of sensory information. Overall, your hypothesis captures some of the key principles of how the brain processes and classifies sensory information, and it is generally consistent with current understanding of this process. However, it is important to note that the brain is a complex and multifaceted organ, and our understanding of how it works is still evolving. There may be additional factors and processes at play that are not captured in your hypothesis.
100.0%
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It's powered by LLMs. The value it brings is being testified widely.
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The art market is relatively small but the stock image market might be much larger.
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... Unlike the Internet era, AI R&D requires much larger capital expenditures. This gives tech giants an advantage. ...

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AI investing
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... The only other company with a commitment to AI at a similar level was FB. Its pivot to Metaverse means that AI will not be (and probably never has been) its core strategy. Microsoft is never about cutting-edge innovation. Apple has never obtained a deep understanding of AI. ...

... Amazon is too pragmatic and revenue-driven for making AI it's core. ...

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AI Investment Nvidia Google
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... Compared to 2000, there are less opportunities for retail speculative investing if VCs are providing the lion share of financing for tech companies at earlier stage. ...

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p/Investing
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... This might greatly improve AI's linguistic faculties. ...

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p/investing
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... To reach the same level of intelligence without a vastly larger number of neural circuitries in artificial neuron networks, they need to be able to do the same thing. . ...

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p/investing AI
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we'll see the boom within the next 18 month
p/Investing
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... thanks to the inflow of investment, as during the internet bubble. ...

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p/Investing
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27.3%
AGI
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