Liu Hu sums up the scene in a few words: “Outside of China, journalists are fired for writing false reports… Inside China, they are fired for telling the truth.”
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Using your talents to identify and invest in high-quality assets and pull money away from low-quality assets is a benefit to everyone involved in the market and, on the larger scale, the market’s future. If you invest in this way, you will beat the market.
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Cinelytic’s AI does is what every AI does at its most basic level. It collects and sifts large amounts of data to find patterns that can be used to make predictions. AI excels at pattern recognition because that is its only purpose. Humans aren’t so linear or predictable.
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Jay Richards asks: Just imagine if our government had taxed earlier technological innovations because they threatened jobs. Does anyone think a targeted “tractor tax” would have been a good idea in the early twentieth century?
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Two theories of human consciousness are about to be tested in a historic contest. Integrated Information Theory (IIT) of consciousness and rival Global Workspace Theory (GWT) have sharply different implications for consciousness in machines.
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Computer algorithms are much, much better than humans at discovering statistical patterns but much, much worse than humans at discerning whether the patterns are meaningful. Wise investors can use the resulting blips to their advantage.
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AI catches things doctor miss, and doctors catch things AI misses. Using the AI to highlight what may be cancer tissue helps the radiologist focus on ambiguous situations, reducing the chance of missing early cancers.
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David Hilbert wanted all mathematics to be proved by logical steps. Kurt Gödel showed that no axiomatic system could be complete and consistent at the same time.
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New research puts us back where we started. The foxes are tame. But why are they tame? Other foxes are decidedly not tame. Why is it so easy to “tame” dogs and cats but not wolves and bobcats?
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Tim Harford points to the Sanchez tragedy to raise an important question: How do we know when a given technology is really helping us? And when we are taking too great a risk or paying too high a price?
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If I could rewind time a week and add a piece of 2019 sci-fi to my list of the year’s Best and Worst Sci-Fi TV, I would add Netflix’s Lost in Space, Season 2—which came out just after I had published. Let's fix that now.
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Both computers and humans can be fooled by patterns that appear significant but really aren’t. But the bigger the computer, the more random patterns it can find in the vast swathes of data processed.
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Some problems experts hope AI can help with may be outside AI's capacities. Some people may simply want to believe doctored images and deepfakes, for example.
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Larry L. Linenschmidt interviews Robert J. Marks on the difference between performing a task and understanding the task, as explained in philosopher John Searle’s famous “Chinese Room” thought experiment.
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Because Tesla has yet to make a yearly profit in any of its sixteen years of existence, it depends on capital raises of various forms (equity, debt, etc.) to stay in business. Capital raises require big promises and Tesla’s overstatements about its self-driving cars are always good for a few billion.
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A major consequence of the advance of modern neuroscience is that we now “know” so much less than we used to. But what we do know points us in promising research directions.
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Many models are ridiculously simplistic, making the results worse than worthless. They become a way of solidifying biases.
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There is no doubt that consciousness is a fundamental property of animal and human existence. As philosopher Philip Goff notes, a philosophy like materialism that cannot plausibly account for it cannot be correct.
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What Google really achieved was increased stability in its quantum computing platform—keeping qubits stable has been a hard problem in quantum computing for a long time. That was certainly a step forward, but advertising it as “quantum supremacy” was certainly a classic exercise in hype.
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In 2019, I fell out with Netflix. I felt bombarded by more and more edgy content, as though Netflix wanted me to know how “adult” it is. Rather than producing a few amazing originals, Netflix started vomiting up a ton of terrible originals.
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