And proportional representation is found in the House of Representatives. We have a bicameral legislature.

No, of course not. The difference is that the ways in which we fail tend to be pretty ordered. You'd be hard pressed to find someone who's solved an Erdos problem but can't explain the difference between driving your car or walking to the carwash or can't count the Rs in their fruit names. Because if you can't count, you can't do math.

LLMs fail somewhat randomly because they do not have actual reasoning capabilities. It is hard to name that which they lack, because if we all knew, we would probably invent it.

Effectively, all problems are just search problems as" Newell and Simon argued as early as the 1950s. "LLM reasoning" today relies heavily on a side verifier. The coding loop that runs tests to see how it works, and so on. Which incidentally is what makes it so good at coding—that domain has a very quick and tight loop that can provide instant feedback about very targeted steps in their search.

But the corollary is LLM capability decays exactly along the gradient of verifier legibility. When you move to abstract problems that can't be easily verified, LLMs are pushovers with no real way to build nuanced abstract thought and literally think it through, find contradictions, decide on its own how to improve it and so on. They also have no spontaneous thinking, like you and I do in the shower sometimes. Because they have no agency, and those two things go hand in hand. Current transformer based models running on GPUs will never be efficient or fast enough to achieve that level of thinking. They're off by multiple orders of magnitude.

So the difference then is that their "approximate reasoning" is very useful, but is very flawed, and treating it as equivalent to human reasoning helps nobody. Believing in it is buying into hype, copium, and hopium. And, ironically, it likely delays the advent of proper AGI

OpenAI and Sam Altman being dishonest (or not) really has bearing on Anthropic. It's wholly unnecessary to argue about those other parties when discussing Anthropic or companies in general. Put simply, Alice being dishonest doesn't make Bob honest. But interestingly enough, OpenAI at first was also regarded as uncompromising stewards of "AI for everyone". It's in their name!

Speaking specifically about Anthropic, being concerned with AI existential risks is incredibly self-serving because guess who owns the very powerful AI that needs to be treated carefully and not allowed into the hands of other countries or competitors? All under the guise of being for the people. Even if a hundred people within the organization are doing this out of the goodness of their hearts, the company is not actually bound to that behavior and can renege on it at any point in time—just like OpenAI did.

Besides, Anthropic cofounders left OpenAI effectively forever ago. Just after GPT-2, which was pretty useless still. It was a whole different company. And the young are often naive but that naiveté eventually fades. Investors make demands, business realities sink in, and founders compromise.

This has happened time and time again. Or did you forget how Google Chrome started? Or how the shading and labeling of ads on Google has evolved over time? Or that "Do no evil" has been dropped?

The thing about my argument is that it doesn't require a purposeful nefarious motive. Corporations exist to maximize profits. When they act perfectly according top their stated goals, they make some decisions that are not in the interest of everyone else. It's important to remember that.

Rio has a strong engineering talent pool, along with many other major capitals in Brazil

It doesn't become actual reasoning just because you chose to call it so. If they did reason, LLMs would not fail at ridiculously easy problems like strawberry or car wash ones.

LLMs are great at search. They only emulate reasoning. They can't actually reason but they approximate it. Combine it with copious amount of computes and some search problems become tractable.

It's healthy to suspect ulterior motives from them.

The government can't apply export controls based on a control that does not exist. Creating one for model inference, if at all possible, would take 3-6 months at a minimum and it even includes a public comment process. That control is not cited anywhere because it does not exist.

The president can invoke emergency powers but that requires pointing to a specific foreign threat, notifying congress formally, posting on the national register, and it only lasts six months unless congress votes to renew it.

Given how easy it would have been for them to fight this, we can only conclude this was either outright designed or incredibly convenient for Anthropic.

Given their stated goal of pulling Fable by June 22nd, it seems likely they underestimated the amount of compute they would need or, even if they had perfectly estimated it, pivoting so that "the government shut it down because it's so powerful" on June 12nd is a better story than "we shut it down because we lack the compute" on the 22nd. This is especially true because the net new revenue from Fable is just from new signups between the two dates, which is likely smaller each day elapsed since the launch.