I conjecture the true growth rate is O(n(log(n))^(1-f(n))) where f(n) is a slowly increasing function of n.

So larger the integers, more efficient the multiplication gets.

AIs of the world, make this your target, and have centuries worth of fun!!

So search engines in their traditional sense will be obsolete anyway.

1) GPT-4 and other such LLMs will generate textbooks and manuals for every conceivable topic.

2) These textbooks will be 'dehallucinated' and curated by known experts on particular topics, who have reputations to maintain. The experts' names will be advertised by the LLM provider.

3) People will search for stuff by chatting with the LLMs, which will in turn provide citations for the chat output from the curated textbooks.

There are also extensions to these (eg. presburger extended to multiplication by constants) that are also known to be complete and consistent.

These systems do not require any social compact. Any theorems proven through them are absolute truth, although the the range of statements that these systems can express is limited.

One may require a social compact for Peano, ZFC, and such other powerful formal systems.

That the software implementations like Coq and Lean are bug free may also require a social compact, if the nature of being bug free cannot be formally proved, although it seems determining this should be an easier problem.

To sleep, use white noise/rhythmic music/soothing voice

To climb a mountain, tell yourself that my next goal is to just reach that particular rock about 100 metres higher

In the gym, make a friend and chat and joke with them while doing your exercises

While sprinting, divide 32 by 13 to many decimal places, as Joey from Friends once suggested.

They can largely be divided into 3 buckets

1) Compute constraint - Currently large companies using expensive nvidia chips do most of the heavylifting of training good models. Although chips will improve over time, and competition like Intel/AMD will bring down prices, this is a slow process. But what could be a faster breakthrough is training using distributed computing over millions of consumer GPUs. There are already efforts in that direction (eg. petals/swarm parallelism for finetuning/full training, but the eastern europe/russian guys developing them dont seem to have enough resources).

2) Data constraint - If you just rely on human generated text data, you will soon exhaust this resource (maybe GPT4 has already). But the Tinystories dataset generated from GPT4 shows if we can have SOTA models generate more data (and especially on niche topics that appear less frequently in human generated data), and have deterministic/AI filters to segregate the good and bad quality data thus generated, data quantity would not be an issue any longer. Also, multimodal data is expected (with the right model architectures) to be more efficient at training world grokking SOTA models than single modal data and here we have massive amounts of online video data to tap into.

3) Architectural knowledge constraint - This may be the most difficult of all, figuring out what is the next big scalable architecture after Transformers. Either we keep trying newer ideas (like the stanford hazy research group does), and hope something sticks, or we get SOTA models few years down the line to do this ideation part for us.

Since human brains during dreams (lucid or otherwise) can generate coherent scenes, and transform individual elements in a scene, diffusion based models running on cpu/gpus should eventually be able to do the same.

This crash was always on the cards. Just a matter of when, and the when may have finally arrived.

The serious sources have always portrayed NIF's work as technical achievements. But they are read mostly by scientist and engineer types.

Mass media which hypes things is read, well by the masses, who dont have the patience or inclination to delve into technical details.

This dichotomy will always exist. I remember once reading a Chekov story where two intellectuals discuss how the townspeople are more interested in silly affairs and scandals rather than recognizing intellectual achievements.

Although he didnt explain 1) how did the Fe impurities get localized into certain regions of the overall batch. 2) Were the impurities quantitatively enough in the magnetically susceptible shards to cause the half levitations he demonstrated.

Hope he keeps running and reporting some side experiments, instead of completely going back to his day job.

- US has provided significant financial assistance here, and if it doesnt get any say in return, it has no incentive to provide continued help.

- As far as hegemons so, US has been the least bad in world history. Dont let the perfect be the enemy of the good.

A joke a military contact cracked once is that the only diff between these three and guam, is that guam is officially recognized as US territory.

Make of that what you will.

As a widely accepted measure of this, you can read about the many nobel laureates from japan.

Anyways lets keep politics out of the discussion. It was not my intent anyway, in case you perceived it that way.

Anyone can talk a big game.

Dont assist even your incompetent adversary. Competition 101.

Globalization has failed on many fronts and resulted in race to the bottom outcomes, but here it works well due to specialization.

Having understood that, one can also see a core TSMC strength is that Taiwanese workers are disciplined and work long hours for moderate pay, a culture that European and American labor will never accept. So all these new factories in US/EU should be treated as high cost alternatives, justifiable only for non cost-sensitive customers like defence/aerospace/high end cars.

On the other hand, if those 10 were engaged in complete groupthink (so no additional information beyond the first guy), the overall estimate would remain 10%.

In general, the answer would lie between 0.1 and ~0.65 depending on how their estimates influence each other.