ironborn123

Even a teleoperated version can command a huge market. Think millions of robo butlers operated by gig workers from low income countries.

Wasnt there a paper a few months back, Textbooks are all you need. yes found it https://arxiv.org/abs/2306.11644

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.

So any salad that contains chopped cabbage/broccoli and eaten daily should do the trick?

There are weaker formal systems like Presburger arithmetic (peano without multiplication) and Skolem arithmetic (peano without addition) that have been proven to be complete and consistent. Tarski also showed that there are formal systems for real numbers (hence also geometry) which have the same properties. (although the real numbers include integers, the integers alone have a lot more structure and so Tarski's result does not imply Peano)

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.

While willpower may work for some people, what actually works for me (and i believe the majority of people) is self-deception or distraction.

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.

Rather than asserting that current LLMs are at their tail end, or that AI isnt good enough, it is much more instructive to check what are the bottlenecks or constraints to further progress, and what would help remove these bottlenecks.

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.

one (quite convincing) theory is that anything that can be achieved by a carbon-based neural network (eg. human brain) can also be achieved by a silicon-based neural network. The hardware may change, but the hardware's software expressiveness shouldnt be affected, unless there is a fundamental chemistry constraint.

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.

How can a declining population selling mostly commoditized goods support ever increasing property prices, that too when property is already overleveraged!!

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

I get the feeling the article preaches to the choir.

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.

I like the fact that Andrew is very transparent and honest about his experiments.

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.

Not going to say US behavior is morally sound in this case, but

- 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.

We can debate about expressions/terminology, but these three countries are very very closely aligned with the US. Ofcourse its mutually beneficial.

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.

Lets not drag Japan into this. They have very high standards in research despite the few examples you gave here, some of which are not even science related.

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.

It would only be logical if Chinese intent also matched its capabilities, which remains to be seen.

Anyone can talk a big game.

Yes but both sides can play the game of blocking cargo. Malacca strait comes to mind.

All what you said may be true, but ASML would still be foolish to trust and export to China, given that the latter is hell bent on copying and reverse engg its products, even if unsuccessfully for now.

Dont assist even your incompetent adversary. Competition 101.

Lets just say semiconductor manufacturing is the best example of regional competencies and global trade.

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.

No,even though the 10 pikachu fans assess independently, their estimations will be correlated. As you may already know the overall estimate wont be 100%, rather about 65%. The formula when the assessors are known to be independent, is simpler and has already been indicated by another commenter, P(A1 or A2 or A3 or ..An) = 1 - P(not A1)P(not A2)..P(not An)

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.

Alright lets do some calculations. Feel free to dissect the assumptions.

K event = Kim says Material L is RTSC

D event = DFT says L is RTSC

S event = L is actually RTSC

we have assumed P(S/K) and P(S/D) are each 0.1, though we could have chosen other numbers for them as well.

We want to estimate P = P(S/(K and D))

P = P((K and D)/S)P(S)/P(K and D)

Assuming Kim and DFT are in the business of making positive predictions, they always get it right when L is actually RTSC.

so P(K/S),P(D/S) and P((K and D)/S) are all taken as 1

hence P = P(S)/P(K and D) = P(S)/(P(K)P(D/K)) = P(S/K)/P(D/K) = 0.1/P(D/K)

(similarly, P = P(S/D)/P(K/D) = 0.1/P(K/D))

But ofcourse we dont know P(D/K) or P(K/D). We could check historical data on how often D aligns with K, a messy exercise at best. Say they dont perfectly align, then the conditionals are less than 1,and P>0.1. Even intuitively when K (or D) gets additional support in the form of D (or K), your P should increase, not decrease.

If we assume D and K align on average, then P(D/K) or P(K/D) is 0.5, and we get P = 0.2.

You may estimate everything above differently, thus getting a different P. You can also come up with your own way of modelling this. I came up with my particular estimate to understand how frequently should i follow the news, and care about the whole thing. You should model it according to your usecase.

You are right, but probability estimation of possibly novel phenomena is an ill posed problem.

So either you do not model it at all, or come up with some mental model of what probability you are comfortable with and due to which factors; the factors being more important than the final number.

- Nothing against Russian researchers, but apart from Iris who is somewhat anonymous and doesnt have the required equipment to create good samples, I havent seen anyone from there interested in performing expts on this

- There have already been some retractions from China after the initial replication claims. I get the feeling they have been overeager about this to prove themselves. Maybe if they approach this with cooler heads, they could be depended on more.

- When i said western labs, i spiritually include japan, taiwan, south korean labs in that, since they generally have similar practices and rigor (even if geographically they are in the east)

There are 2 things in favor of the Korean team

- Hyun-Tak Kim is unlikely to ruin his career and legacy for something careless and frivolous. But stranger things have happened, so lets assign a 10% probability to give some benefit of doubt to the team.

- The various DFT papers show interesting flat band structures. But DFT is an approximation and also they do not take into account electron electron correlations. So lets assign another 10% probability for this support.

This crude estimate would give a 20% chance of RTSC. Rest has to be resolved by actual demonstrations, primarily from the Korean team themselves, and then from reputed Western researchers/labs.

There is some evidence, though still tentative.

https://www.nature.com/articles/s41562-022-01516-2

(Evidence of a predictive coding hierarchy in the human brain listening to speech)

i view this as the newtonian mechanics vs actual reality debate. the former may not be a very accurate model of the latter, but it is very useful and it would be wrong to say there is no similarity between them.

The point is not whether it takes one week or two weeks.

But eastern competition is fierce, and the western world is mired in esg and bureaucracy.

Something is rotten at a general level, and if its not fixed soon, this trend of lagging behind will also start manifesting where it starts to hurt.

This kind of public interest and demonstrations is unique only to RTS and few other phenomena

- ordinary ppl more or less understand the importance of RTS

- a visible and understandable effect (Meissner) can be shown on successful replication

- the materials required are easier to understand, but the synthesis procedure is tricky, and purity is important

- The skills of chemists comes into play, leading to kind of a Breaking Bad feel

Maybe this us vs them mentality is the biggest bottleneck.

If instead you consider that this new form of 'alien' intelligence is actually a descendant of human intelligence, that we are raising a new species which will inherit what humans have built (ideally only the good parts) and then improve upon it further..

It may sound grandiose, but that perspective changes everything.

A question that arises, how good is chemical vapor deposition (albeit a very expensive way and hence for labwork only) in creating a pure sample with proper Cu substitutions?

I may be wrong, but it seems..

US labs dont find replication work exciting enough. If the effect is genuine, good, if not, life goes on.

Chinese labs are looking to build credibility, so they will benefit by publicly resolving this.

Brave are those who have set out to make prompt engg an entire industry, with gpt-5 and gemini lurking on the horizon.

note that f_n = (a^n + b^n) / sqrt(5) ~ a^n / sqrt(5)

the denominator is important.

also another interesting relation is a^n ~ f_(n+1) + f_(n-1) = f_(n+2) - f_(n-2)