But if the universe is infinitely large then any finite thing should fit in it, right? Or are we saying that BB(748) can be infinite?
1,170 karma · joined April 11, 2010
/s
We are living in the best of times as measured by infant mortality, lifespans, literacy, poverty, and technology.
In your mind, who should bear the cost of building and maintaining large services like Instagram?
Does the SRAM latency still allow for single-cycle reads at 10G?
I understand how this might be compromising fundamental rights, but at the same time I just want to get home. Is this wrong?
The profitability of a business is a testament to its sustainability (or lack thereof). Persisting unprofitable structures is inherently unsustainable - despite how valuable they may be to users.
https://cloud.google.com/vertex-ai/docs/generative-ai/models...
At a high level, immutability forces you to be extremely deliberate about state changes in your application. This improves reasoning/understanding, reduces bugs, and eases debugging.
An example of immutability that you might be familiar with would be react props/state. You don’t modify your state. This makes reasoning about state much more simple.
An unrelated point would be that layoffs usually target the lowest-performing segment of the workforce and offer legal protection to the company against unlawful termination. Of course not all laid off workers are poor performers but there is obviously a correlation here.
It’s not clear to me this will ever change. While local compute will always improve (so local models become more viable), I believe that the largest and most capable models will always be cloud based.
Isn’t this a red herring? Do you need to provide a smart phone or just a phone? If it’s a smart phone do you need to enable unfettered access or just the safety related apps you need?
There seems to be less next-level analysis: which topics are more prone to inaccuracy, does the critique loop actually help LLMs overcome those inaccuracies, and do the benefits of LLMs outweigh the consequences of these inaccuracies?
The vocab size is larger than 256 (or in your example 2) because some sequences of bytes occur much more frequently than others. This allows the model to generalize more efficiently.
By analogy consider that we think of “words” as atomic concepts much more than we think of the individual lines that make up the letters in a word - even though the former can be thought of being composed of the latter.
Still, I think LLMs are different than phones in terms of scaling. Faster processor speeds don’t necessarily result in more user value for phones, but scaling up LLMs seem to predictability improve performance/accuracy.
To be clear I’m not passing a moral judgement on sex work - just pointing out the fact that it’s presently illegal in many forms and jurisdictions and that fact is relevant.
That said I think there’s reason to be skeptical about the link between rising rates implying more bonds sold - particularly as you consider other factors like creditworthiness.
This is hilarious