A government computing project acquiring 10k GPUs is pretty impressive, but can hardly be deemed a "competitive advantage" - Google and AWS are already offering double the computing power in a single data center [1]. OpenAI is likely already using a cluster of at least this size to train ChatGPT.
>> "... ensure legal, ethical and scientific criteria are met."
Please... We are talking about stochastic models. This means that we are in the domain of Math, not the domain of Philosophy, and not Law either.
Evaluating a stochastic model, even a multivariate model, involves only two dimensions. Even if it is running on 10k GPUs. Even if it has been trained on billions of data points.
The two dimensions are:
1) Reliability
2) Validity
...and that is all. It is Statistics 101. Not only that, it is the most fundamental part of Statistics 101.
I'm sorry, but WHAT? You're talking about a software model people regularly talk about using as a replacement for google which is capable of telling you to kill yourself. Of course there are moral considerations for such a software system. Such a system could also obviously be useful as a lawyers assistant, which is then clearly related to "the domain of law".
Maybe you are referring to the fact that outputs are statistically correlated to training data, but there has been a large ongoing discussion about the very human process of collecting training data, with many moral questions worth considering.
> It is Statistics 101. Not only that, it is the most fundamental part of Statistics 101.
Any time someone says "It's [subject] 101" when applied to a complex topic, I tend to find they are oversimplifying to a fault. People tend to use the phrase when saying "it's not complicated it is very simple". (I usually hear people say "it's econ 101" while going on to repeat something like the myth of homo economicus.)
Collecting billions of datapoints and then training a system to act as an oracle capable of amalgamating all that data and speaking with apparent authority on it (while being well known to lie) is not a simple situation!
But the humans that create it do exist in that domain and so all we're talking about is tuning the stats so the outputs meet the set of philosophical demands.
We're literally a profession that gets paid almost exclusively to design autonomous systems that obey legal, ethical, and scientific criteria. What makes an LLM different from any other product?
This. I always wonder whether the people talking about ethics in AI and what not, really understand what "AI" means in terms the current state of technology
rebuttal: consider the computer software itself, being trained, emitting a model, replaying model contents on request and prompt. Now consider humans as they occur in social arrangements, daily trading information using human communication patterns, and including information regarding human situations with legal implications, damage, reputation, accuracy and fitness for purpose perhaps.. that human system of systems is where the results of commercial AI will be "consumed" .. not simply the model and its responses. Fitness for purpose immediately might include software security, chain of orders and chain of execution in business process where there are real results and real costs.. In other words, the AI products are used for real things.
Simple. Metaphysics is not math. Ethics is not math. Really, the only intersection is formal logic (until a certain German/Austrian mathematician blew it all up with his annoying theorems)
A government computing project acquiring 10k GPUs is pretty impressive, but can hardly be deemed a "competitive advantage" - Google and AWS are already offering double the computing power in a single data center [1]. OpenAI is likely already using a cluster of at least this size to train ChatGPT.
1. https://www.hpcwire.com/2023/07/27/aws-cramming-up-to-20000-...
It's the right order of magnitude. Things will happen, given the will, the acquired hardware, and the brains in EPFL and ETH Zurich.
> trustworthy AI
>> "... ensure legal, ethical and scientific criteria are met."
Please... We are talking about stochastic models. This means that we are in the domain of Math, not the domain of Philosophy, and not Law either.
Evaluating a stochastic model, even a multivariate model, involves only two dimensions. Even if it is running on 10k GPUs. Even if it has been trained on billions of data points.
The two dimensions are:
...and that is all. It is Statistics 101. Not only that, it is the most fundamental part of Statistics 101.
I'm sorry, but WHAT? You're talking about a software model people regularly talk about using as a replacement for google which is capable of telling you to kill yourself. Of course there are moral considerations for such a software system. Such a system could also obviously be useful as a lawyers assistant, which is then clearly related to "the domain of law".
Maybe you are referring to the fact that outputs are statistically correlated to training data, but there has been a large ongoing discussion about the very human process of collecting training data, with many moral questions worth considering.
> It is Statistics 101. Not only that, it is the most fundamental part of Statistics 101.
Any time someone says "It's [subject] 101" when applied to a complex topic, I tend to find they are oversimplifying to a fault. People tend to use the phrase when saying "it's not complicated it is very simple". (I usually hear people say "it's econ 101" while going on to repeat something like the myth of homo economicus.)
Collecting billions of datapoints and then training a system to act as an oracle capable of amalgamating all that data and speaking with apparent authority on it (while being well known to lie) is not a simple situation!
But the humans that create it do exist in that domain and so all we're talking about is tuning the stats so the outputs meet the set of philosophical demands.
We're literally a profession that gets paid almost exclusively to design autonomous systems that obey legal, ethical, and scientific criteria. What makes an LLM different from any other product?
This. I always wonder whether the people talking about ethics in AI and what not, really understand what "AI" means in terms the current state of technology
rebuttal: consider the computer software itself, being trained, emitting a model, replaying model contents on request and prompt. Now consider humans as they occur in social arrangements, daily trading information using human communication patterns, and including information regarding human situations with legal implications, damage, reputation, accuracy and fitness for purpose perhaps.. that human system of systems is where the results of commercial AI will be "consumed" .. not simply the model and its responses. Fitness for purpose immediately might include software security, chain of orders and chain of execution in business process where there are real results and real costs.. In other words, the AI products are used for real things.
This is why safety considerations do apply.
Where is the firm dividing line that separates math from philosophy?
Simple. Metaphysics is not math. Ethics is not math. Really, the only intersection is formal logic (until a certain German/Austrian mathematician blew it all up with his annoying theorems)
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Whoa, please keep nationalistic flamewar off HN. Last thing we need here.
https://news.ycombinator.com/newsguidelines.html
Why not?
Given a fact just today a news came out that CH bank been caught hiding billions in assets from IRS, I think you have your answer.
they're known for trustworthy and extremely private banking, for one
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