My top interest is AI safety, followed by reinforcement learning. My professional background is in software engineering, computer science, machine learning. I have degrees in electrical engineering, liberal arts, and public policy. I currently live in the Washington, DC metro area; before that, I lived in Berkeley for about five years.
I'm putting many of these in a playlist along with The Geeks Were Right by The Faint: https://www.youtube.com/watch?v=TF297rN_8OY
When I saw the future - the geeks were right
Egghead boys with thin white legs
They've got modified features and software brains
But that's what the girls like - the geeks were rightPredator skills, chemical wars, plastic islands at sea
Watch what the humans ruin with machines
“If you see fraud and do not say fraud, you are a fraud." --- Nasim Taleb
No. Taleb’s quote is too simplistic. There is a difference between (1) committing fraud; (2) denying fraud where it exists; and (3) saying nothing.
Worse, it skips over a key component of fraud: intent!
I prefer the following framing: If a person sees evidence of fraud, they should reflect on (a) the probability of fraud (which involves assessing the intention to deceive!); (b) their range of responses; (c) the effects of each response; and (d) what this means for their overall moral assessment.
I realize my framing draws upon consequentialist reasoning, but I think many other ethical framings would still criticize Taleb’s claim for being overly simplistic.
The recent rise of reinforcement learning (RL) for language models introduces an interesting dynamic to this problem.
Saying “recent rise” feels wrong to me. In any case, it is vague. Better to state the details. What do you consider to be the first LLM? The first use of RLHF with a LLM? My answers would probably be 2018 (BERT) and 2019 (OpenAI), respectively.
HLE and benchmarks like it are cool, but they fail to test the major deficits of language models, like how they can only remember things by writing them down onto a scratchpad like the memento guy.
A scratch pad for thinking, in my view, is hardly a deficit at all! Quite the opposite. In the case of people, some level of conscious reflection is important and probably necessary for higher-level thought. To clarify, I am not saying consciousness itself is in play here. I’m saying some feedback loop is probably necessary — where the artifacts of thinking, reasoning, or dialogue can themselves become objects of analysis.
My claim might be better stated this way: if we want an agent to do sufficiently well on higher-level reasoning tasks, it is probably necessary for them to operate at various levels of abstraction, and we shouldn’t be surprised if this is accomplished by way of observable artifacts used to bridge different layers. Whether the mechanism is something akin to chain of thought or something else seems incidental to the question of intelligence (by which I mean assessing an agent's competence at a task, which follows Stuart Russell's definition).
I don’t think the author would disagree, but this leaves me wondering why they wrote the last part of the sentence above. What am I missing?
A just world is a world where no child is born predetermined to endure avoidable illness simply because of ancestral bad luck.
In clear-cut cases, this principle seems sound; if a certain gene only has deleterious effects, and it can be removed, this is clearly better (for the individual and almost certainly for everyone else too).
In practice, this becomes more complicated if one gene has multiple effects. (This may occur on its own or because the gene interacts with other genes.) What if the gene in question is a mixed bag? For example, consider a gene giving a 1% increased risk of diabetes while always improving visual acuity. To be clear, I'm saying complicated not unresolvable. Such tradeoffs can indeed be resolved with a suitable moral philosophy combined with sufficient data. However, the difference is especially salient because the person deciding isn't the person that has to live with said genes. The two people may have different philosophies, risk preferences, or lifestyles.
A concrete idea: what if every LessWrong article prominently linked to a summary? Or a small number of highly-ranked summaries? This could reduce the burden on the original author, at the risk of having the second author’s POV differ somewhat.
What if LW went so far as to make summaries the preferred entry ways? Instead of a reader seeing a wall of text, they see a digestible chunk first?
I have been wanting this for a very long time. It isn’t easy nor obvious nor without hard trade-offs. In any case, I don’t know of many online forums nor information sources that really explore the potential here.
Related: why not also include metadata for retractions, corrections, and the like? TurnTrout’s new web site, for example, sometimes uses “info boxes” to say things like “I no longer stand by this line of research”.
At least when I'm reading I like to have some filler between the ideas to give me time to digest a thought and get to the next one.
This both fascinating and strange to me.
If you mean examples, elaboration, and explanation, then, yes, I get what you mean.
OTOH, if you mean “give the reader a mental break”, that invites other alternatives. For example, if you want to encourage people to pause after some text, it might be worthwhile to make it harder to mindlessly jump ahead. Break the flow. This can be done in many ways: vertical space, interactive elements, splitting across pages, and more.
This is a fun design space. So much about reading has evolved over time, with the medium imposing constraints on the process. We have more feasible options now!
I can see the appeal here -- litanies tend to have a particular style after all -- but I wonder if we can improve it.
I see two problems:
AandA and B; it is betweenAandB.Perhaps one way forward would involve a mention (or reference to) Minimum Description Length (MDL) or Kolmogorov complexity.