adam_arthur

6 ms·

31.
by adam_arthur 3mo ago
Information density of the interpretability of the intent from the perspective of a human (or human-like). If the intent is not easy to understand, it's information sparse. Because it takes a lot of CPU (or brainpower) to interpret. Yo
32.
by adam_arthur 3mo ago
Information density of the prompt is the most important factor in my experience. And interestingly, LLMs seem particularly bad at writing prompts for other LLMs for this reason (you can guide them to be more dense, just speaking by default)
33.
by adam_arthur 3mo ago
You seem to be missing that if prices are lower, demand is lower. Price is a function of demand. If rents go from 10000/month at 100% occupancy to 5000/month at 100% occupancy, demand has been materially reduced. That occupancy wi
34.
by adam_arthur 3mo ago
Not much moat, incremental improvements, cherry picking models to compare. To be fair, seems more correct to compare against similar strength models if your main edge is pricing.
35.
by adam_arthur 3mo ago
The level of "slop" produced by AI is a direct function of skill of the developer and broadness of the prompts. Broad prompts by unskilled users results in a complete mess. Targeted prompts by a skilled person reviewing the code p
36.
by adam_arthur 3mo ago
Testosterone is directly causally inverse to bodyfat in men (once above some very low baseline) Fat directly converts testosterone to Estrogen via a process called aromatization. Personally my Testosterone close to doubled when going from 2
37.
by adam_arthur 3mo ago
The main difference I'd guess is whether your prompts are targeted or broad. Less experienced people tend to use very broad prompts. Experienced people tend to understand the structure of the code and give explicit guidance such that a
38.
by adam_arthur 3mo ago
Drop in rents is drop in demand, plain and simple. Fewer businesses want to invest and move into Seattle at the price it used to cost. It's true that if occupancy is poor, then a recovery in occupancy will bring more activity. It'
39.
by adam_arthur 3mo ago
An increase in vacancies across the board is reduction in demand, plain and simple. That the new equilibrium price to re-tenant all the buildings is lower is evidence of that. But the OP is correct that when enough of the building owners de
40.
by adam_arthur 3mo ago
Vibe-coding the implementation. I haven't had much issue with Codex, but seems Claude Code has major issues being reported nearly on the daily. They also happen to be the most boastful about not reading or looking at the code. LLMs are
41.
by adam_arthur 3mo ago
It's about information density. Most LLMs by default seem to write both text and code with low information density. You can kind of get around it by prompting them to optimize for compactness, but most just let it run with a more gener
42.
by adam_arthur 3mo ago
AI is clearly a force multiplier, both negative and positive. The truth is there are prolific developers like Antirez who have built quality new projects at an incredible pace (Dwarfstar 4, Redis features). But as unpopular as it is to say
43.
by adam_arthur 3mo ago
I'd like to see a world where the data vendor is separate from the app/UI product vendor. e.g. anyone could build a skin over map data, short form video data, long form video data, short form text content. Data vendor makes money
44.
by adam_arthur 3mo ago
There are hundreds of studies indicating that each marginal additional unit of bodyfat is less healthy for you than not having it. You are quoting poorly done and controlled BMI studies to dispute this, studies which look primarily at elder
45.
by adam_arthur 3mo ago
Yes it is but most of the studies use it, so that's the data we have. And the OP implicitly referenced these studies in his claim that being overweight could be healthier (which comes up in BMI studies of elderly people that don't
46.
by adam_arthur 3mo ago
A 40-70m sustained effort is effectively LISS from a study perspective. The main distinction being made is intensity, and it's impossible to sustain even a marginally intense effort for 40m (unless you redefine "intense" as d
47.
by adam_arthur 3mo ago
https://pubmed.ncbi.nlm.nih.gov/36756765/ Lowest risk is around 18-20 BMI in this recent study, which controls for many confounding factors not controlled for in other studies. Other studies show slightly higher trough
48.
by adam_arthur 3mo ago
If the LLM has to write out the reason, it is "thinking". Whether you ask it to give <reason> or <thinking>, both will produce similar chain of thought processes. To explain the "reason" requires producing th
49.
by adam_arthur 3mo ago
I'd guess through LLM embedded PoC projects. You can rack up token consumption extremely quickly when you embed LLMs into automated processes or products. I'd be very surprised if these numbers are just typical coding usage with n
50.
by adam_arthur 3mo ago
The claim comes from this study: https://www.acpjournals.org/doi/pdf/10.7326/M15-1181 Though to be clear, there aren't a ton of studies that look at bodyfat percentage. Most use BMI and similar measures.
51.
by adam_arthur 3mo ago
Yeah, typically "intense exercise" is implying HIIT style cardio. More and more studies have been indicating that even just a few minutes of intense exercise can outperform long/slow LISS type cardios. E.g. 5m all out effort
52.
by adam_arthur 3mo ago
A large volume of studies already exist. That intense exercise is good, and even very good for you, is proven as far as reasonably possible given that we can't run deterministically controlled experiments. More evidence may come out th
53.
by adam_arthur 3mo ago
The principle of what you're stating is true, it could be correlational. But there's an enormous volume of evidence that exercise, especially intense exercise, is better for health than any other intervention, including more sleep
54.
by adam_arthur 3mo ago
This is the same concept as Chain of Thought. Just that when "native" thinking is used it's hidden from the end result via special tags. If you force a model to reason about a result before producing the result, you get more
55.
by adam_arthur 3mo ago
I've found disabling reasoning entirely but adding a "reason" to the JSON response from the LLM to work significantly faster and consume many fewer tokens for narrowly scoped prompts. At least for Claude family models. e.g. {
56.
by adam_arthur 4mo ago
Mythos finds exploits largely by reading source code. Your open source dependencies may need to be version bumped quickly, but most companies are not going to be immediately exploitable without a large scale source code leak, and an attacke
57.
by adam_arthur 4mo ago
MTP or similar probably is being used on the backend, but that's transparent to the end user
58.
by adam_arthur 4mo ago
Would depend on the yield on debt vs yield on equity (factoring in earnings growth rate) If your company trades at 100x sales you should probably sell the equity.
59.
by adam_arthur 4mo ago
Half of the companies in the S&P 500 are trading at over 10x sales. SpaceX is just another one on top of the pile, whenever it gets included. Valuation multiples always mean revert on a long enough timeline... you can position for it to
60.
by adam_arthur 4mo ago
I'm talking about automation generally, not agent loops. E.g. prompt A to achieve X, output in format Y. Use Y to do something in prompt B. Agentic loops will underperform deterministic control flow pipelines (with non-determinism cons

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