gspetr
Joined 11 years ago
Karma
992
Submissions
724
Member since
Aug 4
Recent submissions
Comment · 2 months ago
> Combine A + B
Really, compress. Compression is a useful proxy for intelligence.
To compress data efficiently, an entity must discover the underlying patterns, structures, and regularities within that data. Identifying these structures is precisely what we define as "understanding" or "intelligence.
Anything we put into writing can be thought of as a string of data. The Kolmogorov complexity of a string of data is the length of the shortest possible computer program that can output that string.
A good compressor doesn't just memorize (yes, there's a reason LLM writing features the "it's not just X, it's Y pattern"), it builds a generalized model to handle unseen, similar data. LLMs are trained by compressing the internet into weights, they use this to write new code.
When an LLM is trained, it compresses ...bytes of human text into a few ...bytes of neural network weights. When you ask it a question, it uses that compressed model to generate (decompress) a coherent response.
Consider the dichotomy:
LLMs display emergent reasoning, coding capabilities, and logic because they were forced to compress human language so tightly.
LLMs often suffer from "hallucinations" and struggle with novel logic puzzles because compression encourages mimicking statistical patterns rather than building a true causal model of the physical world.
An algorithm can achieve massive compression if it utilizes a highly complex, slow, or massive decompression engine. If a system takes 10 000 years to decompress a file, or requires an infinite amount of computing power (like Kolmogorov complexity), it cannot function as a practical intelligence. Real intelligence must operate within tight time and energy constraints.
> Maybe there's true brilliance out there
Brilliance is a trope. pg's 2009 "The Anatomy of Determination" deals with it: https://www.paulgraham.com/determination.html
In it, he argues that determination is the single most important predictor of success, surpassing even raw intelligence.
While popular culture loves the narrative of the "brilliant genius," Graham's experience backing hundreds of startups taught him that a highly intelligent person without drive quickly becomes ineffectual. Conversely, a profoundly determined individual can find pathways to success even in ordinary or unglamorous industries. Over time, determination actually starts to look like talent.
I'm going to commit a faux pas (a breach of HN etiquette) and give an AI summary in 3 bullet points because, well, the article deals with 3 points, so it's a good fit and I doubt I can compress it better than AI:
1. Willfulness. The desire to get your way regardless of obstacles or consequences.Being fearless about consequences and pushing through "hellacious" moments when others quit.
2. Discipline. The ability to force yourself to do what you planned to do. Being "hard on yourself" and turning off the background analysis in your mind that questions the plan.
3. Ambition. The grandness of your destination and what you want to achieve. Choosing the right target; if determination is a vector, ambition is the direction it points.
Of these 3, it's quite obvious at this point that LLMs are superior at 1) and 2), as LLM alignment is quite good, and it's ability to spin up sub-agents that can work for over 24 hrs is better than humans. Human limit is basically 1 hackathon's worth of cognitive work. Beyond that, health becomes a concern, and how many people can produce useful work under sleep deprivation? Codex can work for 24-ish hours, as evidenced by today's "Auto-research with codex: How I achieved a 232x Faster Kernel": https://news.ycombinator.com/item?id=49309549
So what's left for mere mortals? Apparently, nourishing your ambition:
"So here in sum is how determination seems to work: it consists of willfulness balanced with discipline, aimed by ambition. And fortunately at least two of these three qualities can be cultivated. You may be able to increase your strength of will somewhat; you can definitely learn self-discipline; and almost everyone is practically malnourished when it comes to ambition."
Comment · 4 months ago
> Do the anti-DST people understand what they're advocating for?
They do, which is why only 45 countries observe DST.
25 observe it partially.
And the rest, roughly ~125 countries do not.
Historically, ~140 countries did.
To put this into perspective, only about 1.2B people out of 8.3B observe it today. Which puts you into a very small <15% minority.
Comment · 4 months ago
The government? Or your government?
Because there are countries where national or state governments do.
Comment · 4 months ago
Comment · 4 months ago
> formalize these 20 pages of requirements, death by powerpoint style, and put it in our suggestion box - I just pass on that.
Why pass on it now? There has never been a better time in history to deal with it than today: AI can oneshot most of what you've described.
Comment · 4 months ago
$20/kg is a wild claim.
A typical American semi-truck (18-wheeler) can carry between 40,000 and 45,000 pounds (20 to 22.5 tons) can travel only 160k miles (2/3 distance to the Moon) on a budget of $400k (i.e. $20/kg).
Do you expect us to believe that rocket transportation would be in the ballpark of truck prices in the near future?
Comment · 4 months ago
You're right about reason #1. And you've probably heard about strong contenders for #2 and #3.
There's a famous quote attributed to the Italian military commander Gian Giacomo Trivulzio in 1499.
When asked by King Louis XII of France what preparations were needed to invade the Duchy of Milan, Trivulzio responded: "To carry out war, three things are necessary: money, money, and yet more money."
Comment · 5 months ago
You're thinking of a perfect world. We're not in it.
In this one there are often thousands of applicants for a position, most of which can't pass FizzBuzz.
Why would they (or anyone for that matter) choose a candidate who can't figure out how to find info about a trivial method?
Comment · 5 months ago
No worries. My point is, if you get asked questions that seem simple to the point where you feel they're asking if "water is wet", then you need to keep your own thinking process extremely simple in response.
The reason is the intent behind their question, which they don't vocalize.
This question means we are dealing with an extremely broad hiring funnel designed to fail people who can't FizzBuzz and need to keep answers at MVP level.
In other words, if you are asked to put out a fire use a bucket of sand, not a state-of-the-art fire extinguisher.
Comment · 5 months ago
It's simple, unless you're given a specific broader context (like we have an enterprise customer data pruning system that needs to handle a broad range of corner cases) then you must not resort to overengineering this early in an interview.
Comment · 5 months ago
No, there's literally a "find" str method.
str.find(sub[, start[, end]])
"Return the lowest index in the string where substring sub is found within the slice s[start:end]. Optional arguments start and end are interpreted as in slice notation. Return -1 if sub is not found."
Your instinct to resort to "in" is correc,t as it's generally slower than the "in" membership test, but the interviewer has even allowed the use of Google. Blanking out after that is really bad.
Comment · 5 months ago
I don't understand how you jumped to the membership test instead of literally the .find() method on a string?
The interviewer is not asking to solve a problem here, they're asking for a simple ability to follow instructions, hence the offer to use Google to find the correct answer.
You could make a very solid case for using "in" (it is 2-4x faster), but only after you've solved the task at hand, this is what is expected in interviews. Not knowing the interview meta makes an average Joe basically unhireable in this market.
I never dismiss anyone's claims. I simply say that if there's evidence that you have - let us see that evidence. But assertions are often made not only without any evidence being offered but without anyone even asking for evidence.