Sirenos

People like you are rare. It seems like with the ever increasing scale of mechanisation, we are seeing an increasing detachment from everything that makes us human.

I fail to understand this line of thinking. How often are you restarting the browser that this makes any significant difference in your productivity?

The author says to "work on boring problems" but I think what it really boils down to is knowing why you are solving a problem. Just picking a problem depending on how hard or easy it seems is a research mindset. Of course it doesn't make sense to apply that same mindset to more business-oriented problems (unless the business itself is research)!

Both research and business related problems are interesting. You don't have to swing between two extremes every time you have an epiphany.

Just my two cents. Nice article!

What didn't you like about it?

That looks very hacky. Is there a reason for this limitation that you've found makes sense?

You can unify the purist (1) and the ex-nix (3) into a single label: the emotionally attached.

I'm glad to see this sentiment more vocally expressed lately. It's certainly nothing that hasn't been said before, but I think that reality hasn't caught up to the frustrations faced by knowledge workers. Imagine training as a musician, learning the fundamentals, and mastering your craft, only to be used as a glorified set of fingers for playing chords.

This discussion tends to get muddled whenever I bring it up with others because it's seen as an inability to be a team player, or that I'm just trying to daydream instead of "get things done", but my retort is always that you can't know what to get done until you have done the day-dreaming. We need it back.

When you say emulation, do you mean at the logic gate level?

I would caution that it's a matter of priorities.

Currently, statistical/data-driven approaches work best, and that's what you will be expected to use whether you are building your own products, or working for an employer. Most people don't care about the GOFAI approaches anymore, seeing them as outmoded in all respects.

However, if you are curious and want to understand more of the history of approaches we have tried, and learn some really interesting algorithms along the way, I think studying the old school problems and their solutions can be both intellectually stimulating, and potentially increase your depth of understanding. After all, it's only once you've tried to solve a problem and failed miserably that you start to appreciate the depth of its complexity.

That depth of appreciation is sorely lacking in today's new cohorts, who are basically blinded by the incredibly convincing outputs of our cream-of-the-crop LLMs.

Great content! I wish I had this as a beginner. It would have saved me so much pain and time lost in the depths of google search results.

I see this sentiment expressed in almost every venue of discussion, but I never see a concrete plan, or even steps we could take right now to progress towards that future. That's why I'll always remain skeptical about technological utopianism. It simply doesn't work that way in reality.

I've read the article and frankly I don't have the expertise on LLMs to discuss whether it lands on something worth investigating further. What I do notice in the comments here though, are:

1) People nitpicking about the use of mathematical ideas in a loose manner as if every person trying to understand some phenomenon must only open their mouth if they have a watertight theory or shut their mouth otherwise.

2) Getting hung up on the use of the luigi metaphors rather than using it as the basis for a constructive criticism that actually adds to the conversation in an interesting manner.

3) A general snarky attitude towards people exploring ideas on their own. I get it, you might have some expertise that others lack but you're forgetting that you've already made the thousands of mistakes to get to where you are. Do others the courtesy of not judging when they attempt the same.

There's a great book by Culadasa: The mind illuminated. It covers a lot of what ancient meditators thought about the practice, but the essentials can be found in the first chapter.

I'm not trying to be snarky here, but why is the saturated fat in regular whipped cream bad, assuming it is not consumed in excess? This seems to be the main selling point in the article, so I'm genuinely curious.

Any experts wanna chime in?

I was a bit put off by the introductory chapter where he is using a lot of nonstandard terms such as "abstract species/genus" rather than the usual type theoretic treatment. However, take that as the remark of an ignoramus.

I'm not sure why this was posted. It's aged terribly and I think we can all agree that sidestepping constructors for init functions is basically C++ without the ++. Not sure how that's any different from writing in C.

Two counter-points (appreciate some counter-counter-points :):

1) The discrete sequencing is an epiphenomenon. The underlying processes are continuous changes in voltage and current flows. (I'm not sure if Planck scale considerations can throw a wrench in this though. Would love to be educated here.)

2) Our brains do not have ostensibly discrete neural processors. I don't think gradient descent is comparable to how the brain learns, but I think there is some reason to think that it is possible to learn symbolic processes in spite of having a processor that isn't especially built for it.

That's really interesting.

    doTheThing(readFromUser())

Let's not pretend a weekend hobby text editor is anywhere near the feature set of VSCode.

Beware of muscle imbalances on a pushup-only regimen.

I feel you. This is my biggest critique of the so-called "woke" language. Perhaps their intentions are good, but I fail to see how hiding behind inclusive language does anything to change the reality of the lives of people they claim to be helping in the first place.

Calling a "landlord" a proprietor (example from the article) does nothing to change the actual dynamic between landlord and tenant. You have only changed the symbols you use without affecting any meaningful change in the world. Maybe a devil's advocate would say, "Symbols evoke feelings evoke action and thus we are affecting people's actions". That's the strongest counter-argument I can think of, and it's not very convincing either. Not sure how a landlord would suddenly change how they act because they are now proprietors.

I think there is a middle ground. You can give a bird's eye view of the way things are done and a hand-wavy intuition for why they are done that way. Analogies go a long way towards building the latter. Then for those who want to dive deep, you can leave pointers to articles that cover such things in detail.

It doesn't always have to be a choice between writing a book and nothing at all because the topic is too complex. I personally have benefited from bird's eye view blog posts and mini-articles more than I can remember. If you have the knowledge then go for it, someone out there will thank you.

No need to be snarky. It could be new for someone just getting into the field.

Sorry, I didn't mean to downplay the value of using concrete examples. I absolutely agree that everyone learns better from concrete settings, which is why my original comment fixed the parameters for people to play with. I was referring more to the discussions of how exponents are stored biased, the leading bit in the mantissa is implied = 1 (except for subnormals), and so on. All these are distracting features that can (and should) be covered once the reader has a strong intuition of the more fundamental aspects.

Why is everyone complaining about people finding floats hard? Sure, scientific notation is easy to grasp, but you can't honestly tell me that it's trivial AFTER you consider rounding modes, subnormals, etc. Maybe if hardware had infinite precision like the real numbers nobody would be complaining ;)

One thing I dislike in discussions about floats is this incessant focus on the binary representation. The representation is NOT the essence of the number. Sure it matters if you are a hardware guy, or need to work with serialized floats, or some NaN-boxing trickery, but you can get a perfectly good understanding of binary floats by playing around with the key parameters of a floating point number system:

- precision = how many bits you have available

- exponent range = lower/upper bounds for exponent

- radix = 2 for binary floats

Consider listing out all possible floats given precision=3, exponents from -1 to 1, radix=2. See what happens when you have a real number that needs more than 3 bits of precision. What is the maximum rounding error using different rounding strategies? Then move on to subnormals and see how that adds a can of worms to underflow scenarios that you don't see in digital integer arithmetic. For anyone interested in a short book covering all this, I would recommend "Numerical Computing with IEEE Floating Point Arithmetic" by Overton [1].

[1] https://cs.nyu.edu/~overton/book/index.html

Any tips for someone who is struggling to get barely 1 piece done per week?

I wonder if this is something analogous to Parkinson's law. I have found that transitioning to a single screen was initially frustrating, but it forced me to adapt to the lack of space by condensing my writing, both code and prose.

It seems intuitively convincing and almost obvious to me that the quality of your output would be inversely proportional to the amount of available "space" for that output, although the exact relationship doesn't seem so clear.

I get the sentiment but come on. I seriously doubt you cannot even implement a binary search right now.

Is it normal that I don't have close friends and that I'm solitary? Am I missing out on anything?

Not really. Not everybody needs to or wants to have a huge circle of friends. And let's face it, it's impossible to have a huge circle of close friends. You wouldn't be able to maintain the friendships AND your studies, hobbies, etc.

What hobbies do you advise me to adopt that I can do in a group, with camaraderie?

Strength training, hiking, biking, running, dancing, watching anime/drama/movies in a group -- so many to choose from. Just try out whatever interests you. You'll end up meeting lifelong friends just doing that.

And trust me, high school is a not a big deal. It's a very small chunk of your life compared to what's ahead. And what's ahead is much much better.

My understanding of evolution was that it wouldn't necessarily give you the best possible set of "features", only ones that aren't disadvantageous enough to put you out of the race.