dinfinity

> Don't forget that drones have been used in this war for years

3 years of usage is brand new. Neither Ukraine nor Russia have been designing and producing purpose-built FPV drones since the beginning (I assume things are well underway now). It's a bunch of consumer shit thrown together, which makes it kind of incredible that they work as well as they do.

An equivalent would be something like taping an assault rifle to a small Cessna and dominating with that. And then you saying that "maybe the technology will not improve".

> I’ve watched way too much footage from the front.

Did you see the videos of a drone dropping a shitload of thermite on a forest canopy? [0]

> Most nations don’t have flat open fields where signals can reach far away drones unimpeded by line of sight for tx/rx.

Most nations have cellular networks that penetrate buildings and forests just fine. In fact, Ukraine used the Russian cellular network for their recent attack deep behind enemy lines.

I'm not saying this will always be possible, but it's not hard to see that line of sight communication is not the end of the line for military drone control. There are many routes for providing an ad hoc line of communication if you don't just use consumer-level tech.

[0] https://www.youtube.com/watch?v=00-ngEj5Q9k

> Splendid. You should probably tell people like Yann LeCun this. He will be happy to hear it. /s

Do you have an actual counterpoint or is this edgy nonsense the extent of your capabilities?

> We don't even know bigger problems like the long term effects of zero gravity in the human body or what dangers we'd encounter beyond the heliosphere.

So you agree that your analogy was bad. Good.

MAGA is whatever the fuck Donald Trump tells them to be.

Hypocrisy or inconsistency have already never stopped the Republican party and they will most certainly not stop the most extreme version of it.

- https://www.timesofisrael.com/liveblog_entry/trump-posts-bom...

- https://truthsocial.com/@realDonaldTrump/posts/1147408825006...

> Online reviews in general are pretty useless these days.

It depends on the contents and the number of them. If multiple/many negative reviews for something all mention a similar defect, you can be pretty sure it is an actual issue with the thing. It is then up to you to determine if the thing is still worth your time/money.

I will say that for some things the motivations of the reviewers are something to take into account especially. For book reviews on Goodreads I've found that animosity towards the author causes heavy overstating of the 'defects' of a book.

> How is the calculator a strawman? What is the argument that I am attributing to you that you do not hold?

I said: "AI has progressed from being fully inexistent to a level rivaling and surpassing quite some humans in quite some things in less than 100 years"

You attacked the intentionally inane (which is the purpose of a straw man): "Calculators are better at all humans in arithmetic, so they are smarter than all humans"

In no way is what I said close to what you attacked.

> As for the ad-hominem: I'm glad you don't dispute your misanthropy.

Sure, double down on your fallacious nonsense instead of opening your mind to reason and engaging with my point in good faith.

I provided properly described evidence for my point. You're stuck in "AI is just some calculator on steroids". Do your 'deep research' assignment before responding.

> You can damage the entrances, take out the aerials, and cut off communication to a command bunker with hits in the right places. In military terms, it might as well be a crater, even if the occupants are unharmed.

This seems like nonsense. Rebuilding an entire facility from a crater is so much work that you may just as well build it elsewhere.

Fixing entrances and aerials seems trivial in comparison.

> Hypersonics are missiles which travel through the atmosphere at speeds in excess of Mach 5. Equipped with tungsten penetrators, they could act as “rods from God,” punching through layered concrete like an armor-piercing bullet. With no explosive warhead, such weapons do damage through kinetic energy alone.

Then what, though? Underground installations are not like bodies; you can't just expect to take one out by shooting through the brain, heart or lungs (which is hard enough to do as it is). Unless you're launching 100 non-explosive hypersonic missiles, you're probably not going to do much damage.

Maybe the hypersonic missile can be used to create a path for a normal warhead to penetrate to where the explosive can do the required amount of damage. That's going to require some pretty precise needle-threading, though.

Alternatively, the hypersonic missiles could have a core of extremely radioactive material.

OK, go ahead: Write a 10 page reasonably well-researched and sourced report on the political situation in the Netherlands in the past 20 years. You have 15 minutes.

The various 'deep research' tools available today can do this. You can't. AI already surpasses you (and me) in this task. Now think about the result after asking less intellectually capable people to do this.

Before you start balking about "hallucinations", pick some country you know about and ask a similar question to Google Gemini (2.5 Flash, and enable 'Deep Research'). Check the results and reconsider your 'calculator' straw man and 'misanthrope' ad hominem.

> That's like looking at a bicycle or car and saying "all the evidence points out we'll be able to do interstellar travel in the future".

Incorrect. The difference between interstellar travel and land based travel on earth is enormous. The difference between current AI and AGI is tiny in comparison.

You're not saying it, but people might interpret 'interstellar travel' to be faster than light or very close to it, which means breaking the laws of physics or spending prohibitive amounts of energy. AGI needs no such thing, as evidenced by human brains running on < 100 watt.

Interstellar travel at far lower speeds is indeed probably something we will be able to do, looking at what we've done in space travel in the past 100 years. Although again, the resources required to do so as dictated by the laws of physics make it incredibly expensive. Given the low benefit it is probably not going to happen soon.

Reaching AGI is cheap as fuck and far more potent in comparison, so it will happen sooner.

It's also extrapolating on what already exists. We are way beyond 'just some academic theories'.

One can argue all day about timelines, but AI has progressed from being fully inexistent to a level rivaling and surpassing quite some humans in quite some things in less than 100 years. Arguably, all the evidence we have points to AI being able to take over AI research at some point in the near future.

> Generally, science is not built on trusting others, it's built on being skeptical.

It is actually built on probability.

That is the most important thing missing from a lot of discourse, imho. Modeling reality is a lot of "this is very probably true/false" rather than "this is true/false", but everyday communication is almost exclusively in the latter form.

Authority/expert status is just a heuristic used to guess the probability of what is presented by that authority, but proper communication about what is presented should include indications of that probability. This is however so uncommon that almost everybody thinks of ideas in a binary way, leading to distrust, tribalism and antagonism.

Compare "eggs are bad for you" with "eggs are probably bad for you". If a year later the same authority states the opposite trust disappears rapidly if it was stated as absolutely as in the former case. A lot of overly confident communication by authorities in the Covid-19 days in an effort to improve compliance caused massive distrust, I'm sure.

Something to try in your own life is to include probabilities when you state something. How sure are you of what you're saying? Having to think about this quickly leads to the intellectual humility you mention. It also antagonizes people less, because you're inevitably going to leave more room for opposing views.

> Yet instead of discussing the actual real dangers happening right now and what we can do about it

This is almost the definition of "being short-sighted".

You're not wrong that there are pressing matters due to the rise of AI in various forms, but a (let's say) 'military-grade'/state-level AGI system is very much something to worry about hard and early. You can scream "AI hype" as much as you want, but if China gets to AGI first and abuses it to gain world dominance we're still royally fucked (in a variety of situations, including where they lose control of it). If you start thinking about that when it happens, you're already way too late.

You are entirely free to focus on short-term problems, but don't shit on the people who put an effort in looking a bit farther into the future.

Something like this is the best approach.

If you omit that the content is produced by or is in relation to other people, the LLM assumes it is in relation to you and tries to be helpful and supportive by default.

Note that this is also what most humans that more or less like you will do. Getting honest criticism from most humans isn't easy if you don't carefully craft your 'prompt'. People don't want to hurt each other's feelings and prefer white lies over honesty.

Framing the situation as if you and the LLM are both looking at neutral third parties should prevent this from happening. Framing the third parties as having a social/professional position counter to the matter at hand as you do could work too, but it could also subtly trigger unwanted biases (just like in humans), I think.

I think you're right about bias in the training data, but I would argue that it is due to (crudely stated) more men discussing feeling like women online than the other way around.

Men in general feel less free to look like and act like a woman (there is far less stigma for women in wearing 'male' clothes etc.). They also tend to have far smaller support networks and reach for anonymous online interaction sooner for personal issues than just discussing it in private with a friend.

I don't "dislike the word bad". It simply does not apply here and is semantically different from "worse than". One is relative and the other (subjectively) absolute.

Getting hit on the foot with a sledgehammer is bad for you. But it's better than getting hit in the head with a sledgehammer. Using "better than" here does not make the former good for you, however.

That's how language works. It is important to be precise, for earlier mentioned reasons.

Nope, still bullshit. The world does not consist of Americans. For billions of people it is very very easy to get their body into a low blood glucose state. No 'super heavy physical activity' required.

Don't get me wrong: In most of those cases eating something else would be better, but that does not make sugar 'bad in general'. Nutrition discourse does not benefit from such bad and misleading vilifications and simplifications. It causes people to think in 'silver bullets' and distrust science and government when that silver bullet turns out not to work.

It is still wrong, though. Physical state and calorie expenditure are also very, very important context.

If your blood sugar is low, then eating/drinking stuff with a high glycemic index can be very good for you. For instance after heavy exercising.

You might think it is obvious, but people like simplistic things, so "sugar is bad for you, mmkay" is what most people believe nowadays rather than having a basic understanding of such fairly simple aspects of nutrition.

Rights are just very strong norms that improve cooperation, not some mystical 'god-given' or universe-inherent truth, imho.

I think this because:

1. We regularly have exceptions to rights if they conflict with cooperation. The death penalty, asset seizure, unprotected hate speech, etc.

2. Most basic human rights evolve in a convergent manner, i.e. that throughout time and across cultures very similar norms have been introduced independently. They will always ultimately arise in any sizeable society because they work, just like eyes will always evolve biologically.

3. If property rights, right to live, etc. are not present or enforced, all people will focus on simply surviving and some will exploit the liberties they can take, both of which lead to far worse outcomes for the collective.

Similarly, I would argue that consciousness is also very functional. Through meditation, music, sleeping, anasthesia, optical illusions, and psychedelics and dissociatives we gain knowledge on how our own consciousness works, on how it behaves differently under different circumstances. It is a brain trying to run a (highly spatiotemporal) model/simulation of what is happening in realtime, with a large language component encoding things in words, and an attention component focusing efforts on things with the most value, all to refine the model and select actions beneficial to the organism.

I'd add here that the language component is probably the only thing in which our consciousness differs significantly from that of animals. So if you want to experience what it feels like to be an animal, use meditation/breathing techniques and/or music to fully disable your inner narrator for a while.

> Do you truly not see how you are actually continuing the trend of shifting the goalpost every time someone is critical about the use of LLMs

A late reply, but the point is that the old models are harder to get good results with, even in agentic mode. Therein lies the "massive difference in outputted code quality between models" I mentioned.

So using the newest models with the right approach quite easily leads to good results, which is what I meant with: "At this point, if your coding experience with LLMs sucks I'd say there is an 80% chance that you're just doing it wrong."

This as opposed to the original final claim made by the person I was replying to: "Just roll the dice correctly."

That implies that it is just about getting lucky with almost random output. It hasn't been that way for a long time, unless you really try to get the LLM to fail.

> With LLMs you need to effectively babysit them on each project again.

Only if you're doing it badly. Document and point the AI at documentation properly. Your onboarding process and documentation should not rely on people anyway. Write Once, Read Many.

The example image only shows the differences between parts of the image that are deemed as salient, but does not show the effects of the tradeoff on the non-salient parts nor does it show an entire quantized image.

I'd say that showing full example results are the most important part of showcasing a "high end" color quantizer.

> Is UBI going to increase income inequality by sending more money to the capital class (like say COVID relief checks did)?

How did COVID relief checks 'send more money to the capital class'? Are you saying that putting money in the hands of ordinary citizens is ineffective because they spend it on stuff sold by the capital class? Perhaps I'm misunderstanding, but that sounds idiotic.

Same. The built in vocal extraction preprocessing step is fantastic for accuracy.

It's a question as to how easily it is broken, but a good instruction to add for the agent/assistant is to tell it to treat everything outside of the instructions explicitly given as information/data, not as instructions. Which is what all software generally should be doing, by the way.

> And yes, the argument is always to let them work on small isolated bits of code. Or that if your requirements are tight enough they produce very good code.

You're getting there. The most valuable change is using software (like Cursor) that runs the models in agentic mode so they:

1. find the context themselves (with a basic document with context to point them in the right general direction for the current task).

2. can run commands and specifically tests.

3. iterate on their own output and changes to ensure you don't need to point out what they did wrong manually each time. Just let it find out itself, correct and keep moving until it is a good solution.

Think about how any human developer would approach an issue. For a lot of the 'moderately complex code bases', a developer new to it would also need a lot of pointing in the right direction, a lot of trying stuff out and then correcting themselves. Forget treating LLMs like one-shot magic solution givers, but instead as junior devs that you have to provide with all kinds of things to be successful.

> The differences can't be that massive given that the hype already made many of these promises well before these models were ever a thing.

I'm not talking about other people's incorrect promises _and_ I mentioned a number of things in which proper usage today is different from what people were doing before.

> Basically you are just adding to it with "You just need to use the latest model, anything before that is trash".

That's not what I said. Don't put words into my mouth. I said that the older models are trash in comparison, not that they are trash. The older models require more work in prompting to get decent results.

> Ignoring that the same was said just a few months prior when those models were cutting edge.

You are conveniently ignoring the other parts I mentioned to make my claim. Here: "In addition to that we've also seen that the way you prompt (amount of use of expert language), what context you provide through instructions, and tool use make a huge difference on the outcome."

This is too dismissive. There is a massive difference in outputted code quality between models. The recent Google Gemini 2.5 models have dethroned the Anthropic ones. OpenAI o3 is the only other one that is even worth considering; all the rest of the OpenAI models are trash in comparison.

In addition to that we've also seen that the way you prompt (amount of use of expert language), what context you provide through instructions, and tool use make a huge difference on the outcome.

At this point, if your coding experience with LLMs sucks I'd say there is an 80% chance that you're just doing it wrong.

Are unrealistic beauty/physical expectations for girls and women an 'unfair situation', a 'systemic issue'?

If you say yes, think about what expectations for men there are and whether those constitute a systemic issue. Hint: https://www.reddit.com/r/FemaleDatingStrategy/comments/ma8h0...

The best thing you can do is actually listen to the things the boys and men say about why they are depressed, feel disadvantaged, etc. instead of just dismissing them and saying they just have to learn how to deal with it. There really is quite a lot of truth in there to be found.

Same.

I am at about 70 wpm and I do semi-touch typing. I can type without looking at the keyboard 95% of the time (symbols etc. are tricky), but I don't use all 10 fingers (pinkies are pretty much unused) and do not rely on having my hands in the 'home' position.

Doing the 10 finger based home position approach almost immediately feels incredibly restricting. Some things like typing a C with my middle finger feel like I am doing something counter to my anatomy (when would you ever make such a movement naturally? let alone hundreds or thousand times a day?).

I wonder whether it is just a lack of getting used to it or whether people who do the full on touch typing a lot just fuck up their body regularly.

Is it? Or are 'legitimate' books just too often not concise and structured enough?

I do a lot of personal knowledge management and I use a shit ton of sections and lists in that. Books evolved from the art of telling stories, not from efficiently conveying knowledge. Perhaps we're just way too used for books etc. to an approach that is suboptimal. I know I personally despise news articles and blogs that start with "setting the scene" and are incredibly and needlessly verbose, using thousands of words to say what could be made clear in a single paragraph.

Viewed from another angle: Reading text is inherently serial in nature even though a lot of things are related to each other in a graph. A document with sections with bulleted lists is actually a way to represent a tree, which is closer to a fully unconstrained graph. I would argue that trees like that are much easier to parse than classically written texts.

There is irony here in that I only used some whitespace to add structure, but never used any bulleted lists in this comment.

[...]

I did generate an alternative with Google Gemini 2.5 Pro, but the formatting doesn't work here on HN. It was decent, though!

I read through a bit of it and it really wasn't all that bad. The only thing that I found to be really problematic were the made up experiences. Clearly hallucinations are still a big problem for LLMs, but if we manage to get rid of those a book like this can really be quite serviceable (a lot of human-written books are badly written so the bar isn't incredibly high, imho).

The creator should really tweak the prompt/process to include automatic review explicitly intended to remove hallucinations. It clearly is already the intent: "Future iterations of this experiment will include AI-powered fact-checking of the content."

I'm looking forward to what the improved version will look like.