dinfinity

Neither of those are based in intelligence, but rather in dexterity, agility and sensing capabilities. Try again, and this time please read the question carefully and answer in good faith rather than trying to (unsuccessfully) look for a loophole.

> If you're in tune with animals and spend time around a parrot, it's obvious there is a lot going on in their minds.

Not saying there isn't and somewhat offtopic, but if you apply this to LLMs those are much, much 'smarter' than all the animals people like to call intelligent (or something similar). If you disagree, please tell me for which task requiring intelligence you'd rather have an animal's wit than that of an LLM.

I really do feel we should be taking the current state of affairs as a starting point to recalibrate what counts as smart or worth 'protecting', whether it's our beloved animal friends or something inorganic. Simultaneously believing "birds are super smart" and "LLMs are just stochastic parrots" seems absurd.

Keychron keyboards are absolutely amazing. And very affordable for what they are.

You did not engage with my main arguments. You should still do so.

1. Redundancy: "The code is what it does. The comments should contain what it's supposed to do. [...] You don't have to know anything else to see that something is wrong here." and specifically the concrete trivial (but effective) example.

2. "My take on developers arguing for self-documenting code is that they are undisciplined or do not use their tools well. The arguments against copious inline comments are "but people don't update them" and "I can see less of the code"."

> Respectfully, if someone wrote code like this, I wouldn't want to work with them. I mean next step is "I copy paste code [...]

This is an nonsensical slippery slope fallacy. In no way does that behavior follow from placing many comments in code. It also says nothing about the clearly demonstrated value of redundancy.

> I have been navigating code for 20 years and in good codebases, comments are rare and describe something "surprising".

Your definition of good here is circular. No argument on why they are good codebases. Did you measure how easy they were to maintain? How easy it was to onboard new developers? How many bugs it contained? Note also that correlation != causation: it might very well be that the good codebases you encountered were solo-projects by highly capable motivated developers and the comment-rich ones were complicated multi-developer projects with lots of developer churn.

> My problem with "literate programming" [...] is that I find it hard to trust developers who genuinely cannot understand unsurprising code without comments.

This is gatekeeping code by making it less understandable and essentially an admission that code with comments is easier to understand. I see the logic of this, but it is solving a problem in the wrong place. Developer competence should not be ascertained by intentionally making the code worse.

The code is what it does. The comments should contain what it's supposed to do.

Even if you give them equal roles, self-documenting code versus commented code is like having data on one disk versus having data in a RAID array.

Remember: Redundancy is a feature. Mismatches are information. Consider this:

// Calculate the sum of one and one

sum = 1 + 2;

You don't have to know anything else to see that something is wrong here. It could be that the comment is outdated, which has no direct effects and is easily solved. It could be that this is a bug in the code. In any case it is information and a great starting point for looking into a possible problem (with a simple git blame). Again, without needing any context, knowledge of the project or external documentation.

My take on developers arguing for self-documenting code is that they are undisciplined or do not use their tools well. The arguments against copious inline comments are "but people don't update them" and "I can see less of the code".

"Nearly odorless"?

I call bullshit.

> I'm not saying "let the producers run free". Intervening there is fine as long as we keep front of mind and mouth that people need to take their responsibility and that we need to do everything to help them to do so.

Exactly. It's not that the producers or distributors (of food, content, etc.) are not malicious/amoral/evil/greedy. It's that the real solution lies in fixing the vulnerabilities in the consumers.

You don't say to a heroin addict that they wouldn't have any problems if those pesky heroin dealers didn't make heroin so damn addictive. You realize that it's gonna take internal change (mental/cultural/social overrides to the biological weaknesses) in that person to reliably fix it (and ensure they don't shift to some other addiction).

I'm not saying "let the producers run free". Intervening there is fine as long as we keep front of mind and mouth that people need to take their responsibility and that we need to do everything to help them to do so.

> This is where algorithmic, ad-fueled social media leads a republic.

Only if we keep repeating things like this.

People have agency and there are many people who are not led by or actively abusing social media. You don't tell a heroin addict it's not their fault, that the presence and malice of dealers made their fate inevitable.

> It is always the eternal tomorrow with AI.

ChatGPT is only 3 years old. Having LLMs create grand novel things and synthesize knowledge autonomously is still very rare.

I would argue that 2025 has been the year in which the entire world has been starting to make that happen. Many devs now have workflows where small novel things are created by LLMs. Google, OpenAI and the other large AI shops have been working on LLM-based AI researchers that synthesize knowledge this year.

Your phrasing seems overly pessimistic and premature.

That GP's comment is an advertisement for a subscription based closed source application that gets access to your credentials.

To be fair, most vending machine operators do not allow suggestions from customers on what products to stock, let alone extensive ongoing and intentional adversarial psychological manipulation and deception.

If it had just made stocking decisions autonomously and based changes in strategy on what products were bought most, it wouldn't have any of the issues reported.

> But the real issue is that price of the panels themselves is already only about 35% of the total installation cost of utility-scale PV. This means that even if the panels were free, it would only reduce the cost by a factor of 1.5.

1. Do the other costs scale with the number of panels? Because if the sites are 5 times the scale of the current ones I would imagine there are considerable scale based cost efficiencies, both within projects and across projects (through standardization and commoditization).

2. Vertically mounted bifacial PV already greatly smoothes the power production curve throughout the day, improving profitability. Lower cost panels make the downside of requiring more panels in such a setup almost non-existent. Additionally, they reduce maintenance/cleaning costs by being mounted vertically.

3. Battery/energy storage (which further improve profitability) costs are dropping and can drop further.

Also, please address the matter of using the overprovisioned power in summer. Possible projects are underground thermal storage ("Pit Thermal Energy Storage", only works in places where heating is required in winter), desalination, producing ammonia for fertilizer, and producing jet fuel.

Did you use AI to help you understand the code and what it was doing (incorrectly)?

> 5x to 10x overprovisioning would turn solar from one of the cheaper into the by far most expensive power generation method out there.

This is trivially false if the cost of solar generation (and battery storage) further drops by 5x to 10x.

Additionally that implies the overprovisioned power is worthless in the summer, which does not have to be the case. It might make certain processes viable due to very low cost of energy during those months. Not trivial as those industries would have to leave the equipment using the power unused during winter months, but the economics could still work for certain cases.

Some of the cases might even specifically be those that store energy for use in winter (although then we're not looking at the 'pure' overprovisioning solution anymore).

> My main point is that that distance x is going to rapidly get towards just a few miles away from point of use very shortly.

That seems physically unlikely to me. Sure, burying and maintaining cables costs money, but other than that transferring energy in a very fundamental and solid state way is going to be much easier than packaging it up and transporting it with heavy machinery.

This is definitely a case where your argument only works if it is supported by the actual calculation.

The anti-duck-curve is actually really, really pronounced for east-west mounted bifacial panels.

The panels still don't generate any electricity at night of course, but other than that the output is an almost perfect inverse of the conventional equator-facing angled mounted panel output.

Just search for "bifacial solar panels graph".

1. Microsoft is not a "dotcom startup". We live in a different, much more consolidated tech world of companies that either balloon to become behemoths or are bought by existing behemoths.

2. Power and data centers can be used for other things than AI.

3. They might turn out to be wrong and not need the deal/power. For companies sitting on a shitload of cash that would be an inconvenience whereas not investing and then later having to beg for electricity amounts to losing the race.

Yeah, if supporting fascism is okay, a little bit of copyright infringement is definitely okay.

Yes. Yes, it is a tragic event. Apart from it being simply morally utterly reprehensible, it is an extremely primitive and counter-productive way to fight against ideas and the messengers of those ideas.

Again, morally reprehensible and it doesn't fucking work. It only shows 'the other side is just as bad/worse', turns the messenger into a martyr, and galvanizes support.

Tip for enrolling in the Extended Security Updates for Win10:

https://github.com/builtbybel/Flyoobe/releases

> What’s new in Flyoobe 1.7.284

> This update is especially important for everyone still on Windows 10 who plans to stay there and take advantage of the Extended Security Updates (ESU) program.

Also in 1.10 stable, of course.

The obvious solution is going triple monitor:

One 32" 3840x2160 landscape and two 25" 2560x1440 portrait monitors is perfect for me.

The world is indeed not static. That it hasn't happened yet doesn't mean it won't.

Predictions about self driving were off, but far from "comically wrong". Waymo's operations are proof of that.

And to conclude things based on the state of the replacement of programmers after only 2-3 years of ChatGPT being a thing is folly.

The reality is that AI has far fewer limitations and legacy cruft than humans to deal with. Don't get me wrong, I like humans, but our performance is very close to the peak of what it could ever be. That of AI not so much. Remember that AI has been evolving for less than 100 years and it is already where it is today. That took us/biology orders of magnitude more time.

The only real question is how fast it will replace (which) human labor.

Gemini 2.5 Pro is also pretty good, if you need a fallback.

I think the key insight is that AI is (undoubtedly going to be) better at analysis and diagnosis than radiologists, but isn't yet widely deployed because:

1. The medical world doesn't accept new technologies easily. Humans get a much higher pass on bad performance than technology and especially than new technology. Things need to be extensively tested and certified, so adoption is slow.

2. AI is legally very different than a radiologist. The liability structure is completely different, which matters a lot in an environment that deals with life or death decisions.

3. Image analysis is not language analysis and generation. This specific machine learning part is not the bit of machine learning that has advanced enormously in the past two years. General knowledge of the world doesn't help that much when the task is to look at pixels and determine whether it's cancer or not. Now this can be improved by integrating the image analysis with all the other possibly relevant information (case history etc.) and diagnosing the case via that route.

If you look at his facial movements in the video it looks as if he is pretty actively using his facial muscles, 'trying' to speak while moving as little as possible (which would cause the clearest signals to be emitted).

If that is what is happening, to me it feels like harder work than just speaking (similar to how singing softly but accurately can be very hard work). It would still be pretty cool, but only practical in use cases where you have to be silent and only for short periods of usage.

My watch history has been off for almost a decade now.

They may weasel you into activating it via some other route that states in the fine print that they need to activate your watch history to provide [random almost unrelated feature].

Although I agree with your general message here, to be fair: GP has a very clear specification, namely an exact duplicate of an existing product. That means that as long as the end product functions identically to the original, it is completely successful.

This does require facilitating the implementer to have full access to use the original product.

Only if you forget that money is supposed to function as a lubricant for satisfying needs and think that it is somehow a good reflection of someone or something's worth to society.

Reducing accumulation of money (by means of for instance a wealth tax) is incredibly important to keep the economy as a whole going and to maximize the needs satisfied, but if you only think in terms of "but poor people don't deserve free money!", you miss this point and say dumb things like "a wealth tax is deeply immoral".

It's not terrible, but I definitely wouldn't call it 'huge'. The learned motions are very oldschool in that the performed actions aren't particularly smooth coordinated movements along different degrees of freedom.

The Google robot applying a timing belt presented earlier this year looks much more natural, imho: https://www.youtube.com/watch?v=2AAFiuEP7iE (albeit still pretty robotic)