I did a similar thing but with backend-heavy code, and I agree with this assessment:
> In particular, I asked ChatGPT to write a function by knowing precisely how I would have implemented it. This is crucial since without knowing the expected result and what every line does, I might end up with a wrong implementation.
In my eyes, it makes the whole idea of AI coding moot. If I need to explain every step in detail - and it does not "understand" what it's doing; I can virtually the statistical trial-and-error behind its action - then what's the point? I might as well write it all myself and be a bit more sure the code ends up how I like it.
Oh, that's easy: "founder mode" means the founder is hyperfocused (or in the oldspeak, obsessed) on his work (with his company) and optimizes (micromanages) everything. We know that already. Perfection demands micromanagement. Steve Jobs was actually doing that - reaching down the ranks and directly helping (molesting) people doing some piece of a larger product he particularly cared about.
It also often causes (or is caused by) eccentric behavior (or mental issues) - but it's been done since forever, and when it's successful, we call it "visionary." When it's not, we call it "toxic."
It's curious to see how times have changed. Soft-updates are indeed a very clever solution to the problem of file system consistency in the face of possible failures like OS crashes or power outages.
While journaling "simply" writes a journal of FS ops to a continuous area of the drive (especially important for mechanical drives) which is fsynced faster than random writes across platters, Soft-updates opts to be really clever with the way FS ops ordered, so that what's actually on the drive is always consistent, even with decent amount of write caching. It doesn't guard file content, though, just the file system itself.
Soft-updates is what enabled the BSD's to support short-lived files never touching the physical drive. You could create a file, write to it, read it, close and delete it, and if this was done in a reasonably short amount of time, no writes whatsoever got to the actual hardware. It was wonderful with software which used to generate a lot of temp files, like building C software.
OTOH, if a write got trough to the hard drive, Soft-updates guaranteed that file system structures get written in a way so that if an OS crash or a power failure happened at any single time, the only downside could be some unreferenced blocks, which could be garbage collected later; assuming hardware doesn't lie about fsync, of course...
I think ext4 supports this kind of short-lived-files-never-touch-the-drive caching.
- Row-level anything introduces write alignment and fsync alignment problems; pages are easier to align than arbitrary-sized rows
- PostgreSQL is very conservative (maybe extremely) conservative about data safety (mostly achieved via fsync-ing at the right times), and that propagates through the IO stack, including SSD firmware, to cause slowdowns
- MVCC is very nice for concurrent access - the Oriole doc doesn't say with what concurrency are the graphs achieved
- The title of the Oriole doc and its intro text center about solving VACUUM, which is of course a good goal, but I don't think they show that the "square wave" graphs they achieve for PostgreSQL are really in majority caused by VACUUM. Other benchmarks, like Percona's (https://www.percona.com/blog/evaluating-checkpointing-in-pos...) don't yield this very distinctive square wave pattern.
I'm sure the authors are aware of these issues, so maybe they will write an overview of how they approached them.
Neat but... Someone will make a crummier version of this in a language which doesn't feature parts looking like Unicode white noise and the original authors will be frustrated why the crummier vetsion took off and their project didn't.
Not every idea deserves to have an esoteric language attached to it to work.
This has been known and ocassionally touted for AGES. I've attempted to start a couple of such projects and have been following the progress of other projects with similar ideas.
There has been near ZERO interest for them, because there's no currently viable business case for such projects, except "let the government pay for it." Data mining isn't THAT useful if there's no data in there - who would force entities like companies, universities or the SEC to push the data into the blockchain?
I'd be very happy if could find funding for https://github.com/WOTvision/wot1 and I can see a business case for it as a potential platform for legal, paid distribution of news between creators/reporters and distributors like news portals. But even so, no takers.
This is a beautiful example of the biggest current problem with DAOs and all (and I do mean ALL) crypto projects which aim to interface with the real world (i.e. all projects not doing with purely abstract stuff like DeFi-like tokens, and closed systems like "metaverses"): THEY CAN'T.
They really cannot interface with the Real World, without leaking real-world problems into the "perfect" smart contract-driven crypto systems. They can't interface with the real-world financial systems (with stablecoins) and expect it to be always stable (see USDC), they can't interface with people doing real-world chores/tasks and have it reflected in blockchain brownie points aka tokens (like socially-useful DAOs like the one in the article), they can't interface with logistics where people and machines do actual work and fail unpredictable (like blockchain tracking of the supply chain), they can't authenticate artwork purely on blockchain (without paying actual people to guard the artwork), etc.
They just can't. All projects claiming they can are pure scams (of course, I'd be very happy to be proven wrong).
The nearest we can get to having perfect digital systems like cyptoanarhysts and cryptobros (sometimes there isn't any difference) advocate is to give up on the physical world and actually move everything into the metaverse where it doesn't depend on real world messyness, but then a) people will still find ways to mess things up and b) this Matrix-like system still needs electricity.
Just... embrace the messiness. You can't really escape it. Crypto is not special. Blockchains are useful tools, but so far, systems based on them they have not been proven to be strictily better than real-world messyness.
The best use cases for blockchains are those which don't really earn a lot of money for the operators, such as tracking publically visible official data - like university degrees, corporate tax returns and financial statements, fighting fake news, etc. - so they are avoided like the plague.
Yeah, it sucks and the teams has acquired the reputation of sellouts, but in practical terms, does it really matter?
It looks like there's a new team with equally good or better models announced on HN every few days.
OpenAI looks like they've ingnited the field like no-one before, then did a smart move of selling to a company which has a lot of money but doesn't always know what to do with acquisitions, while at the same time that sale didn't hinder actual open development (by other teams) one iota.
Heh... (of course) it still needs to be tuned for some particular mindset or personal view. I've asked Marcus Aurelius' book "What is man?" expecting to get
"A little breath, a little flesh, and reason to rule it all- that is myself"
but got
"Consider that all men are actually made up of the same basic components—body and soul, their properties and parts. And so, if you look at the whole, all men are one..."
Technically correct, the best kind of correct.
Also, if it directly quotes the book, is it really ChatGPT?
Isn't the term "epigenetic" about non-DNA information, like in mitochondria etc, i.e. not something recoverable by just scanning DNA more precisely? If so, it doesn't seem reversable?
It depends mostly on the year of birth of the beholder.
I imagine in a couple of decades that "built-in features" of a programming environment will include Bayesian inference, GPT-like frameworks and graph databases, just as now Python, Ruby, Go, etc. include zlib by default, and Python even includes SQLite by default.
It seems like operations with the format would be a bit faster if the pre-compression data would just be a framebuffer dump, instead of prefixing each row with a 1-byte "filter ID", possibly breaking data alignment.
> In particular, I asked ChatGPT to write a function by knowing precisely how I would have implemented it. This is crucial since without knowing the expected result and what every line does, I might end up with a wrong implementation.
In my eyes, it makes the whole idea of AI coding moot. If I need to explain every step in detail - and it does not "understand" what it's doing; I can virtually the statistical trial-and-error behind its action - then what's the point? I might as well write it all myself and be a bit more sure the code ends up how I like it.
link: https://www.linkedin.com/feed/update/urn:li:activity:7289241...