LLM cannot reason about anything.
It can provide text that can be plausibly interpreted as reasoning by someone reading that text.
When human provides a plausible explanation then it means they either had someone else provide it to them or they actually understand the issue.
LLM cannot understand anything, it can only provide output based on the training data where similar input has likely to have produced similar output in the past.
Human can tell you they don't understand or don't know something but LLM is unlikely to have training that will produce that kind of output, it is more likely you will always get something that looks correct but it might not be.
LLM can automate a part of the process where human might take slightly but, ultimately, any output generated by LLM cannot be trusted and should be checked by human that understands the issue...and that is actually the hard part where humans will struggle so they won't actually do it.
When human is producing the output that human is performing the following actions:
-analysing the issue
-analysing the exiting process
-building the understanding of the existing process
-building the understanding of how issue affects the existing process
-producing the output to address the issue in the existing process
-checking the output as it is being produced
-updating the understanding of the existing process with lessons learned from the above
-checking the final product to ensure that it has solved the original issue and hasn't broken some other part of the system
LLM can help speed up one of those steps (producing the output) at the expense of slowing down the other parts (which were already slow) and reducing the understanding and reliability of the existing system which will make future iterations even slower.
LLM can be used to speed up the generation of examples but just like in the past you could not just copy the example from some random internet search result, you should not just copy the LLM output without understanding it...and that is the slow part where LLM might not help (and might actually make worse) for most people.
And when in the past you encountered comprehensive and well documented output you could assume human that put that amount of effort actually understood what they were doing and wouldn't have expended that much effort to generate garbage, you cannot make that same assumption now with LLMs.
I hate losing access to software just because it is "unmaintained".
If module is "endorsed" now, since it is included in current version, and there is no maintenance, so no changes made to it, why is it suddenly not good enough to "endorse" in the future?
No, security issues do not count as they don't magically appear, either they are in there now and debian is fine with distributing "insecure" code or they don't matter.
Debian is fine with shipping broken version of software for years as long as they consider it "stable" so why drop working "stable" software just because no one is making changes to it?
As a pedestrian I find cyclist are worse than cars for obstructing my path.
Riding on the footpath (illegal here) even with bike lane available right next to it, not respectig the traffic lights (mowing through pedestrians on crossings or blocking pedestrian crossings when stopped on red light), parking by blocking the footpath (must leave 1.5m of footpath unobstructed), riding the wrong way through traffic, flying down bike lanes (40kmh limit) and raging when anyone infringes their "rights" when they respect noone.
In my experience, I estimate that 20% of car drivers are a-holes, 50% or truck drivers and 80% of cyclists.
I would like for Linux to be able to replace Windows.
I run Linux on some of my computers with various levels of success.
But even with Windows 11 being as annoying as it is and Ubuntu/Mint/Cachy/Fedora/etc having some really good points they are not as easy to use as Windows.
Sure, web browsing is almost the same and simple home office tasks are close enough.
But all of the complaints that GP has mentioned are valid.
Windows file chooser is essentially small Windows Explorer and you can do almost everything that you can in the explorer while you are in file chooser mode. None of the Linux desktops have anything close.
HiDPI and multi monitor scaling on Linux has gotten better and it might approach what Windows had for the last 10 years but it is not 100% there yet.
Wayland is just a protocol with many incomplete and incompatible extensions that may or may not be implemented by your DE.
VNC is not even remotely close to RDP in features or performance. It just isn't.
I have used RDP over dial-up that was more responsive that VNC over LAN.
Not to mention sound, printer, disks, USB, etc all being available over one RDP connection.
Accessibility on Linux is a joke. On screen keyboard may work 80% of the time, screen reader might work 20% of the time. Sound might come out of random output or it might not. You may have to play with random settings, good luck with that if you are vision impaired.
One big reason Linux isn't there yet is people who just dismiss all of the above and go with "it works for me so it must be good for everyone."
Having seen LLMs so many time produce incoherent, nonsense, invalid answers to even simplest of questions I cannot agree with categorization of "thinking" or "intelligence" that applies to these models.
LLMs do not understand what they "know" or what they output. All they "know" is that based on training data this is most likely what they should output + some intentional randomization to make it seem more "human like".
This also makes it seem like they create new and previously unseen outputs but that could be achieved with simple dictionary and random number generator and no-one would call that thinking or intelligent as it is obvious that it isn't.
LLMs are better at obfuscating this fact by producing more sensible output than just random words.
LLMs can still be useful but they are a dead-end as far as "true" AI goes. They can and will get better but they will never be intelligent or think in the sense that most humans would agree those terms apply.
Some other form of hardware/software combination might get closer to AI or even achieve full AI and even sentience but that will not happen with LLMs and current hardware and software.
If the payload expands to something too large then it is easy to detect and ignore. Serve up thousands of 10kb or 100kb files that expand to 10s of MB with random garbage inside...possibly the same text but slightly modified. That will waste the time and CPU cycles and provide no value to them. Maybe also add a message you want to amplify so AI bots train on it.
We currently don't really know what intelligence is so we don't have a good definition of what to expect from "AI" but anyone who has used current "AI" for anything other than chat or search should recognize that "AI" is not "I" at all.
The "AI" does not "know" anything. It is really a fuzzy search on an "mp3" database (compressed with loss resulting in poor quality).
Based on that, everyone who is claiming current "AI" technology is any kind of intelligence has either fallen for the hype sold by the "AI" tech companies or is the "AI" tech company (or associated) and is trying to sell you their "AI" model subscription or getting you to invest in it.
UTF8 is a horrible design.
The only reason it was widely adopted was backwards compatibility with ASCII.
There are large number of invalid byte combinations that have to be discarded.
Parsing forward is complex even before taking invalid byte combinations in account and parsing backwards is even worse.
Compare that to UTF16 where parsing forward and backwards are simpler than UTF8 and if there is invalid surrogate combination, one can assume it is valid UCS2 char.
Runtime flexibility is not restricted to dynamically typed languages, it just happens to be less available in some of the popular statically typed languages.
Error handling, expressiveness, testing culture, meta-programming and gradual typing have nothing to do with static vs dynamic typing.
The main "advantage" of dynamically typed languages is that you can start writing code now and not thing about it too much. Then you discover all the problems at runtime...forever.
Statically typed languages force you to think about what you are doing in advance a lot more which can help you avoid some structural issues. Then when you do refactor computer helps you find all the places where you need to change things.
Dynamically typed languages force you to write more tests that are not required in statically typed languages and that might prompt you to write other tests but if also increases the chance you just give up when you start refactoring.
Finally, after some time has passed and few updates have been applied to the language and libraries, you may not have a working project anymore. With statically typed languages you can usually find and fix all the compile errors and have the fully working project again. With dynamically typed languages, you will never know until you explore every line of code, which will usually happen at runtime and on the client computer.
I don't know what I am doing wrong but nothing written in Python has ever worked for me.
I download the .py repo from from github or wherever and try to run it - errors.
I try to install missing libraries pip this and that - errors.
I battle fixing endless error with dependencies and when the .py finally runs - errors - wrong version of whatever library or wrong patch of this or that or the "production ready" .py does not work correctly on Windows or single file script uses excel library that has changed in incompatible ways 3 times in 2 years.
I Download all the files from the flashy looking web site and follow all the instructions to the letter - errors.
Python is anything but "robust".
It is the most fragile environment in the universe, worse than c, c++ and javascript put togeter, at least this is my experience with it.
I don't like to be seen as defending Microsoft, they definitely have their share of faults, but as far as business goes, I think Microsoft is the least likely company to screw you over as a (business) customer.
Microsoft has kept old software working pretty much unchanged for the last 20 years. I know, I still have software built on early Windows 95/NT4 that works fine on Windows 11...and with some registry tweaks Windows 11 will run on a computer from 2005 without too many issues (sure, 3rd party security software and js-heavy web pages will be slow but that is not directly MS fault).
Windows 10 EOL in 2025 is only for consumer level stuff, you can get Windows 10 support for enterprise for another 2 years at least and some versions even up to 2029, so again, if you are a business, you are taken care of (if you are "cheaping" you way with Windows Home and Pro in business then you kind of get what you pay for, I am sure you as a business don't give away free products/services for years on end). And you can keep using your Windows 10 after EOL, not like they lock you out, they just don't support you...just like you don't repair stuff for free after warranty end.
Compare that to any other tech company that churns through HW and SW much faster and much more severely where old HW and SW no longer works or cannot connect to the internet or use the latest browser so you cannot connect to the latest HTTPS servers. Even open source software breaks compatibilty with older versions much more oftern than Microsoft, but since that is "free" people just shrug it off.
They always had that option but somehow it was cheaper to ship there and back than to manufacture in US.
So either you get 2x the tariff increase in price or you manufacture locally for something that increases the price by more than 2x shipping.
Oh no, indeed.
>Can we all stop pretending that they don't abuse of their power and hold your deepest darkest secrets indefinitely? Even though most of us are law abiding citizens.
I don't anyone know who thinks powerful don't abuse their power. It is the nature of the beast.
And it seems none of us are law abiding citizens:
https://www.saponelaw.com/blog/2019/10/professor-says-that-e...
>Can we please start making open hardware without Apple/google backdoors and stop pretending our systems are "secure".
Few try...and either fail or languish in obscurity. You comment in itself is the proof that open hw cannot compete since you don't know of these open hw platforms and don't use them even tough you seem to advocate their creation here.
>Can we please write all software in Rust...
Rust only eliminates memory safety issues of C/C++. There are large number of languages, some decades older than Rust, that provide various aspects of Rust memory safety without imposing the same limits...and some are being used but people always flock to either new and flashy or the most widely used. Besides, Rust still provides ample foot guns and pushes reliance on 3rd party libraries which replaces memory safety issues with supply chain issues. Not to mention the the very poor ergonomics of the language that purposefully shies away from a lot of syntax sugar that makes writing and reading (understanding) code easier.
>Can we please use distributed systems to avoid censorship or holding our private information in the hands of the rich?
Even if you managed to persuade a lot of people to use these, some nodes will become popular/trusted and be targeted for censorship and propaganda and that will achieve the same result as the current model. Again, it is the nature of the beast.
What can be done? I don't know, probably nothing...things have to get to the point where most people are compelled to act because the alternative is death or worse, until such time there will just not be enough support for action to matter. Just how people are.
What is currently advertised as AI (LLMs) cannot replace all software developers.
It is a tool that can make software developers more productive so there will be less need for low level positions but there will still be a substantial need for senior developers.
LLMs, if tuned for software development, present an opportunity for a company, that can plan beyond the next couple of quarters, to produce software of unprecedented quality and with as yet unseen features and usability.
Of course, there will be companies which will use LLMs incorrectly and replace most developers (and other people) and create products that are even worse than what is currently available since they don't understand what LLMs are or how to utilise them correctly. Those companies will either realize and fix their mistakes or go bankrupt.
I have a really hard time understanding why people like 0 based indexes.
They are a relic of C style arrays that are based on and interchangeable with pointers which use offsets that are naturally 0 based.
Use in later languages gives us endless off-by-1 issues and rise to "for 0 to count/len/num - 1" or even better range syntax that is start inclusive BUT end exclusive.
It is a horrible cludge just to support 1970s language perfomace optimization.
Arrays should start and end at whatever start index is required, not at offset 0 of pointer to fist element of array.
Like everything in life, it depends...
For example:
Storage has 5 items that need to be processed.
5 items need to be split equaly between available processes.
There are currently 0 available processes so 5 / 0 = 0 items to be processed is more correct than either 5 or Nan or infinity.
"Fixable" in computer hardware has for many years meant that the computer can be disassembled without having to melt glue and that memory, network card, and disk can be replaced without having to replace the motherboard.
GPU and CPU are a bit special. In desktop system I would argue that GPU and CPU must be replaceable separately from the motherboard. In space constrained systems like laptops I can see the need to solder those two to the motherboard so when while not ideal it is tolerable. But disk and memory must be replaceable on their own or the computer is simply not repairable.
Replacing a screen, hinges and alike should be possible but I can see that parts may not be as readily available.
I have replaced a screen on my HP Zbook and it was just a matter of popping off the bezel, removing 4 screws and unplugging the connector, then doing the same in reverse with the new screen - 15 min job. That is repairable.
Why should all other companies and developers spend money to help $2T company make even more money when it was that company that broken all the existing software?
Apple users will through their money at Apple every opportnity they get but won't spending any money on new version of 3rd party software that Apple has broken with their changes.
I would abandon Apple if had any software released on their platform.
LLM can only provide statistically most likely diagnosis based on the training data.
If used by the experienced doctor LLM can be a valuable tool that saves time and maybe even increases accuracy in majority of cases.
The problem is that LLMs will be used to replace experienced doctors and will be used as 100% accurate tools.
This will result in experienced doctors becoming first rare and then non-existent and outcomes for patients will become increasingly unfavorable due to LLMs always producing a confident result even when it would be obviously wrong to an experienced doctor or even just a student.
There is something disturbing about your take on this:
1) People who did the work do not deserve to be compensated.
2) Advertising is more valuable than the product being advertised.
I am struggling to understand this mindset.
LLM can automate a part of the process where human might take slightly but, ultimately, any output generated by LLM cannot be trusted and should be checked by human that understands the issue...and that is actually the hard part where humans will struggle so they won't actually do it.
When human is producing the output that human is performing the following actions: -analysing the issue -analysing the exiting process -building the understanding of the existing process -building the understanding of how issue affects the existing process -producing the output to address the issue in the existing process -checking the output as it is being produced -updating the understanding of the existing process with lessons learned from the above -checking the final product to ensure that it has solved the original issue and hasn't broken some other part of the system
LLM can help speed up one of those steps (producing the output) at the expense of slowing down the other parts (which were already slow) and reducing the understanding and reliability of the existing system which will make future iterations even slower.
LLM can be used to speed up the generation of examples but just like in the past you could not just copy the example from some random internet search result, you should not just copy the LLM output without understanding it...and that is the slow part where LLM might not help (and might actually make worse) for most people.
And when in the past you encountered comprehensive and well documented output you could assume human that put that amount of effort actually understood what they were doing and wouldn't have expended that much effort to generate garbage, you cannot make that same assumption now with LLMs.