231–240 of 742 posts
If you want to destroy open source completely, the more models the better. Microsoft's co-opting and infiltration of OSS projects will serve as a textbook example of eliminating competition in MBA programs. And people still support it by uploading to GitHub.
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I use both Claude and ChatGPT/GPT-4o a lot. Claude, the model, definitely is 'better' than GPT-4o. But OpenAI provides a much more capable app in ChatGPT and an easier development platform. I would absolutely choose to use Claude as my model with ChatGPT if that happened (yes, I know it won't). ChatGPT as an app is just so far ahead: code interpreter, web search/fetch, fluid voice interaction, Custom GPTs, image gene…
Are there any good 3rd-party native frontend apps for Claude (on MacOS)? I mean something like ChatGPTs app, not an editor. I guess one option would be to just run Claude iPad app on MacOS.
I use cursor and its tab completion; while what it can do is mind blowing, in practice I’m not noticing a productivity boost. I find that ai can help significantly with doing plumbing, but it has no problems with connecting the pipes wrong. I need to double and triple check the updated code - or fix the resulting errors when I don’t do that. So: boilerplate and outer app layers, yes; architecture and core libraries,…
Just sanity checking that the output and “piping” is correct.
My productivity (in frontend work at least) is significantly higher than before.
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The speed with which AI models are improving blows my mind. Humans quickly normalize technological progress, but it's staggering to reflect on our progress over just these two years .
I wonder how long people will still protest in these threads that "It doesn't know anything! It's just an autocomplete parrot!" Because.. yea, it is. However.. it keeps expanding, it keeps getting more useful. Yea people and especially companies are using it for things which it has no business being involved in.. and despite that it keeps growing, it keeps progressing. I do find the "stochastic parrot" comments slowl…
If these tools boost tue productivity where is the output spike of all the companies, the spike in revenue and profits?
How often do we lose the benefit auto text generation to the loop of That’s wrong Oh yes of course, here is the correct version Nope, still wrong Prompt editing?
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Conversely I feel that the experience of searching has been degraded by a lot since 2016/17. My these is that, at this time, online spam increased by an order of magnitude
I think it was the switch from desktop search traffic being dominant to mobile traffic being dominant, that switch happened around the end of 2016. Google used to prioritise big comprehensive articles on subjects for desktop users but mobile users just wanted quick answers, so that's what google prioritised as they became the biggest users. But also, per your point, I think those smaller simpler less comprehensive po…
I use cursor and its tab completion; while what it can do is mind blowing, in practice I’m not noticing a productivity boost. I find that ai can help significantly with doing plumbing, but it has no problems with connecting the pipes wrong. I need to double and triple check the updated code - or fix the resulting errors when I don’t do that. So: boilerplate and outer app layers, yes; architecture and core libraries,…
I'd highly recommend reading through Aider's docs[0], because I think it's relevant for any AI tool you use. A lot of people harp on prompting, and while a good prompt is important I often see developers making other mistakes like not providing context that's good, correct, or even too much[1].
When I find models are going on the wrong path with something, or "connecting the pipes wrong", I often add code comments that provide additional clarity. Not only does this help future me/devs, but the more I steer AI towards correct results, the fewer problems models seem to have going forward.
Everybody seems to be having wildly different experiences using AI for coding assistance, but I've personally found it to be a big productivity boost.
[0] https://aider.chat/docs/usage/tips.html
[1] https://aider.chat/docs/troubleshooting/edit-errors.html#red...
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Claude is a product name, OpenAI is a company name. You really think Claude is better than ChatGPT?
Asking Americans to read a French name that is a homonym for “clod” may not be the best mass market decision.
I use cursor and its tab completion; while what it can do is mind blowing, in practice I’m not noticing a productivity boost. I find that ai can help significantly with doing plumbing, but it has no problems with connecting the pipes wrong. I need to double and triple check the updated code - or fix the resulting errors when I don’t do that. So: boilerplate and outer app layers, yes; architecture and core libraries,…
> in practice I’m not noticing a productivity boost. How can this be possible if you literally admit its tab completion is mindblowing? Isn't really good tab completion good enough for at least a 5% producitvity boost? 10%? 20%? Select line of code, prompt it to refactor, verify they are good, accept the changes
What about it makes it impossible? I’m impressed by what AI assistants can do - and in practice it doesn’t help me personally.
> Select line of code, prompt it to refactor, verify they are good, accept the changes.
It’s the “verify” part that I find tricky. Do it too fast and you spend more time debugging than you originally gained. Do it too slow and you don’t gain much time.
There is a whole category of bugs that I’m unlikely to write myself but I’m likely to overlook when reading code. Mixing up variable types, mixing up variables with similar names, misusing functions I’m unfamiliar with and more.
I use cursor and its tab completion; while what it can do is mind blowing, in practice I’m not noticing a productivity boost. I find that ai can help significantly with doing plumbing, but it has no problems with connecting the pipes wrong. I need to double and triple check the updated code - or fix the resulting errors when I don’t do that. So: boilerplate and outer app layers, yes; architecture and core libraries,…
Time will tell. As a GitHub Copilot user, I still review the code. SpaceX's advancements are impressive, from rocket blow up to successfully catching the Starship booster. Who knows what AI will be capable of in 5-10 years? Perhaps it will revolutionize code assistance or even replace developers
That felt like it was LLM generated since that doesn't have anything to do with the subject being discussed. Not only it's on a different industry but it's a completely different set of problems. We know what's involved in catching a rocket. It's a massive engineering challenge yes, but we all know it can be done(whether or not it makes sense or is economically viable are different issues).
Even going to the Moon – which was a massive project and took massive focus from an entire country to do – was a matter of developing the equipment, procedures, calculations (and yes, some software). We knew back then it could be done, and roughly how.
Artificial intelligence? We don't know enough about "intelligence". There isn't even a target to reach right now. If we said "resources aren't a problem, let's build AI", there isn't a single person on this planet that can tell you how to build such an AI or even which technologies need to be developed.
More to the point, current LLMs are able to probabilistically generate data based on prompts. That's pretty much it. They don't "know" anything about what they are generating, they can't reason about it. In order for "AI" to replace developers entirely, we need other big advancements in the field, which may or may not come.