Let's Talk about ChatGPT with Code Interpreter and Microsoft Copilot
oneusefulthing.org
oneusefulthing.org
I'm left wondering what the role of a software eng is and all I can come up with is a glorified quality analyst. Nothing wrong with that, but it's just such a transformation, and so sudden. I'm excited, scared, and exhausted all at the same time!
Unless, of course, you want to be a software engineer.
If all there is to my career is checking generated code for correctness, then there is nothing of value in my career anymore.
That's not how it will be, though. At worst, there will still be niches I can fit in.
> Unless, of course, you want to be a software engineer.
It’s time to adapt to a changing world.
So we're all to become systems integrators? I'm genuinely happy that excites you. Personally, I find the prospect depressing.
> It’s time to adapt to a changing world.
How do you adapt to no longer being able to do what you love to do? Saying "it's time to adapt" doesn't address the fundamental issue here at all. Obviously, we have to adapt. The question is how to do that and, if happiness is no longer on the table, at least be able to maintain some amount of career satisfaction.
If I can't write software, then my career as a dev is over, no?
Humans gotta realize that we are all replaceable. What happens to the least of us, happens to us all.
Whatever we do about this AI stuff? We should do it for everything else, too.
https://www.nbcnews.com/science/environment/west-virginia-co...
Change is hard, but it is possible, and one thing humans are good at that machines still can't do is to make our own meaning.
Wishing you the very best.
Nothing will make me happier than to be wrong about what I see coming.
I doubt there were that many who actually enjoyed digging coal as opposed to just having a relatively well paying job
Forget “love” how are we supposed to adapt when jobs seem to be increasingly specialized requiring ridiculous education costs and companies don’t want to train people anymore.
I understand that some engineers/developers struggle with this change, but it also seems to be a personal take on ground breaking changes which are shaking up this career path; which are positive for some, and negative for others. Maybe we are on two different part of the spectrum, because I can't wait to have my job reduced to prompting and building even bigger things. IF it was not that way, I would have been close to a career change. No doubt, these changes will introduce new engineering challenges, which will be equally as exciting and in need of an engineering mindset as the previous paradigms have been.
This isn't an issue of struggling with adapting to change. If it were just a matter of doing my job in a different way, that would be totally fine. This is an issue of seeing the sort of work that I enjoy -- the entire thing that drew me to this career -- evaporate completely.
But this all makes me sound more upset than I actually am. I'm very troubled, but I also only have a decade or two left in my career, so I think it's likely that I'll be able to find niche positions where I can keep doing what I love to do.
I do worry about younger devs who are in the business for similar reasons as me, though.
In addition to data analysis stuff, I've also used it for running comparative benchmarks: https://simonwillison.net/2023/Apr/12/code-interpreter/
You can upload all sorts of weird things to it. I've uploaded .whl wheel files from PyPI to give it extra Python dependencies.
I also uploaded a Deno (and a Lua) interpreter and that gave it the ability to write and execute code in JavaScript and Lua!
https://til.simonwillison.net/llms/code-interpreter-expansio...
Instead of having an AI model output some kind of "black-box conclusion" on a data set / question, it can output code that we can inspect, improve, and learn from. Using LLMs in this way still keeps us as users "in control" - and I think it's a promising path for responsible AI.
I've done some experiments[1] adding ChatGPT-like functionality to my open source Typescript Notebook environment[2] back in december, and hope to revisit this soon :)
[1] https://twitter.com/YousefED/status/1599805936280907776 [2] https://www.typecell.org/
In a weird way, it's actually still aligned with their "think different" motto: when everyone is thinking about getting on the AI bandwagon, think different and avoid doing that!
[0]: Which is fine—the world needs boring companies as much as pioneers who break things.
Also, Apple should first fix Siri, or get rid of it for good. It's a joke at this point.
I feel like any company which has chatbots as a "core" part of their systems (like Siri is often advertised to be) would be looking very heavily into generative AI. It makes way too much sense and would clearly make Siri way more useful. Imagine if Siri was current ChatGPT with plugins for interacting with the OS -- this immediately solves basically all the complaints about Siri. Plus Apple has efficient local AI acceleration already, which could make it even better.
It feels so obvious it'd be weird if they weren't trying to make a better Siri with gen AI! I have a feeling we'll hear about it either at WWDC or the iPhone event in the fall.
It's also not like AI tools are why people buy Apple products. So "waiting" probably doesn't cost them much money -- it doesn't impact their core hardware and service revenue. It's "just" a value add for now.
For acquisition yeah I was thinking along the lines of Siri.
Who would've thought that in just four months, GPT-4 will completely transform people's perception of AI progress timeline and impact.
I have no idea what Apple will do with LLM's. But Apple is already leveraging ML in things like built-in local dictation and OCR, and we can probably expect that it will leverage things like LLM's at the OS level (iOS/macOS) rather than focusing on their iWork suite. (Honestly at this point I don't understand Apple's strategic purpose with iWork, or even Final Cut Pro.)
In April 2023, Apple has a 30% market share of smartphones worldwide [1]. And in the first 3 months of 2023, Apple accounted for 50% of global smartphone revenue... and 80 percent of the industry's profits [2]. These is smartphone revenue, not services revenue. (Apple makes money from the App Store too but that's separate.)
80% of industry profit from 30% market share is certainly not a commodity. Cheap Android phones are a commodity. iPhones are the polar opposite.
[1] https://www.oberlo.com/statistics/smartphone-market-share#:~....
[2] https://www.statista.com/chart/29925/apples-share-of-the-glo....
Also frankly, productionalizing LLMs is very different from making research strides on them. Even inside Google researchers are realizing that a bulk of the improvements are now coming from the OSS community.
Apple will implement these technologies when it makes sense to do so.
Why would Apple even pursue LLMs? They are building hardware: computers, phones, screens, accessories. In a sense, that’s what you said. Just phrasing a question to your thought.
You can see in the chat transcript [2] that I had GPT-4 tell me how to download census data, suggest some hypotheses to test, test one, summarize the results and plot a graph. As we went along, I had it write the code for all that as a python script in my local git repo.
I presume anything ChatGPT generates belongs to the user who asked for the code to be generated. Is there any clause in the EULA that says this is the case? Or is code generated by ChatGPT automatically BSD-licensed? Or can ChatGPT claim ownership or joint-ownership of code generated using their tools?
Another question is the code it was trained on. Presumably all of it was open source. BSD-licensed code typically requires attribution. GPL code requires anything copied to remain GPL. If the GPT is reproducing small stanzas of code from memory it probably doesn't matter. If GPT reproduces larger blocks of code from stuff that it was trained on, there is a possibility of failing to comply with copyright.
Machine generated works cannot be copyrighted, only human-created works. The part here that has yet to be determined is whether or not AI output is considered "machine generated". An argument could be made that writing a prompt is sufficient control to consider the output human-made for the purposes of copyright. If that's the case, then copyright will go to the human who wrote the prompt (or their employer).
This will, at some point, have to be decided in court. Right now, the only answer is "nobody knows".
Pushing a button is sufficient to own copyright, in theory.
Last I checked , that’s not the case. Otherwise the entire proprietary software universe would collapse (not that having that outcome isn’t desirable per se )
I'm a little confused by the responses I'm getting to my comment. People seem to be thinking that I'm saying that copyright cannot apply to AI produced output. I said no such thing.
What I am saying is that this is not a legally settled matter. It will certainly end up in a courtroom, and will then become a settled matter. That day isn't here yet.
(I'm not saying that's the right call from an ethical point of view, just that I think that's how courts will interpret the law.)