If you do end up getting a used Apple device I recommend making sure that it has the newer keyboard style that the current models have (I think it switched in 2018). The old keyboard was not fun to use.
Working with various data, ML, and researcher-type engineers there's a bit benefit to using Python. Especially if you want to be at the forefront of what's being built.
I've been building with Python FastAPI and a React/Nextjs app. I've gone back and forth on whether we should have used Django, but we've been full steam ahead with what we have.
If I wasn't building in the AI space I think I probably would have used Node <-> React with tRPC to make the typed full stack monorepo experience seamless.
Oh and Postgres - I'm irrationally loyal to Postgres
Based on nothing but a guess, my bet is that it's probably roughly breakeven
Though I'm curious how they're not charging any subscription given that the device will have ongoing costs to run the models. That feels like it could hemorrhage money – though if users are actively using it I guess it'd be a good problem to have
A bit of a different take, but given the amount of experience you have, I wouldn't put as much weight on using a CV at all.
With an updated LinkedIn you can reach out to past bosses, coworkers, and friends for introductions to other people in industry (whether they're hiring or not) – and follow that chain until you find something you're interested in.
It feels like it's sort of it's own thing. LLMs are really good at morphing or fuzzy finding.
An interesting example – I had a project where I needed to parse out addresses and dates in a document. However, the address and date formats were not standardized across documents. Utilizing LLMs was way easier then trying to regex or pattern match across the text.
But if you're trying to take a text document and break it down into some sort of a structured output, the outcome using LLMs will be much more variable.
Can you elaborate on what you mean by "really complex solution"? It is well-written/designed, but over-engineered? Or is it poorly done and subsequently hard to read + maintain? Or is it moreso an issue of documentation?
Also regarding CRUD apps – I actually was able to automate code generation of most of my CRUD pretty easily using cursor. I hand wrote a couple of them and now I just create the new file and prompt it referencing the Model and one of the other CRUD files as an example.
I used to use Github Copilot, but I find Cursor (https://cursor.sh/) to be even better.
You can add an OpenAI API Key and it'll use the GPT-4 API. It indexes your code for you and it'll crawl documentation for you if you give it the link. Then you can reference specific files or documentation with "@". There are also some really intuitive hot keys.
> Is it sufficient to be skilled in one programming language, such as Python, and implementing a software renderer or ray tracer, your own neural network, your own HTTPS server, your own OS, your own memory allocator, your own interpreter, your own virtual machine...?
May be misunderstanding here, but if I was implementing my own OS I probably wouldn't be using Python. Different problems warrant different solutions – by a "general problem solver" I mean that you think about the coding language as a tool to solve a problem. Similar to how you might think of S3 or ECS as a tool.
That you're thinking of the problem in the business context rather than purely the technical context.
GPT-4 has fully altered my dev workflow. I don't think I could move away from it unless there was a clear, equivalent, alternative.
Not only on the OpenAI UI, but also via the Cursor IDE which I actively use with an OpenAI API Key.
Even if you don't use the OpenAI UI you'll likely end up using the produce via other products. Github Copilot, Arc Browser, Duolingo – likely more in the future – all use GPT under the hood.
Not exactly in a DAW, but I found Syntorial to be incredibly helpful. Teaches you a lot of jargon around sound manipulation and how to reproduce a desired sound. It'll make you way more comfortable navigating a DAW later.
I've been thinking about this recently regarding photos – Would be sad to lose a life's worth of photos just because someone can't get into your phone.
In a similar, but different vein, I've recently found interesting to think about how all the photos of yourself tend to live on other people's phones – whereas photos on your own tend to be of places and other people.