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As a non-developer, I played with rust and various copilots over the last couple of months. I ended up with a backtesting engine.

Now I figured out I want to go all in actually learning rust and doing the deep dive in crypto. Enjoy the trip.


I use ChatGPT to help study linear algebra.

It helps me a lot when I feel lost. It's often wrong in the calculations, but it's cool to have a study buddy that doesn't judge you.

If I get blocked with a problem I can't solve, I ask for assistance with my approach.

I enjoy asking ChatGPT about the context behind all that math theory. It's nice to elaborate on that as most of the math books are very lean and provide no applied context.


I find myself more and more into the CLI and recently got introduced to Neovim. Decided to start learning Neovim by simply writing markdown documentation and I'd say it's even intuitive.

That works pretty good with markdown files hosted on github pages as I don't have to move out of the CLI when pushing them online.

However, the use case that this workflow doesn't cover is when I write something that I'd like to send for a proofread to a friend of mine, who's an editor. He really loves his Word files.

As I'm a noob, I asked then ChatGPT to help me with a bash script that converts that .md file into a .doc file using pandoc. That worked pretty well.

My thought was if it couldn't be possible to use something like pandoc for converting an .md file into a templated doc with headers, footers, page numbering, even toc?

That wouldn't solve 100% of the use cases, but still could be pretty good.


As I'm still a coding noob, I don't ship code as much as I want to.

However, I make a simple bullet task list and work on it. Tasks are not necessarily related to coding. It could be a task related to image editing. Initially, I was feeling very bad if I can't finish a task within the time I've set for it.

Now I don't feel bad if I can't finish that task on time. I perceive it as a micro-iteration of the task. The trick is to iterate further, until the task is done.

While rushing to do a task within a specific timeframe, might be productive in the short-term, I don't see it feasible if you push yourself all the time doing it. I imagine it might reflect on the quality of your work and lead to a self-induced burnout.

Shipping for the sake of it, in my opinion, might create some false perception of work being done. In my experience, employers tend to reward that behavior.

So maybe the question here would be: why are you shipping in first place? To show off, to boost dopamine through gamifying yourself, or to deliver a piece of work you'll be proud of before going to bed.


What would be interesting for me is, if I can develop an app for, let's say macOS, and expose its context to Siri (with Intelligence) in an easy way.

For example:

Imagine a simple Amazon price tracker I have in my menu bar. I pick 5 products that I want to have their price tracked. I want that info to be exposed to Siri too. And then I can simply ask Siri a tricky question: "Hey Siri, check Amazon tracker app, and tell me if it's a good moment to buy that coffee machine." I'd even expect Siri to get me that data from my app and be able to send it over my email. It doesn't sound like rocket science.

In the end of the day, the average user doesn't like writing with a chatbot. The average user doesn't really like reading (as it could be overwhelming). But the average user could potentially like an assistant that offloads some basic tasks that are not mission critical.

By mission critical I mean asking the next best AI assistant to buy you a plane ticket.


In theory this is covered by the App Entities framework, though it seems like Apple only trains their on-device models to learn about entities for some standard types of apps. https://developer.apple.com/documentation/appintents/app-ent...


I mostly use Google to search on reddit, github and hacker news with "site:github.com".

It's also somehow good to find pdf files with "filetype:pdf".

As already mentioned, the occasional currency and time conversions are also pretty nice. I admit I use their calculator too sometimes.

Essentially, Google advanced search operators have been a pretty powerful feature that I've been using since I learned about it in 2011.

Other than that, I agree the generic search result are a bloody mess.

For a lot of other searches, GPT 4 helps a lot.


What is your favorite operator?


Thanks for sharing this great project! Randomly browsing through the first page results, I ended up reading some of the ideas.

Reading that someone else, somewhere else, has a similar idea, has made my day. Cheers.


Thank you!

Reach out to them and make the idea a reality :)


Location: Bulgaria, EU

Remote: Yes

Willing to relocate: Possibly

LinkedIn: https://linkedin.com/in/angel-gpetrov

About: Strong generalist, working for the last 9 years as a business analyst and product manager. Spent 6+ years in card payments (both POS and eCommerce). I worked mostly with startups, some of them managed to scale up.

Depending on the project, product and/or team I like to:

- Facilitate ideation and discovery workshops on Figma, Miro and recently Freeform

- Build hypotheses based on market research, customer feedback, analytics

- Facilitate iterations based on the hypotheses built in the workshops

- Iterate over user personas, collect data about them and map to use cases

- Map use cases to user flows and then user stories

- Diagram and wireframe. I even tried to do the DailyUI challenge, but I gave up at day 40

- Demo and ask for feedback

Technologies: HTML, CSS, Flask,

Currently interested in building products utilizing generative AI. Questions occupying my head right now:

- Can I connect Siri to Ollama so that I can enhance my productivity?

- Can I scrape up-to-date dev docs that I feed into a local LLM and use them when needed?

If anyone wants to have a chat, feel free to text me on linkedin or spicylimer [at] gmail [dot] com


Yesterday I had the thought of what we could achieve right now with let's say 3 x A2000 leftover GPUs from a random second-hand crypto mining rig.

I think it would be awesome to be able to use GPUs from second-hand crypto mining rigs for cheaper fine-tuning research.

Good luck! As an enthusiast who loves The Lean Startup and who recently started playing around with LLMs, I'm super stoked about Answer.AI


Yes, I love that thread. It helps me with brainstorming on new ideas.

Also, it's pretty nice to share with the small team I'm part of. We're currently working on custom client projects and we'd like to build our product. Seeing how people do it is a nice morale boost, especially for a team that lacks experience in building.


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