abhimskywalker

Hi HN community,

I'm trying to start working on a project to create a personalized AI language model that evolves based on user interactions and feedback. Inspired by Ted Chiang's "The Lifecycle of Software Objects," I envision AI companions that learn and grow with their users, acting as personal assistants, tutors, or friends.

My plan is to use an open-source LLM like Meta's Llama or Stanford's Alpaca, host it on a personal server or low-cost cloud service, and fine-tune it based on conversation history and user feedback.

I'd appreciate your thoughts on:

  - Feasibility and potential challenges.
  - Best practices for fine-tuning LLMs and effective feedback mechanisms.
  - Ideas for user-friendly interfaces that encourage interaction.
  - Ethical considerations, privacy concerns, and potential biases in the learning process.
  - Relevant experiences or resources you'd recommend.

Quick context on "The Lifecycle of Software Objects," by Ted Chiang: The story explores the concept of digital beings called "digients" that evolve and learn through interactions with their human "parents" in a virtual environment.

Having searched multiple places, it seems there are mixed opinions on best way to start learning C++ across time and internet forums.

For experienced programmers (Python, JS, Java, Kotlin, etc.), what's the best way to pickup modern C++?

What are best resources you have come across for C++?

What are some of the most interesting problems from you respective domains that you feel should be solved but which aren't in focus areas of decision-makers and not being worked upon by enough people?

Was looking around on internet on how to set processes in place to bette manage a large team which works on a large codebase and deals with multiple business stakeholders to get. - Need to sort out both team structure & clean the code. - Was looking at clean code (SOLID principles) as guidelines to re-architecture codebase - And to organise team units around the independent modules they will work with

Would appreciate any leads on where can i find any reading material or experiences of folks having done such transitions & how they managed team incentives/KPI alignment to enhance overall productivity of the organisation...

tl;dr Need to move from (Messy team + Messy codebase) => (Clean team + codebase structure) for better productivity. Any guidelines or stories on this from experiences?

Was just curious. I remember reading a nice post on Instagram feed queues and sharding architecture, and the S3 issues they faced. But can't find it anywhere on Google now. Would be great if anyone could point to engineering architecture explanations of these at that scale.

Recently I discovered https://github.com/igrigorik/videospeed a chrome plugin. And now I can easily breeze through most videos on internet at 2x-3x speeds. It's been awesome! Saves lot of time and increases efficiency. It was a very pleasant discovery. Would love suggestions for similar everyday tool/plugins to deal with ever-increasing interesting content.

Currently have a plan to start with "Principles of Corporate Finance" (by Richard Brealey and Stewart Myers), followed by "Options, Futures, and Other Derivatives" (by Hull). Then perhaps "Security Analysis" (by Benjamin Graham and David Dodd). These seem to be of quite seminal nature in finance literature according to most sources.

Not very sure what to do after that. Would really appreciate any guidance in this direction, or if there is a better/efficient way to go about gathering solid applicable knowledge in this area. Want to acquire solid finance foundations, so as to be able to implement the complex financial processes & systems (like marketplaces, securities & OTC instrument contracts, trading bots, etc.) on my own.

Additional background info if it helps: Current skill sets I have: Economics & Stats (MS level knowledge) | R, SAS, Stata, MATLAB, etc. (2 years as data science guy) | Python (2 years as full stack dev); basic Java (coding challenges level only) | Also good college level calculus, linear algebra, basic optimization techniques etc. so won't shy away from complex Maths.

Motivation: - I have lived in Bangalore (India) for last 4 years, and been to lots of tech, startup & product conferences, meetups, etc. One common phrase I have heard often is how things go down in "The Valley". Many lines from established folks have started with "Back in the valley...", and so on to arouse enough curiosity as to what sort of holy land is this place? - I had the opportunity to visit SF for 5 days for Elasticon in March'15, did meet a few interesting people but frankly couldn't really find much magic of the promised land... :/ - I am planning to do a personal trip again now for a week or two to just spend time to explore "The Valley" & see for myself what is it all about... Hence looking for suggestions on how to best utilize time to experience the magic that is apparently much more dense here than most other places in the world, and then plan the trip accordingly.

Brief personal background: - 27 years old right now. Masters in Economics (Minor in CS ...unofficial), then 2 years as data science guy/analyst at large bank, then career shift with 2 years as full-stack developer at a "Valley"-funded startup. Now trying to solve a problem in fintech space starting with India.

Thanks!