Generative AI 2024 Retrospective 2024 witnessed a parade of increasingly more powerful AI model releases, culminating in OpenAI’s groundbreaking “o3”. While I’m certain these advancements really are significant, I don’t think they have translated to noticeable improvements for the average user. What people are paying attention to, though, are the really amazing product features that are coming out of Anthropic and Google. I’ve heard a lot about people building software Claude’s Artifacts.

This is a review of Open WebUI, an extensible and user-friendly self-hosted WebUI for LLMs. I recently decided to run my own UI layer for LLMs, as I have some exciting ideas. For those who are not familiar with chatbots, their architecture basically looks like this: While I’m pretty good at customizing the middleware, I’m not as skilled at customizing the UI layer. I tried writing my own UI at first, but I quickly gave up when I realized it was beyond my skills as a frontend developer.

OpenAI took the world by storm in 2023 with the relase of ChatGPT. Other companies quickly followed suit, introducing their own competitors to ChatGPT. In this update, I want to write down my thoughts on some of the biggest players in the field of generative AI. When I use the term “generative AI,” I am referring to a computer program that can generate text, images, or other types of content. These programs can understand natural language and follow complex instructions.

Once you know a programming language well, the process for learning a new language is not very hard. It is just time consuming. You need to read the documentation for basic syntax and flow control, get familiar with its idioms, memorize core parts of the standard libraries, and learn its tool chains. What can we do to speed up the learning process? One thing we can do is provide great examples in the documentation.

Writing code with ChatGPT. In the aftermath of ChatGPT’s debut, the Internet is abuzz with GPT’s ability to write code. I used it to write code yesterday, and this is what I thought. I wanted to create a command line program to interact with APIs from OpenAI and AI21. The design is a single program with subcommands for each company’s APIs: Usage: /bin/foo_to_be_named <command> A tool to interact with various LLM models from the CLI Flags: -h, --help Show context-sensitive help.

I had two weeks off at the end of 2022. Telesign closed its operations on the last week of 2022 to give employees well-deserved time off for a year of hardwork and I took another week off in addition to that. Like many technologists, I became captivated by OpenAI’s release of ChatGPT in 2022, and I spent a lot of the last two weeks exploring what OpenAI has to offer.

In Chapter 1.3 of [Ball’s Writing an Interpreter in Go][1], we encounter one design decision of his Monkey programming language. Here, the lexer has a NextToken() method that looks like this: func (l *Lexer) NextToken() token.Token { var tok token.Token switch l.ch { // [...] default: if isLetter(l.ch) { tok.Literal = l.readIdentifier() return tok } else { tok = newToken(token.ILLEGAL, l.ch) } } // [...] } This means the lexer itself does not do backtracking.

Author: Rachel Simmons Notes It’s not always about your child. She must learn what we have and do not have control over Examples: Racism, sexism, stereotypes Be aware of such injustices. Learn to manuver around them Model self-regulation Example: Not panic when your child gets poor grades “I wrote ‘be more confident’ in my previous …. I have a change of heart.” - Simmons Principles Model serenity in the face of uncertainty Calibrate parental expectations Manage your own parental anxieties Tips Identify facts.

bind Sometimes a synonym for “map” conflate combine disjoint separate, e.g., odd numbers and even numbers are disjoint disjunction inclusive or – if one of the inputs is True extrinsic not intrinsic federated Top-down delegation of responsibilities; Has a single point of failure at the top. PID controller control loop feedback mechanism e.g., curise control 99%ile Abbreviation of percentile EBNF Extended Backus-Naur Form Useful for defining the syntax of a programming language EBNF terminal a token/word/chunk in EBNF Alpha Αα Beta Ββ Gamma Γγ Delta Δδ Commonly denotes ‘difference’ Epsilon Εε Used in Greedy-Epsilon algo for multi-armed bandit problems Error margin in floating point comparisons.