I write about why I decided to move from Ghost to Writefreely.
I never think of myself as a “sales” man. I've seen many classmates sell more raffle tickets than me in school. Heck, I even thought that making partner was too much for me. Convincing people to hand over their cash? That's not me.
It's essential, though. One of my first lessons as an associate was that research and submissions count for nothing until the client pays the invoice. Being a law firm partner is not so much about being the sharpest knife in the firm but bringing in the dough. You have to network, you have to serve, and you've got to make people hand over the money.
Part of growing up (read: growing old) is being more comfortable with your skin. Lately, I have recognised other traits in me — tenacity, a willingness to try, and under all that unwillingness to socialise with others, gobs of empathy. I can think of some jobs I am uncomfortable with, but I must keep finding something that fits me.
That's what this blog is about, and it will stay that way for a while.
I compare two discussion papers on possible approaches to regulating the use of generative #AI.
Given the coming AI Apocalypse, you would expect tech companies to barrel down and make their products safe at all costs. Well, you know they are completely focused on averting the Cthulu apocalypse... when they are on a world tour.
Since we are not going to get much of a hand from companies like #OpenAI, it's up to users to figure out how to do AI safety by themselves. I've been fortunate to come across two new approaches to share with my readers.
The angst about #AI apocalypse shouldn't be about the Cthulu apocalypse. At least, it should be something that works.
Fresh from learning what happens if you use #ChatGPT (wrongly) in court, it seems that not a day goes by without some dire warning about large language models and AI.
A brief flirtation with viral success brought new attention to one of my #Python libraries and some real-world applications of the workings of #OpenSource.
Readers who have stuck around might recall my big project last year. It was a study on the readability of legislation in Singapore and how much “Plain Laws” drafting affected it. (Spoiler alert: limited, if any).
I wrote a Python library called “#redlines” while writing that post. I needed to represent changes in text like the “track changes” function in Microsoft Word, which was the most familiar method to my audience of lawyers. I couldn't find any libraries to do this in Markdown, so I created one and published it anyway.
I publish most of my coding publicly on my GitHub. I do it with little expectation that anyone would use it. This post discusses my motivations for publicising almost all of my coding work.
When registering myself from some professional conferences, I found greater emphasis on ChatGPT and AI regulation. I write about what I am now dreading with this trend.
I share my experience and process of generating daily newsletters from Singapore Law Watch using ChatGPT, serverless functions and web technologies.#Featured
Introduction
It's easy to be impressed with Large Language Models like #ChatGPT and GPT-4. They're really helpful and fun to use. There are a ton of uses if you're creative. For weeks I was mesmerised by the possibilities — this is the prompt I would use. Using this and that, I can do something new.
When I got serious, I found a particular itch to scratch. I wanted to create a product. Something created by AI that people can enjoy. It has to work, be produced quickly and have room to grow if it is promising. It should also be unique and not reproduce anything currently provided by LawNet or others.🤔
There is one problem which I felt I could solve easily. I've religiously followed Singapore Law Watch for most of my working life. It's generally useful as a daily update on Singapore's most relevant legal news. There's a lot of material to read daily, so you have to scan the headlines and the description. During busier days, I left more things out.
So… what can ChatGPT do? It can read the news articles for me, summarise them, and then make a summary report out of all of them. This is different from scanning headlines because, primarily, the AI has read the whole article. Hopefully, it can provide better value than a list of articles.
I discuss how ChatGPT can be augmented with custom data to improve its performance using Singapore law as an example.
🔷 Update (31 May 2023): (1) Added a reference to Intellex's Scott; (2) Streamlit now embeds your apps, so there's a convenient way to access the Compare app.
#ChatGPT is a language model developed by OpenAI, with 1.5 billion parameters. It is capable of generating high-quality text in response to prompts and has been used for a variety of natural language processing tasks. It was trained on a large corpus of text from the internet and has achieved state-of-the-art performance on a number of benchmark datasets. Its versatility and accuracy make it a powerful tool for a wide range of applications.
One of the biggest questions I had was how it would perform on the subject of Singapore law. Law is a specialised area, and Singapore law is an even smaller niche in that. I suspected that statistically, ChatGPT wouldn't know much about it. I wouldn’t be holding my breath.
I explain how to use #ChatGPT to write resumes, including finding a template, directing the model to produce bullet points, and summarizing experiences. The article highlights the benefits of using ChatGPT and provides tips for using the tool effectively.
If you are an introvert like me, writing a #resume or a curriculum vitae (#CV) must be one of the most irritating chores. Unfortunately, it’s integral to finding a new job and opening new opportunities. In this post, I try to save myself from this nonsense by getting ChatGPT to do it for me instead. Once you see how easy and effective it can be, you’d probably never want to do it on your own again.
