Chris Albon@chrisalbon · Apr 20, 2023

If you are interested in it, here why I think you should get into AI right now. Disclaimer: If you are looking for…

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Summary

The author argues that AI/LLMs represent a current window of opportunity similar to blogging (2003-2009) and data science (2007-2014), where barriers to entry are low and no one is yet an expert. Getting involved now through experimentation and community engagement can establish networks and expertise that become much harder to acquire once the field matures in 5-10 years.

Summarized by ThreadOut AI from the full thread. May miss nuance — read the thread below.

#1
If you are interested in it, here why I think you should get into AI right now. Disclaimer: If you are looking for some AI hype thread, go somewhere else.
#2
TL;DR when a new thing comes along, there is a window of time where nobody is an expert. There are only people interested in it, playing around with it, and talking with each other. But eventually the thing matures and the window closes. After barriers to entry are much higher.
#3
I have been a part of three of these windows. The first was blogging (2003-2009). What ChatGPT/AI is today, blogging was in 2003. Nobody was a "big name" in blogging. Everyone was just some random person writing about a topic on their website.
#4
People had "blogging houses", the blogging community was small enough that a lot of people networked together and hung out together. Back then I had a blog about the health effects of armed conflict. I'd spend hours reading and debating with other political/natsec bloggers.
#5
A lot of us got to know each other, hung out together, and are still friends to this day. And over time, these people, the people WHO WERE THERE AT THE START, eventually got jobs with major publications and companies, wrote books, became themselves influential in journalism, etc.
#6
My takeaway for you is that these people *would not have been able to get their foot in the door in journalism/politics* today. They were too young, didn't have the right degrees etc. They got into blogging/writing about politics when the window was open.
#7
The second window was data science (2007-2014). I have a PhD in quantitative political science. I'd probably struggle to get into ML today given the number of STEM PhD joining the field. But in 2008 "data science" wasn't a thing. It was just some friends who would get drinks...
#8
together and talk about data. And internet friends who would discuss and debate data things on twitter every day. Some of us had STEM majors, others had music majors and ag majors. The formal barrier to entry was so much lower than it is now.
#9
Over time data science got popular and matured, and the window closed a bit. Now people can get degrees and PhD directly in data science. But the people who got in during that early window made a reputation for themselves and continue to have major success.
#10
Right now we are living in a third window: LLMs/generative AI. Nobody is an expert, nobody has a decade of experience in LLMOps. Nobody has 10,000 hours experience writing prompts. The barriers to entry are super low. The window is wide open. BUT THIS WON'T ALWAYS BE TRUE.
#11
5-10 years from now there will be "senior" people in the LLM field with a mountain of experience a new person trying to get their foot in the door couldn't dream of having yet. And they will have a deep social network they can rely on for support and advice.
#12
The window is open right now. But it won't always be open. So if you are interested, start playing around, talking to people, reading about what people build, etc. It will set you up in a really good spot for the next decade.