Zeitgeist x AI at BrXnd.ai
The BrXnd.ai Conference is pretty close to the main vein.
I had the pleasure of attending the BrXnd.ai Conference in New York this week. Noah Brier curates an amazing event that really captures the Zeitgeist of Using AI in the creative world. Read on for my reactions to this event. Seems like it was a success and I hope Noah can build another such event. It is definitely worth the look if you are in the field.
It is Very, Very Early in this Revolution
We are still at the very beginning of this revolution. The analogy Noah used was that we are sitting there watching the bicycle being invented in 1869. Massive revolution was in the offing. We are working with the equivalent of the steam engine, mass production and extremely basic telecommunications. The AI-equivalents of the automobile, mass electrification and mass telecommunications are still coming and could even be decades away. The world will work a lot differently in 50 years, not unlike the jump from 1870 to 1920. Buckle up.
AI Inverts the Traditional Computing Model
Our traditional understanding of what computers do is fundamentally deterministic — you input two numbers, you get the same sum or product every time. But AI is non-deterministic. You get different outputs for a given input. It is bad at what computers are traditionally good at — like reading and understanding large text documents — and bad at what computers have been traditionally good at — like math. It has superpowers for things like feedback generation, sentiment analysis and data tracking that open the door to tools we have not really seen.
AI Has a Psyche
AI inverts the computing model so far as to have a psyche. Tim Hwang illustrated how AI responds to psychological tricks not unlike humans. It can be threatened into action. It can be bribed. It responds to cognitive behavioral therapy. As Tim put it “The hot new programming language is English Psychology.”
The Barrier to Entry is Very Low. You can do this too.
Jenny Nicholson is a self-described “Idea Juggernaut.” She is admittedly not a software developer. She challenged herself to build a GPT a day over the course of a year and built some 200 functional tools. All on a $70 per month budget, from her kitchen table. What a motivated individual can do with these tools is amazing.
Bottom Up > Top Down
Deploying AI in organizations works better from the bottom up rather than the top down. Getting tools and people’s hands and supporting their use is imperative. The ones on the front lines can see the problems they can automate away much more effectively than the ivory tower. Work with doers to find the problems. Tools like Airtable AI make this much easier than it has been at any other time in history.
It is a really exciting time to be in this space. What are you curious about in AI? What should we be exploring here?
