The Track
A Section Blog
Can you build a team of just AI tools?
How to build a custom GPT
Follow these step-by-step instructions to build a custom GPT model that completes specific tasks for you.
How to set an AI policy for your company
In this post, we'll cover the four parts to a strong AI policy – your stance on AI, operating norms, rules/guidelines, and real-life use cases.
Where's the money going to be made in AI?
Not every AI investor will make their money back. In this post, we dig into the AI business models that will work, and those that will be the next Pets.com.
10 lessons from running a startup in 2023
This was a hard year for Section, but we’ve come out of it fitter and stronger. Here are 10 lessons that I’ve learned about running a startup – hoping they provide some inspiration to you.
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What is Web3 (and why should I care)?
Everything you need to know to talk about Web3 at your next cocktail hour.
The science-based secret to being more productive at work
Have you ever sat in a 9 a.m. meeting with your team and wondered why one person is jacked up on coffee and firing off ideas, and another person looks like they just woke up from a 100-year sleep?
You might think, “Well, the first person is just more productive. They’re good at their job, whereas Steve is a useless lump. Duh.”
But actually, it’s not that simple. These two people probably have different chronotypes – meaning they’re inclined to sleep, work, and recover at different times.
How the Royal Family’s AI-powered mental health agent overcame privacy concerns
Most orgs feel unready for the challenges that Gen AI brings to risk management. Yet many AI applications will have to navigate the line between user value and user privacy. So we sat down with specialist, Brian Kolodny, to understand how he traversed matters of privacy when building a mental health bot for the Royal Family’s foundation.
Our Guide to Building Enterprise AI Applications
Every company needs to be thinking about where AI slots into their product or service, but all the noise and hype makes it hard to determine what a valuable vs. novel use case looks like. Machine & Partners’ Ed Ortega is sharing 2 frameworks to narrow down your laundry list of AI ideas.
