The Track
A Section Blog
Is Deep Research worth $200 a month?
How we built a generative AI bot
By summer 2023, we were convinced we needed to use AI to improve our student experience. From August to October, we designed, built, and prototyped an AI course tutor called ProfAI. In today's post, we'll walk you through how we did it.
Our hot take on Google Gemini
On Wednesday, Google announced its long (long, long)-awaited AI product, Gemini. We dug in to understand whether Gemini lives up to the hype, what it signals for OpenAI and Microsoft, and what you can use it for right now.
The best AI chatbots in 2023
AI chatbots are not all built the same, and even the best ones aren’t best for every use case. That's why we put together a list of the best AI chatbots in 2023 - consider it your "holiday gift guide" for AI.
The biggest lessons from Tinder’s Matchmaker feature
We're diving into the product strategy behind Matchmaker, a new feature from Tinder that lets you share your potential matches with friends and family. Read on for our take on why this development is a product engagement win.
The most AI Proficient industries in 2024
A rundown of the industries that are leading the AI charge – and what sets them apart – and which are lagging behind.
Claude for Teams: What You Need to Know
Will Anthropic's new features in Claude for Teams – “Projects” and "Artifacts" – really make your team more collaborative and productive? We put them to the test.
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.
