What our community of 200+ ML engineers and data scientists is reading now

Bailey Seybolt
[Image: The New Yorker]

The new poem-making machinery

The singularity, according to a poetry-writing AI.

[Image: unite.ai]

Reddit Band ‘SFW’ deepfake community

How companies like Google and Reddit are dealing with more “complex” usages of advanced deep learning models.

[Image: wbur.org]

Smarter health: how AI is transforming healthcare

American health care is complex, expensive, and hard to access. This podcast series offers a good overview of the potential of AI to change that – from from predicting patient risk, to diagnostics, to just helping physicians make better decisions.

[Image: future.com]

Emerging architectures for modern data infrastructure

An update on an article first published in 2020, article that explores data architectures across multiple contexts to help data teams stay on top of industry changes. The article not only explores current best-in-class stack across analytic and operational systems, but also what’s changed since 2020 and why.

[Image: Lenny's podcast]

Gibson Biddle on his DHM product strategy framework, GEM roadmap prioritization framework, 5 Netflix strategy mini case studies, building a personal board of directors, and much more

An exploration of product strategy for consumer companies with former VP of Product at Netflix Gibson Biddle. Also covers recent events in the product world (e.g. Netflix and share price) and what PMs should know.

[Image: Forbes]

Synthetic data is about to transform artificial intelligence

According to a widely referenced Gartner study, 60% of all data used in the development of AI will be synthetic rather than real by 2024. What does that mean the modern economy, business operations, and applied AI?

[Image: Brian Christian]

The alignment problem

Published in 2020, this book examines what is know as the “alignment problem” in AI, from its technical foundations to its philosophical implications. The section on inverse reinforcement learning and how this might help build high-trust AI systems is particularly interesting.

Related Stories

Applied AI

How RAG (Retrieval-Augmented Generation) Is Reshaping Document Review in M&A

Applied AI

What Is AI Content Discovery? A Guide for Educators

Applied AI

AI in Risk Management: A Comprehensive Overview

Applied AI

How to Measure ROI on AI Investments

Applied AI

AI Consulting in Healthcare: The Complete Guide

Applied AI

How AI Is Revolutionizing Nutrition Tracking and Personalized Health

Applied AI

The Hitchhiker’s Guide to Generative AI for Proteins

Applied AI

No labels are all you need – how to build NLP models using little to no annotated data

Applied AI

The Generative Context Engine Explained: A New Way to Handle Log Overload

Get started with Tribe

Companies

Find the right AI experts for you

Talent

Join the top AI talent network

Close
Head of Content
Bailey Seybolt
Bailey got her start in storytelling as a journalist, before pivoting to tech content development for unicorn startups from Montreal to San Francisco – helping build brands and shape stories to drive business results.