What our community of 200+ ML engineers and data scientist 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

Key Takeaways from Tribe AI’s LLM Hackathon

Applied AI

7 Prerequisites for AI Tranformation in Healthcare Industry

Applied AI

AI for Cybersecurity: How Online Safety is Enhanced by Artificial Intelligence

Applied AI

AI-Driven Digital Transformation

Applied AI

How 3 Companies Automated Manual Processes Using NLP

Applied AI

Key Generative AI Use Cases From 10 Industries

Applied AI

Tribe's First Fundraise

Applied AI

An Actionable Guide to Conversational AI for Customer Service

Applied AI

8 Ways AI for Healthcare Is Revolutionizing the Industry

Applied AI

How the U.S. can accelerate AI adoption: Tribe AI + U.S. Department of State

Applied AI

Using data to drive private equity with Drew Conway

Applied AI

AI Consulting in Insurance Industry: Key Considerations for 2024 and Beyond

Applied AI

AI in Construction in 2023: Use Cases and Benefits

Applied AI

AI Consulting in Finance: Benefits, Types, and What to Consider

Applied AI

AI in Banking and Finance: Is It Worth The Risk? (TL;DR: Yes.)

Applied AI

AI and Predictive Analytics in the Cryptocurrency Market

Applied AI

8 Prerequisites for AI Transformation in Insurance Industry

Applied AI

Thoughts from AWS re:Invent

Applied AI

A primer on generative models for music production

Applied AI

How to Measure ROI on AI Investments

Applied AI

AI Diagnostics in Healthcare: How Artificial Intelligence Streamlines Patient Care

Applied AI

A Guide to AI in Insurance: Use Cases, Examples, and Statistics

Applied AI

How AI for Fraud Detection in Finance Bolsters Trust in Fintech Products

Applied AI

AI Consulting in Healthcare: The Complete Guide

Applied AI

A Deep Dive Into Machine Learning Consulting: Case Studies and FAQs

Applied AI

Machine Learning in Healthcare: 7 real-world use cases

Applied AI

10 ways to succeed at ML according to the data superstars

Applied AI

What the OpenAI Drama Taught us About Enterprise AI

Applied AI

Everything you need to know about generative AI

Applied AI

How to Build a Data-Driven Culture With AI in 6 Steps

Applied AI

Leveraging Data Science – From Fintech to TradFi with Christine Hurtubise

Applied AI

Self-Hosting Llama 3.1 405B (FP8): Bringing Superintelligence In-House

Applied AI

Advanced AI Analytics: Strategies, Types and Best Practices

Applied AI

AI in Construction: How to Optimize Project Management and Reducing Costs

Applied AI

3 things we learned building Tribe and why project-based work will change AI

Applied AI

AI Security: How to Use AI to Ensure Data Privacy in Finance Sector

Applied AI

Why do businesses fail at machine learning?

Applied AI

Welcome to Tribe House New York 👋

Applied AI

AI Implementation: Ultimate Guide for Any Industry

Applied AI

How to Enhance Data Privacy with AI

Applied AI

5 machine learning engineers predict the future of self-driving

Applied AI

How data science drives value for private equity from deal sourcing to post-investment data assets

Applied AI

Write Smarter, Not Harder: AI-Powered Prompts for Every Product Manager

Applied AI

Understanding MLOps: Key Components, Benefits, and Risks

Applied AI

Tribe welcomes data science legend Drew Conway as first advisor 🎉

Applied AI

Making the moonshot real – what we can learn from a CTO using ML to transform drug discovery

Applied AI

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

Applied AI

How to build a highly effective data science program

Applied AI

AI and Predictive Analytics in Investment

Applied AI

AI in Customer Relationship Management

Applied AI

Scalability in AI Projects: Strategies, Types & Challenges

Applied AI

AI in Private Equity: A Guide to Smarter Investing

Applied AI

How to Evaluate Generative AI Opportunities – A Framework for VCs

Applied AI

Navigating the Generative AI Landscape: Opportunities and Challenges for Investors

Applied AI

Announcing Tribe AI’s new CRO!

Applied AI

The Secret to Successful Enterprise RAG Solutions

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.