The Heavybit Library
The Heavybit Library is an extensive catalog of educational content featuring hundreds of hours of expert presentations, insightful podcasts, and articles focused on helping technical founders achieve breakout success.
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Open Source Ready Ep. #20, Exploring AI Memory with Vasilije Markovic of Cognee
In episode 20 of Open Source Ready, Brian and John sit down with data engineering and cognitive science expert Vasilije Markovic...
Regulation & Copyrights: Do They Work for AI & Open Source?
Emerging Questions in Global Regulation for AI and Open Source The 46th President of the United States issued an executive order...
Platform Builders Ep. #1, The Future of CRM is No CRM with Justin Belobaba
In this inaugural episode of Platform Builders, hosts Christine Spang and Isaac Nassimi of Nylas welcome Justin Belobaba, Founder...
How It's Tested Ep. #15, Empowering Upward Mobility with Devin Cintron of Comun
In episode 15 of How It’s Tested, Eden speaks with Devin Cintron, engineering manager at Comun. Devin shares how his team creates...
RAG vs. Fine-Tuning: What Dev Teams Need to Know
RAG vs. Fine-Tuning: Advantages and Disadvantages In the rapidly evolving world of artificial intelligence, the ability of...
How to Properly Scope and Evolve Data Pipelines
For Data Pipelines, Planning Matters. So Does Evolution. A data pipeline is a set of processes that extracts, transforms, and...
Synthetic Data for AI: Purpose and Use Cases
What to Know About Synthetic Data for AI Programs For software developers, large language models (LLMs) like ChatGPT can help...
How to Think About Positioning for Open Source
Positioning Open Source for Your Community (and Yourself) Why is Heavybit posting this extensive interview on thinking through...
Best Practices for Developing Data Pipelines in Regulated Spaces
How to Think About Data Pipelines in Regulated Spaces Tech teams standing up new AI programs, or scaling existing programs, need...
The Role of Synthetic Data in AI/ML Programs in Software
Why Synthetic Data Matters for Software Running AI in production requires a great deal of data to feed to models. Reddit is now...
How Local-First Development Is Changing How We Make Software
What Local First Is, and Why It Matters Local-first development is a development ethos that keeps data and code on your device...
Machine Learning Lifecycle: Take Projects from Idea to Launch
Machine learning is the process of teaching deep learning algorithms to make predictions based on a specific dataset. ML...