add section on Relational Algebra.

book/00-introduction/00-purpose.md

@@ -7,7 +7,7 @@ authors:
 
 # Introducing DataJoint
 
-This book is a comprehensive guide to *DataJoint for Python* — a specialized framework designed to implement scientific data pipelines that manage data and orchestrate computations in collaborative studies. At its core, DataJoint builds upon the traditional relational database model, enabling scientists, data engineers, and programmers to design and query relational databases. However, DataJoint’s main innovation lies in introducing computational dependencies as a first-class feature within the relational database. This allows researchers to define, execute, and reproduce data processing pipelines with precision and efficiency.
+This book is a comprehensive guide to *DataJoint for Python* — a specialized framework designed to implement scientific data pipelines that manage data and orchestrate computations in collaborative and AI-powered scientific projects. At its core, DataJoint builds upon the traditional relational database model, enabling scientists, data engineers, and programmers to design and query relational databases. However, DataJoint’s main innovation lies in introducing computational dependencies as a first-class feature within the relational database. This allows researchers to define, execute, and reproduce data processing pipelines with precision and efficiency.
 
 # Purpose of This Book
 
@@ -57,8 +57,12 @@ While the tools and concepts in this book are applicable to any computationally
 
 As a result, some of the examples in this book will naturally have a neuroscience focus. However, these examples are chosen to illustrate broader principles and techniques that can be adapted to a wide range of scientific disciplines.
 
-# Contributions
+# AI Integration
+As of early 2025, it has become unmistakably clear that AI assistance is no longer a temporary trend but a transformative force reshaping the programming landscape. AI is rapidly becoming an indispensable companion in software development, enhancing productivity, enabling more sophisticated workflows, and fundamentally altering how we approach problem-solving and manage knowledge in collaborative projects.
+
+In this book, we will explore the profound impact of AI on database schema design, computational orchestration, and data queries. These core elements of scientific data management and analysis are poised for significant evolution within AI-infused environments. From automating repetitive tasks to providing intelligent recommendations, AI tools can streamline database design, optimize computational workflows, and offer insights that were previously out of reach.
 
-I welcome and appreciate your contributions to this book, whether as a reviewer or as a contributor.
+# Contributions
+I, Dimitri Yatsenko, am the principal author of this book but I welcome and appreciate your contributions, whether as a reviewer or as a contributor.
 All contributions will be gratefully acknowledged.
 Please feel free to contact me directly or submit an issue in the book's GitHub repository.

book/00-introduction/01-history.md

@@ -47,8 +47,11 @@ By 2018, Vathes had added key members: Shan Shen, Thinh Nguyen, Chris Turner, an
 In 2021, we rebranded the company as **DataJoint** to better align with our core product, shifting our focus toward commercial technology for research collaboration. During this time, I transitioned to a full-time role as CEO.
 
 # The DataJoint Platform
-In 2022, we received a Phase II SBIR commercialization grant from the NIH to develop an online collaborative platform—[**DataJoint Works**](https://works.datajoint.com). Monty Kosma, who joined the company that year, led the effort to build the platform. Monty later became a co-founder and President, guiding the company’s transformation from a consulting firm to a product-focused enterprise.
 
-The **DataJoint Works** platform officially launched in 2024, with the first cohort of labs successfully operating their experiments on the platform.
+In 2022, we were awarded a Phase II SBIR commercialization grant from the NIH to develop an innovative online collaborative platform: DataJoint Works. This marked a significant milestone in our journey, enabling us to expand our capabilities beyond traditional consulting services. Monty Kosma, who joined the company that year, spearheaded the development of the platform, bringing his vision and leadership to the forefront. Monty's contributions were instrumental, and he later became a co-founder and President, guiding DataJoint's transformation from a consulting firm into a product-focused enterprise.
 
-Today, DataJoint blends community-driven open-source development of core tools with a robust online platform for hosting and managing DataJoint pipelines.
+The **DataJoint Works** platform officially launched in 2024, empowering the first cohort of labs to seamlessly operate their experiments using its robust and intuitive features. This milestone demonstrated the potential of DataJoint Works to revolutionize how scientific data is managed and shared, setting a strong foundation for its adoption across the research community.
+
+In the fall of 2024, the company entered a new phase of growth with the addition of Jim Olson, a seasoned executive with a proven track record. Jim had previously served as CEO of Flywheel.io, a leading data operations platform, where he established himself as a visionary leader in the field. Joining DataJoint as CEO in December 2024, Jim brought fresh perspectives and strategic insights, positioning the company to scale its impact and reach new heights in the years ahead.
+
+Today, DataJoint exemplifies a harmonious blend of community-driven open-source development and a powerful online platform for hosting and managing DataJoint pipelines. This dual approach ensures that our tools remain accessible, reliable, and continuously evolving, while providing researchers with a secure, collaborative environment to advance their work.