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💻 Part 2: How Digital Fragments of Optimization Become Abstract Agents A Deep Dive in the “Fragments to Agents” Series

In Part 1, we explored how biological and cultural systems turn scattered parts into living, social, and economic agents. In Part 2, we shift focus to the digital and abstract realms, where fragments of optimization and computation give rise to systems that act—sometimes in ways even their designers didn’t anticipate.

This session features a substantial presentation followed by deep group discussion. We’ll unpack the central question:

How do fragments of digital optimization become abstract agents?

From machine learning systems and feedback loops to digital marketplaces and algorithmic trading—how do we draw the line between a tool and an agent? And what happens when optimization processes become powerful enough to behave as if they have goals?

We’ll explore topics and questions such as:

• When does optimization become agency?
• What distinguishes a system doing work from one with intent?
• What does mesa-optimization teach us about AI and control?
• How do abstract systems—like social networks or algorithms—begin to influence the real world with agent-like persistence?

This session draws from thinkers such as Alan Turing, Norbert Wiener, Stuart Russell, Melanie Mitchell, John von Neumann, and others in the space of AI alignment, computational emergence, and abstract systems.

This event is open to all groups, but the core emphasis will be on questions most relevant to our AI, computation, and systems-focused members. Other lenses—including biological, philosophical, and cultural—will return in future sessions.

Format:

• Substantial presentation on core ideas
• Open, in-depth discussion and Q&A
• Optional follow-up materials and content links

Whether you’re curious about optimization, autonomy, agency, or existential risk—this session offers a deep look into one of the most urgent and fascinating transitions in the modern world.

Learn how to write, tune, and port SQL queries and other statements for a Big Data environment, using Impala—the massively parallel processing SQL query engine for Apache Hadoop. The best practices in this practical guide help you design database schemas that not only interoperate with other Hadoop components, and are convenient for administers to manage and monitor, but also accommodate future expansion in data size and evolution of software capabilities. Written by John Russell, documentation lead for the Cloudera Impala project, this book gets you working with the most recent Impala releases quickly. Ideal for database developers and business analysts, the latest revision covers analytics functions, complex types, incremental statistics, subqueries, and submission to the Apache incubator. Getting Started with Impala includes advice from Cloudera’s development team, as well as insights from its consulting engagements with customers. Learn how Impala integrates with a wide range of Hadoop components Attain high performance and scalability for huge data sets on production clusters Explore common developer tasks, such as porting code to Impala and optimizing performance Use tutorials for working with billion-row tables, date- and time-based values, and other techniques Learn how to transition from rigid schemas to a flexible model that evolves as needs change Take a deep dive into joins and the roles of statistics