Law Does Not Return a Boolean
Fidryn is a proposed language for legal instruments—precise where law is mechanical, explicit on judgment, never hiding authority or ambiguity in a Boolean.
Senior ML research scientist / Boston, Massachusetts
Bryan Gass
I build learning systems and think about memory, agency, and control.
I’m a senior machine learning research scientist working where learning systems meet information theory and dynamical systems. Most of my questions begin with a simple one: what lets an intelligent system carry experience forward?
Selected work
A longer argument
Work / 01
Read the essay →
In progress
Questions, notes, and the route here.
Current questions
A few problems I keep returning to.
- 01
Long-context learning
I am interested in models that can carry useful experience across very long horizons without making memory prohibitively expensive.
- 02
Continual agency
What would it take for an agent to keep learning after deployment—to accumulate skills, revise its world model, and remain useful over time?
- 03
Control and alignment
I use ideas from control and information theory to ask how intelligent systems gain influence, and how they might do so without diminishing ours.