Learning, memory & adaptation
Exploring cognitive computation and the relationship between experience, prediction, and action. Interactive tasks offer a way to ask specific questions about an experimental system’s behavior.
Independent research · AI-assisted engineering
Stay curious.
Build. Test.
Ask again.
I’m Sterling Tuttle. I’m interested in how systems learn, remember, and adapt—and how that work can help us build a more sustainable future.
01 / Research interests
Big questions.
Concrete testing grounds.
Simulation & control
Duck simulations and adaptive-control experiments provide a tangible setting for studying movement, feedback, and failure. Simulation is a testing ground for questions about embodied systems.
Prediction & evaluation
Investigating signals, comparisons, and the conditions under which a prediction is useful. The challenge is to distinguish an interesting historical result from an advantage that survives new tests.
The work is experimental. I use interactive tasks, simulated environments, and historical prediction tests to examine specific questions. Published results will identify the version tested, comparisons, and limits of the evidence.
02 / The person behind the work
James Sterling Tuttle.
Also known as
Jim James & V.
My path into research runs through business operations, automation, and independent technical work. I learn by building, testing, and staying with the questions.
I originate ideas and research directions, then lead AI teams through implementation and testing. AI does most of the coding. My role is to frame the experiments, challenge the results, and decide what to investigate next.
I’m working toward a research-lab role where I can collaborate with curious people on difficult problems. I’m also open to AI engineering and consulting that builds useful experience and moves that work forward.
03 / Working principles
The next question
has to earn its place.
- 01Make the question testable.
Define the observation and the comparison before deciding what a result means.
- 02Keep the failures in view.
Corrections and negative results help determine which direction deserves more work.
- 03Connect ambition to useful problems.
A sustainable society shaped by AI is the larger goal. Problems we face today are where the ideas must prove useful.
04 / Research · Engineering · Collaboration
A good question is
a good place to start.
Working on something difficult? I’m interested in research opportunities, substantive technical conversations, and AI engineering projects where I can contribute and learn.
sterling@sterlingtuttle.com ↗