The Dan MacKinlay stable of variably-well-consider’d enterprises
Human reward hacking
Deep linear networks
Discretizing and quantizing neural nets
The Predictive Approach to Bayesian Inference
Degrees of freedom in NNs
Inductive biases
Multi-level agency
The deep history of intelligence
Fractal and self-similar behaviour in neural networks
Distributed community NN training
Estimating the Local Learning coefficient
Learning Schrödinger bridges
Commitment, contracts, cooperation
Bayesian epistemics
“Opponent shaping” as a model for manipulation and cooperation
Learning with theory of mind
q-exponential process
The United States of America
Being stroppy
Configuring machine learning experiments with Fiddle
Neural denoising diffusion models of language
Developmental interpretability
Disentangled representation learning
Multi agent causality
Computational complexity of Bayesian inference
Rituals
Singapore
Machine learning for partial differential equations via flows
Machine learning for partial differential equations using diffusion models
Causal abstraction
ILIAD2
Garbled highlights from ICLR 2025
The Netherlands
Building AI Agents
Fine tuning foundation models
Aligning AI systems
Governance of and by AI
Human domestication
Computational complexity and computability results in neural nets
Prefigurative politics
AI Alignment Fast-Track Course
The production of bullshit
Machine learning for biology
State capacity
World models arising in foundation models.
Which self?
Constructivist rationalism
Quantum computing for ML
Home automation
Natalism and fertility
Certification of neural nets
uv, the python package manager