How Stochastic-Oracle Turing Machines May Change AI Computation
Stochastic-Oracle Turing Machines (SOTMs) redefine AI computation by using context-driven responses. Discover the implications of cached versus fresh-response oracles.
Read the full articleYou might also wanna read
AI Evolution in 2025: From Stochastic Parrots to Chain of Thought Reasoning
blog comments powered by Disqus
The Evolution of AI: From Static Benchmarks to Inference-Time Search for Autonomous Agents
Benchmarking at inference time as a way to achieve your agent's goals
Rethinking Search: From Query-Answer Services to Programmable Primitives for AI Agents
Evolving search from monolithic services to programmable primitives for the era of agent harnesses.
The Rhetorical Battle Over LLMs: Between "Solved" and "Stochastic Parrot"
Your favourite ROP gadget
The Rhetorical Battle Over LLMs: Between "Solved" and "Stochastic Parrot"
Your favourite ROP gadget
Meta Tech Lead Nishant Gupta Makes Case for Deterministic Infrastructure to Support Non-Deterministic AI Agents
Nishant Gupta from Meta discusses the critical need for deterministic infrastructure to reliably run non-deterministic AI agents, highlighti
Red Queen Gödel Machine: An Evolutionary Framework for Self-Improving AI with Dynamic Evaluation
Self-improving agents are state-of-the-art (SOTA) on agentic coding benchmarks and have recently been extended to general domains. However,
Red Queen Gödel Machine: An Evolutionary Framework for Self-Improving AI with Dynamic Evaluation
Self-improving agents are state-of-the-art (SOTA) on agentic coding benchmarks and have recently been extended to general domains. However,

Comments
Sign in to join the conversation.
No comments yet. Be the first.