Shopify's ML team demonstrated compounding inference by fine-tuning a 0.8B-parameter model that outperformed GPT-5.6-sol on buyer profile tasks through three rapid training cycles in one week. The breakthrough came from reinvesting inference outputs as training data, reducing prompt costs 8x, and increasing throughput 36x across three simultaneous feedback loops. Success required task-specific quality judges, production-to-training data pipelines, rapid iteration cadence, and dynamic routing between teacher and student models.
RSI AI refers to artificial intelligence capable of recursive self-improvement through feedback loops, where each improvement strengthens the system's ability to produce the next one. The concept, formalized in modern research but rooted in decades of work from Turing to evolutionary algorithms, raises the possibility that AI development could eventually become largely autonomous. The term covers varying degrees of persistent improvement with no single agreed threshold for when RSI is fully achieved.
A new study finds that climate feedback loops from thawing permafrost, wildfires, and warming wetlands could amplify global warming by 20-30% by century's end, adding 0.2-0.4°C beyond direct emissions. These natural sources of methane and carbon dioxide are largely missing from current climate models and projections, potentially underestimating future warming and overestimating safe emission budgets.