Because reasoning-focused RL is new, the amount all AI developers spend on the RL training stage is still small, so the field is early on its scaling curve.

Judge as of the date the statement was made: 2022-10-13 as given, or, if the source shows it was actually made later, that later date. True: evidence from that time shows that RL training aimed at reasoning was a recent development and that developers' spending on the RL stage was small (for example small compared with pretraining compute), so large gains from further scaling remained available. Mostly true: the substance holds, but a detail such as the extent of spending across 'all' developers is slightly overstated. Mixed: RL for reasoning was new, but there is evidence that some developers already spent heavily on it, or the 'early on the scaling curve' point is contested. Mostly false: the claim stretches a narrow or early observation into a general one, or reasoning RL was not new or not small-scale at that time. False: the evidence shows major developers were already spending at large scale on reasoning RL, with limited room to scale left.

Set before the research began.

1. E1 Training compute | AI Wiki AI Wiki · 15 October 2026

   “Until recently, Epoch AI wrote in 2025, most large language models were trained with about 100 times more pretraining compute than post-training compute.”

2. E2 Training compute | AI Wiki AI Wiki · 15 October 2026

   “Reasoning models changed that by spending large amounts of compute on reinforcement learning after pretraining and on long chains of reasoning when answering, known as test-time compute.”

3. E3 Training compute | AI Wiki AI Wiki · 15 October 2026

   “xAI said it used its 200,000-GPU Colossus cluster to run reinforcement learning for Grok 4 "at pretraining scale", and that the run used over an order of magnitude more compute than had been used previously.”

E1 reports Epoch AI's 2025 finding that until recently most large language models used about 100 times more pretraining compute than post-training compute. That fits the claim that spending on the RL stage was small. E2 describes reasoning models, with their heavy RL after pretraining, as a later change from that pattern, which supports the claim that reasoning-focused RL was new and had room to scale. E3's Grok 4 RL run "at pretraining scale" is undated and appears to come later, so it does not contradict the claim as of the judging date. The evidence does not say exactly when reasoning RL emerged or confirm the claim for every developer, so the verdict is mostly true rather than true.