Researcher Zhang Dinghuai stated in a post that he has left xAI for some time. He wrote that the past year has been the most intense and rewarding phase of his career, focusing on the large-scale training of cutting-edge models: stability, large-scale training, and efficiency.

He studied mathematics at Peking University for his undergraduate degree and pursued his PhD under Yoshua Bengio at Mila, during which he worked at Apple Machine Learning Research and Meta FAIR. After graduation, he served as a senior researcher at Microsoft New England Research and then joined xAI.

At xAI, he worked on the stability of reinforcement learning, scaling reinforcement learning, and large-scale training of programming reinforcement learning. After pre-training, reinforcement learning was used to further enhance reasoning, programming, and agent capabilities, allowing thousands to tens of thousands of GPUs to run continuously for days or weeks without crashing or degrading suddenly.

When Grok 4.5 was released, he wrote about his foundational algorithm changes to promote the stability and capability of reinforcement learning, iterating on infrastructure day and night, and executing large-scale training at the cutting edge. The model was positioned for programming and agent tasks, trained using tens of thousands of NVIDIA GB300 GPUs, with reinforcement learning covering hundreds of thousands of multi-step software engineering tasks.

He thanked colleagues in the overnight war room who helped restart training after system crashes, stating that the team moved quickly and dove into problems until the system was operational again. His academic work also includes research on generative models, probabilistic methods, and enabling models to self-adjust their curriculum in reinforcement learning.

In market mechanisms, the cost is borne by laboratories needing to catch up on programming agent capabilities, while the few researchers who can run large-scale reinforcement learning stably are in demand. The event is driven by personnel movement, with funds flowing from the merged platform to competitors that can still attract key personnel for later training; benefiting are the next laboratories that can open positions, while those needing to continue pushing Grok's programming capabilities face scheduling pressures.

Source: Public Information