Ilya Sutskever, a prominent figure in the field of artificial intelligence, delivered a talk titled "Pre-training as we know it will end." The talk centered on the future of pre-training in large language models (LLMs). Sutskever argued that the current paradigm of pre-training LLMs on massive datasets of text and code, followed by fine-tuning on specific tasks, is nearing its limits. He posited that future advancements will likely involve fundamentally different approaches to training these models, moving beyond the current reliance on pre-training.

The core of his argument revolved around the limitations of scalability and the potential for alternative training methodologies that could surpass the performance of current pre-training methods. While specifics regarding the "next generation" of training weren't extensively detailed, the implication was that significant paradigm shifts are expected within the field. The talk highlighted the need for innovation and exploration beyond the current, established pre-training methods to achieve further breakthroughs in AI capabilities, namely: agents, reasoning, understanding, and self-awareness.