According to Stanford AI Lab, the team released End-to-End Test-Time Training (TTT-E2E), enabling LLMs to continue training during deployment by using live context as training data to update model weights (source: Stanford AI Lab on X, Jan 12, 2026). According to Stanford AI Lab, the announcement names NVIDIA AI and Astera Institute as collaborators and provides links to a project blog and an arXiv preprint for the full release (source: Stanford AI Lab on X, Jan 12, 2026). According to Stanford AI Lab, the release does not mention any cryptocurrencies, tokens, or blockchain integrations, indicating no direct on-chain changes for digital assets to track in this announcement (source: Stanford AI Lab on X, Jan 12, 2026). According to Stanford AI Lab, traders can reference the official blog and arXiv links to evaluate benchmarks and implementation details once reviewed, which can inform assessments of compute intensity and hardware dependencies relevant to AI-infrastructure exposure (source: Stanford AI Lab on X, Jan 12, 2026).