According to @hyperbolic_labs, the team released End-to-End Test-Time Training TTT-E2E to address LLM long-context memory, with Hyperbolic supporting the work with its AI infrastructure; source: Hyperbolic @hyperbolic_labs on X Jan 13 2026. According to @hyperbolic_labs citing Karan Dalal, the method continues training at test time by using the input context as training data and leverages next-token prediction as an effective compressor rather than changing architectures; source: Hyperbolic @hyperbolic_labs on X Jan 13 2026, links nvda.ws/4syfyMN and arxiv.org/abs/2512.23675. According to @hyperbolic_labs, the full release is a collaboration with NVIDIAAI, Astera Institute, and Stanford AI Lab, with resources available via the NVIDIA blog and arXiv; source: Hyperbolic @hyperbolic_labs on X Jan 13 2026. For traders, the announcement names NVIDIA NVDA among collaborators and does not mention any cryptocurrency or token, so positioning and timing should reference the cited announcement and linked materials for verification; source: Hyperbolic @hyperbolic_labs on X Jan 13 2026.