According to @DeepLearningAI, Google researchers introduced ATLAS, a transformer-like language model that replaces attention with a trainable memory module and processes inputs up to 10 million tokens; source: @DeepLearningAI. According to @DeepLearningAI, the team trained a 1.3 billion-parameter model on FineWeb and updates only the memory module at inference; source: @DeepLearningAI. According to @DeepLearningAI, ATLAS achieved 80 percent on BABILong with 10 million-token inputs and averaged 57.62 percent across eight QA benchmarks, outperforming Titans and Transformer++; source: @DeepLearningAI. According to @DeepLearningAI, the source does not mention cryptocurrencies, but the reported long-context benchmarks and memory-augmented inference provide concrete performance data that traders can track when assessing AI-related market narratives; source: @DeepLearningAI.