.@Qbeast_io gets $7.6M in funding to streamline data lakehouses queries with multidimensional indexing https://t.co/wItrMLss8n @SiliconANGLE @Mike_Wheatley “But these AI agents can’t operate in real-time if your platform still relies on partitions and full scans, and…” - @MikeNi https://t.co/4hQSMmtAAQ
.@Google on Tuesday introduced new #AgenticAI capabilities aimed at #data engineers and data scientists. https://t.co/6q0RNVlnLk
Calendar mode for Dynamic Workload Scheduler is in preview! This mode provides short-term ML capacity—up to 90 days of reserved capacity—without requiring long-term commitments. Learn more about reserving the GPUs and TPUs you need with Calendar mode → https://t.co/Ez4KaVFSCn https://t.co/8Ka0CT7aNE
Google has introduced six new AI tools aimed at enterprise data science and engineering, unveiled at the Cloud Next Tokyo event. These AI agents, including the Data Engineering Agent and Data Science Agent currently in preview, are designed to automate data tasks, provide real-time analysis, and reduce the labor involved in data preparation by up to 70%. Developed in collaboration with Google DeepMind, the new capabilities also feature a Code Interpreter and an enhanced Conversational Analytics Agent. Additionally, Google Cloud announced a Calendar mode for its Dynamic Workload Scheduler, allowing short-term machine learning capacity reservations for up to 90 days without long-term commitments. These innovations target increased productivity and error reduction in data processes.