When approaching machine learning operations, the options can be overwhelming. There may be multiple solutions available for each step in the process, and the most popular (usually open source tools) may not necessarily be good or easy to use, but they are free.
Today’s governmental and educational organizations can’t fully use the wealth of data they possess to improve citizen and student outcomes. Government agencies often deal with disparate and siloed data that can impact real-time decision-making. Securely exchanging information and collaborating on data remains an essential task in almost every agency strategy.
Artificial intelligence (AI) has reached a tipping point in the public consciousness. Much of this has been driven by technology developments related to large language models (LLMs) and the release of generative AI tools, including ChatGPT from OpenAI. However, for enterprises shaping forward-looking AI strategy, a critical part of the conversation that needs to be addressed is the issue of private AI vs. public AI.
Databricks’ 2023 State of Data + AI report highlights the importance of the modern data stack in leveraging AI.
A microVM is a lightweight virtual machine. Any function or container workload can run inside of one. It is ideal for running multiple high-performance and secure workloads concurrently on a single machine because it combines the security and isolation of traditional VMs with the resource efficiency of containers. In this blog post, we dive into the world of microVMs, specifically Firecracker microVMs.
How BigQuery’s ML inference engine can be used to run inferences against unstructured data in BigQuery using Vertex AI pre-trained models.
