Generative AI (GenAI) and large language models (LLMs) are disrupting the way we work at a global scale. Snowflake is excited to announce an innovative product lineup that brings our platform’s ease of use, security and governance to the GenAI world.
Generative AI is unlocking new ways to drive innovation, improve productivity and derive more value from data. For organizations to fully capitalize on this potential, it’s critical that everyone — not just those with AI expertise — is able to access and use generative AI.
At Next ‘23, Exabeam, Dun & Bradstreet, Optimizely and LiveRamp shared how they use BigQuery and Google Data and AI Cloud for data monetization.
Enterprises see embracing AI as a strategic imperative that will enable them to stay relevant in increasingly competitive markets. However, it remains difficult to quickly build these capabilities given the challenges with finding readily available talent and resources to get started rapidly on the AI journey.
To ensure a frictionless AI/ML development lifecycle, ClearML recently announced extensive new capabilities for managing, scheduling, and optimizing GPU compute resources. This capability benefits customers regardless of whether their setup is on-premise, in the cloud, or hybrid. Under ClearML’s Orchestration menu, a new Enterprise Cost Management Center enables customers to better visualize and oversee what is happening in their clusters.
Every business that analyzes their operational (or transactional) data needs to build a custom data pipeline involving several batch or streaming jobs to extract transactional data from relational databases, transform it, and load it into the data warehouse. In this post, we show how you can leverage Amazon Aurora zero-ETL integration with Amazon Redshift and ThoughtSpot for GenAI driven near real-time operational analytics.
A patient interaction turned into clinician notes in seconds, increasing patient engagement and clinical efficiency. Novel compounds designed with desired properties, accelerating drug discovery. Realistic synthetic data created at scale, expediting research in rare under-addressed disease areas.
AI. It’s on everyone’s mind—and marketers are no exception. You’ve likely heard about it from co-workers, vendors and peers, and if you had a nickel for every AI mention you heard … well, you get the point.
