Systems | Development | Analytics | API | Testing

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.

Every day, more companies unlock the potential of artificial intelligence (AI) and machine learning. When AI and machine learning are utilized in embedded analytics, the results are impressive. Much of this can be seen in modern solutions that offer advanced predictive analytics. Together, predictive analytics and AI can help application teams by streamlining processes, generating personalized recommendations, and creating a more intuitive and efficient user experience.

Fivetran COO, Taylor Brown, spearheads AI success via robust data foundation.

It's not hard, it's just new. How can you, your business unit, and your enterprise utilize the exciting and emerging field of Generative AI to develop brand-new functionality? And once you’ve figured out your use cases, how do you successfully build in Generative AI? How do you scale it to production grade?