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.

The AI technologies of today—including not just large language models (LLMs) but also deep learning, reinforcement learning, and natural-language processing (NLP) tools—will equip telcos with powerful new automation and analytics capabilities. AI-powered automation is already driving significant margin growth by reducing costs.

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?

Artificial Intelligence (AI) is rapidly evolving, and one of the prominent breakthroughs is OpenAI's ChatGPT, which has gained considerable attention. As AI and Large Language Models (LLMs) like GPT-3/4 gain prevalence, various industries are exploring their potential, including software testing. Integrating AI into test management tools seems enticing.

In the ever-evolving landscape of the financial services Industry, change is a constant and transformation is a requirement—to stay at pace with new regulations, risk mitigation, and the technological developments that support transformation. And just as financial services experiences its cycles, this time of year I find myself returning to the topic of cost reduction.

Learn how to perform analytics on BigQuery data using BigQuery DataFrames and its bigframes.pandas and bigframes.ml APIs.

As of 2023, organizations engaged in software development are investing 31% of their total budget into ensuring software quality meets their defined standards.

In the age of climate consciousness, industries worldwide are grappling with the urgent need to reduce their carbon footprints. One industry that has come under increased scrutiny is telecommunications, where Scope 3 emissions, or the indirect emissions that occur in a company’s value chain that the company has no direct control over, alone account for a staggering 85% of a typical telecom company’s carbon footprint.

Every September, world leaders, business executives, investors, NGOs, and global citizens descend upon New York City to learn and discuss progress towards building a sustainable future for all. Although there was much excitement and energy surrounding the UN General Assembly and Climate Week this year, there was very sobering news that more must be done if we expect to achieve the goals set out by the UN 17 Sustainable Development Goals(SDGs) and Paris Climate Accords.

Read About The Hidden Costs, Challenges, and Total Cost of Ownership of Generative AI Adoption in the Enterprise as Well as C-level Key Considerations, Challenges and Strategies for Unleashing AI at Scale ClearML recently conducted two global survey reports with the AI Infrastructure Alliance (AIIA) on the business adoption of Generative AI. We surveyed 1,000 AI Leaders and C-level executives in charge of spearheading Generative AI initiatives within their organizations.

We’ve talked about the many ways large language models (LLMs) and artificial intelligence (AI) are impacting business efficiency, data and analytics, and even FinOps. But we’ve yet to talk about arguably one of the most important areas of concern: security.