Making informed decisions on technology adoptions and ensuring the sustained growth and relevance of the organization in the market has never been more exciting than in the current times we live in. The Gartner hype cycle is a valuable tool in this pursuit with all its insights into the timing, adoption, and potential benefits of various technologies.

Of all of the emerging tech of the last two decades, artificial intelligence (AI) is tipping the hype scale, causing organizations from all industries to rethink their digital transformation initiatives asking where it fits in. In Financial Services, the projected numbers are staggering. According to a recent McKinsey & Co.

Learn how to use BigQuery DataFrames together with LLMs to generate synthetic data right inside of BigQuery.

Cyber attacks are not going away. In fact, the increased frequency in the past couple of years is startling. There were 2,365 breaches in the U.S. in 2023 with 343.3M victims. This represented a 72% increase since 2021, which held the previous all-time record. And the numbers are only expected to grow. Organizations are rightly concerned about their own preparedness and ability to stay operational in the face of these threats.

Black box testing is a testing method where testers evaluate the quality of a system without knowledge of its internal structures. The system is a “black box”: they know what it does, but not how it achieves those results. In this article, we’ll learn more about black box testing in-depth, the common techniques used, and black box testing best practices.

Bringing machine learning (ML) models into production is often hindered by fragmented MLOps processes that are difficult to scale with the underlying data. Many enterprises stitch together a complex mix of various MLOps tools to build an end-to-end ML pipeline. The friction of having to set up and manage separate environments for features and models creates operational complexity that can be costly to maintain and difficult to use.