None of us wants our personal data exposed; think how closely we guard our Social Security numbers. But the privacy and confidentiality rules that protect our data often are complicated and wide-ranging. They include large-scale regulatory frameworks, such as the Health Insurance Portability and Accountability Act (HIPAA), plus industry-specific rules and internal policies. Although oftenRead… Read more »
Public information — about road closures, meeting times, emergency responses, and other concerns — may be accurate, but AI’s interpretation of such communications may not be. Learn about one option to address the problem.
Most data today are unstructured, found in everything from Microsoft Word documents and PDFs to video and social media feeds. That array of formats makes it hard for users to collect, analyze and act upon data. It creates an obstacle to data accessibility.
Agentic AI offers capabilities beyond what earlier AI can do. But agentic AI’s autonomous nature amplifies an organization’s underlying data, governance and other weaknesses and requires a new IT mindset.
In this video interview, Snowflake’s Adam Edelman explains how a unified data stack solves challenges and delivers on the promise of AI.
In this video interview, Nick Brown with Uber discusses the public sector’s status-quo approach to providing transportation services and the benefits of a modern alternative.
As AI increasingly becomes an intermediary between government organizations and the public, the structure of information begins to matter as much as the content itself. It is not a shift in messaging — it is a shift in how data is read.
AI is embedded in government operations, and agencies need a proactive approach to data governance in order to mitigate risk — and foster trust.
As government organizations make greater use of AI, their privacy risks are expanding beyond traditional data protection. Critical infrastructure sectors must address new challenges related to data aggregation and accountability for AI-assisted decisions, among other concerns. To navigate this landscape successfully, organizations must enforce strong privacy protections to sustain innovation while maintaining public trust.
RDMA is a fascinating approach to “sharing memory” without having to burden a CPU. Learn why, and why AI data centers and cloud vendors use it.