Building Trustworthy Data Foundations for AI

A plethora of reports highlight the prevalence and dangers of AI hallucinations and other forms of inaccuracies resulting from AI applications. These errors can be traced to many different root causes, but the solutions boil down to a few methods: restrict the content to a carefully defined and structured set of validated information, protect the application through governance and monitoring, and evaluate the output to provide continuous improvement.

Enhancing AI Reasoning With Knowledge Graphs and GraphRAG

There is a disconnect happening with AI that cannot be ignored. A model can retrieve information, summarize it, or generate an answer, but it cannot determine whether the answer reflects how the business works or if it's truly correct. The limitation is not model intelligence but missing context. Using connected data, semantic relationships, and graph-based retrieval improves AI reasoning, contextual understanding, and decision making.

Nuances of Build-or-Buy Decisions

The intricacies of the time-honored question of whether to build or buy take on new dimensions when it comes to enterprise AI. Organizations must not only account for traditional considerations like cost, time-to-market, and proof of concepts but also for those that are unique to advanced machine learning and language model deployments.

The Power of RAG

Think back a few years to OpenAI's initial introduction of its generative AI (GenAI) chatbot—the excitement, the promise of marvelous opportunities, the sense of a change for the better. It wasn't long before the euphoria of GenAI wore off and people started noticing that large language models (LLMs) could produce absolutely fabulous results, but they could also deliver flawed information that looked plausible but was untrue.

Zuvu AI and Vana Collaborate on Decentralized AI in the Bittensor Ecosystem

Zuvu AI and Vana are announcing a strategic partnership to advance decentralized AI by integrating user-owned data, permissionless compute, and economic incentives.

SSI Strategy and Metalmind Collaborate on Life Sciences Enterprise AI Solutions

Through this partnership, SSI Strategy will leverage Metalmind's advanced capabilities in natural language processing (NLP) and large language models (LLMs) to enhance its service delivery.

On Demand Webinar: MIT Scaling Agentic AI Pilots

Agentic CX AI Frontline Report

Gartner® Report: How Leaders Avoid the Top 10 Operational Issues When Scaling AI

Forrester Report: AI Agents Reshape The Customer Service Workforce In Dramatic Ways