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Hardware and Chips > Features
Hardware and Chips are fundamental to the development and deployment of AI technologies. They provide the computational power, efficiency, and scalability needed to train and run complex AI models. Advances in hardware drive innovation, enable new applications, and make AI technologies more accessible and effective.

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The Rise of Agentic AI: Why Your AI Agent Is Clueless

Enterprises are rushing to adopt so-called "agentic AI," systems that promise to not just answer questions, but also take actions, automate tasks, and drive decisions. In theory, these agents can draft emails, update records, generate product specs, or flag anomalies without human involvement. In practice? Most deployments don't make it past the demo.

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.

Architecting a Modern Data Stack for AI Agents

Even if you've got a brand-new business model based specifically on the capabilities of a language-centered AI agent, you still have to deal with time-honored challenges such as disparate and scattered data, slow response, finding necessary information, and trusting that information.

Building Enterprise-Grade AI Applications

As the C-suite continues to marvel at AI, many companies are settling into the early stages of undertaking enterprise AI adoption in targeted areas now that the "winner takes all" rush to apply AI technologies to outpace the competition is mostly gone.

OpenAI Faces Wrongful Death Lawsuit

Now, OpenAI faces its first known wrongful death lawsuit after a teen died by suicide further spurred on by ChatGPT, The New York Times reports.

Exploring the ‘SIX D’S’ Framework for Language Model Training and AI Agent Creation

The integration of AI into customer service and support is by no means a futuristic vision—it is a present-day reality. AI is reshaping how organizations engage with their customers.

AI Techniques Powering Enterprise Productivity: From Automation to Augmented Intelligence

AI stands beyond experimental status—it is a founding power for corporate productivity delivery. From automating repetitive workflows to enhancing complex decision making, AI transforms how work gets done.

AI Enhances Customer Service in Several Ways

Although the initial seeds of generative AI (GenAI) were planted in the 1960s, for the most part it didn't come into full bloom until the introduction of ChatGPT in November 2022. Before that, GenAI had all but the most nascent use in business. As the technology entered the public consciousness, it spread across industries from entertainment to manufacturing to healthcare for a wide variety of uses, including customer service.

The Rise of GenAI and LLMs

In 1950, Alan Turing suggested a test to determine if computers could mimic human intelligence well enough that an impartial observer could no longer tell the difference. We are still talking about the Turing Test almost 75 years after its inception.

The AI-Driven Transformation of Enterprise Data Architecture

The past year has been an exhilarating one with AI and more specifically, generative AI (GenAI), quickly emerging as a transformative force, reshaping how businesses will operate, innovate, and interact with customers. As AI continues to gain prominence, its impact on enterprise data architecture is becoming increasingly apparent.

Developing a Strong AI Governance Framework

The exponential advancement of AI technologies necessitates the implementation of robust governance frameworks to guide their responsible development and deployment.

Transforming Customer Service with AI and Knowledge Management

Customer service and customer support operations are no strangers to AI technologies. AI has long been embedded in the interactions between companies and their customers.

Adding Meaning to Data: Knowledge Graphs, Vector Databases, and Ontologies

This article discusses the importance of context in enterprise data for generative AI (GenAI), and, in fact, for any AI initiative.

Elevating Enterprise Search With AI, ML, NLP, and LLMS

Information retrieval, now more commonly known simply as search, is one of the earliest manifestations of using AI. Consequently, enterprise search is inseparable from AI and one of the most meaningful beneficiaries of the exponential advancements recently achieved by machine learning (ML)—the most accomplished expression of statistical AI.

The Future of Work Chatbots, Voicebots, and Virtual Assistants

Enterprises increasingly rely on chatbots, voicebots, and virtual assistants to service more customers without adding to their staff count. These devices can be connected by a single underlying software platform, although there are several companies that use these devices independent of each other.

Upskilling and Reskilling in the Age of AI

The AI revolution is upon us. A tidal wave of AI technology is sweeping across businesses, fundamentally reshaping how employees, managers, and AI system developers approach their work.