We live in an on-demand world. Customers expect every product delivered to the doorstep, every service ordered online, and any information they seek immediately available at their fingertips. When customers have questions, they expect answers–on demand. As customer expectations have risen, so have...
The field of Natural Language Processing (NLP) has witnessed significant advancements, yet it continues to face notable challenges and considerations. These obstacles not only highlight the complexity of human language but also underscore the need for careful and responsible development of NLP...
In machine learning, embeddings are a technique used to represent complex, high-dimensional data like words, sentences, or even entire documents in a more manageable, lower-dimensional space. An analogy would be nice. Right. Think about Lego bricks. A lot of them. High-dimensional data is like the...
Neural networks involve a series of algorithms designed to recognize patterns, interpret data, and make decisions or predictions. They are modeled loosely after the human brain’s architecture. Neural networks have become a cornerstone of AI technologies alongside others, such as rule-based...
We need more than just artificial intelligence. We need virtual experts that are accurate, authoritative, and effective. It’s not enough to deploy AI technologies to answer customer service questions, assist a doctor’s medical diagnosis, identify a negotiator’s key clauses in a contract, provide...
Semantic search goes far beyond the words that people use in their searches, to interpret the intent behind the words, and the greater context in which people are asking. Traditional lexical or keyword-based technologies cannot accomplish this. The relevance and actionability of information that...
Listing use cases for artificial intelligence (AI) is like describing how to use the internet — the AI implementation examples are nearly infinite, constrained only by the inventive minds behind the wheel. AI is being implemented in business practically everywhere, from personalizing sales...
Generative artificial intelligence (GenAI) has emerged as a powerful tool for content creation, but often requires a human in the loop to ensure the outputs are valuable. The value of GenAI includes productivity gains, opportunity for revenue growth, and better accuracy for your organization’s...
OpenAI introduced artificial intelligence (AI) to the general public and their latest keynote emphasized their influence on the development of this new technology. Since Chat-GPT was unveiled in November 2022, every major tech company has announced their own AI initiative, but OpenAI remains the...
In our first entry in our series of future-proofing for artificial intelligence (AI), we discussed the inevitability of AI disruption and how your organization should prepare to manage change. In this second entry in the series, we focus on what your AI strategy needs to manage risk, evaluate ROI,...
Customers have more ways to communicate with your organization than ever before, which presents a challenge for designing a seamless customer service journey. Multiple touchpoints, disconnected experiences, and increased costs can hinder customer satisfaction. Overcoming these challenges requires...
Your customers already want AI Customer Service. Artificial intelligence (AI) and Generative AI (GenAI) have created a new era of automating the most vital aspects of customer service. The results have shown boosted employee productivity, enhanced accuracy, and improved self-service containment rate.