Shelf
Data mesh and data fabric are two architectural paradigms that are shaping the future of data management and analytics. At their core, both aim to address the complexities of handling vast and diverse data in modern organizations, but they approach the challenge from different angles. In this...
Artificial intelligence engines need data to learn and operate, but the data you and I find meaningful is foreign to machines. Machines need data translated to their preferred language: math. This conversion happens with the help of vectors. What are vectors in machine learning? Vectors are...
Synthetic data is artificially generated data that imitates real-world data without using actual information. It is generated through algorithms and statistical techniques to capture the same patterns and characteristics found in real data. Instead of relying on sensitive or private data,...
We encounter content chunks every day. Think of a recipe. A recipe contains content components like a title, a list of ingredients, cooking times, pictures of food, and instructions that contain individual steps. These are “chunks” that together compose a recipe. The process of chunking this...
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...
ChatGPT and other generative AI platforms are transforming how we access information, answer questions, and even create and interpret art. But there are limitations when it comes to performing more complex tasks like planning an event, or chaining multiple steps together like conducting buyer...
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...