AI

Generative artificial intelligence (AI) models have become increasingly popular and powerful, enabling a wide range of applications such as text generation, summarization, question answering, and code generation. However, despite their impressive capabilities, these models often struggle with domain-specific tasks or use cases due to their general training data. To address this challenge, fine-tuning these models […]

Generative artificial intelligence (AI) applications powered by large language models (LLMs) are rapidly gaining traction for question answering use cases. From internal knowledge bases for customer support to external conversational AI assistants, these applications use LLMs to provide human-like responses to natural language queries. However, building and deploying such assistants with responsible AI best practices

Despite its limitations, the makers of MarioVGG think AI video could one day replace game engines.

This week on Politics Lab, we’re talking about AI’s potential impact on the election—and why it’s so hard to regulate nationwide.

This post was co-written with Jerry Liu from LlamaIndex. Retrieval Augmented Generation (RAG) has emerged as a powerful technique for enhancing the capabilities of large language models (LLMs). By combining the vast knowledge stored in external data sources with the generative power of LLMs, RAG enables you to tackle complex tasks that require both knowledge

As generative artificial intelligence (AI) continues to revolutionize every industry, the importance of effective prompt optimization through prompt engineering techniques has become key to efficiently balancing the quality of outputs, response time, and costs. Prompt engineering refers to the practice of crafting and optimizing inputs to the models by selecting appropriate words, phrases, sentences, punctuation,

Legislation addressing the crisis of deepfake porn is being proposed, passing, and failing at the state level all over the US. WIRED is keeping track of it all.

Kubernetes is a popular orchestration platform for managing containers. Its scalability and load-balancing capabilities make it ideal for handling the variable workloads typical of machine learning (ML) applications. DevOps engineers often use Kubernetes to manage and scale ML applications, but before an ML model is available, it must be trained and evaluated and, if the

Generative artificial intelligence (AI) foundation models (FMs) are gaining popularity with businesses due to their versatility and potential to address a variety of use cases. The true value of FMs is realized when they are adapted for domain specific data. Managing these models across the business and model lifecycle can introduce complexity. As FMs are

Many ecommerce applications want to provide their users with a human-like chatbot that guides them to choose the best product as a gift for their loved ones or friends. To enhance the customer experience, the chatbot need to engage in a natural, conversational manner to understand the user’s preferences and requirements, such as the recipient’s