In the rapidly evolving world of AI, the ability to customize language models for specific industries has become more important. Although large language models (LLMs) are adept at handling a wide range of tasks with natural language, they excel at general purpose tasks as compared with specialized tasks. This canContinue Reading
This post is co-written with Vladimir Turzhitsky, Varun Kumar Nomula and Yezhou Sun from MSD. Generative AI is transforming the way healthcare organizations interact with their data. Large language models (LLMs) can help uncover insights from structured data such as a relational database management system (RDBMS) by generating complex SQLContinue Reading
Resilient architectures are the foundation upon which successful businesses are built. However, keeping up with the latest advancements and making sure your systems are resilient can be a daunting task. Between monitoring, analyzing, and documenting architectural findings, a lack of crucial information can leave your organization vulnerable to potential risksContinue Reading
Thomson Reuters, a global content and technology-driven company, has been using artificial intelligence and machine learning (AI/ML) in its professional information products for decades. The introduction of generative AI provides another opportunity for Thomson Reuters to work with customers and advance how they do their work, helping professionals draw insightsContinue Reading
In today’s world, effective communication is essential for fostering inclusivity and breaking down barriers. However, for individuals who rely on visual communication methods like American Sign Language (ASL), traditional communication tools often fall short. That’s where GenASL comes in. GenASL is a generative artificial intelligence (AI)-powered solution that translates speechContinue Reading
One of the most common applications of generative artificial intelligence (AI) and large language models (LLMs) in an enterprise environment is answering questions based on the enterprise’s knowledge corpus. Pre-trained foundation models (FMs) excel at natural language understanding (NLU) tasks, including summarization, text generation, and question answering across a wideContinue Reading
This post is co-written with Aishwarya Gupta, Apurva Gawad, and Oliver Cody from Twilio. Today’s leading companies trust Twilio’s Customer Engagement Platform (CEP) to build direct, personalized relationships with their customers everywhere in the world. Twilio enables companies to use communications and data to add intelligence and security to everyContinue Reading
Media and entertainment companies serve multilingual audiences with a wide range of content catering to diverse audience segments. These enterprises have access to massive amounts of data collected over their many years of operations. Much of this data is unstructured text and images. Conventional approaches to analyzing unstructured data forContinue Reading
Name entity recognition (NER) is the process of extracting information of interest, called entities, from structured or unstructured text. Manually identifying all mentions of specific types of information in documents is extremely time-consuming and labor-intensive. Some examples include extracting players and positions in an NFL game summary, products mentioned inContinue Reading
This is a guest post co-written with Ori Nakar from Imperva. Imperva Cloud WAF protects hundreds of thousands of websites against cyber threats and blocks billions of security events every day. Counters and insights based on security events are calculated daily and used by users from multiple departments. Millions ofContinue Reading
