Large Language Models are Taking Over
LLMs, or Large Language Models, are becoming increasingly popular in the realm of artificial intelligence due to their ability to generate shockingly human-like language. These AI models are trained on a large amount of textual data and can perform a variety of language-related tasks at a high degree of accuracy, including often performing better than most humans at text-related tasks. In this post, we’ll explore some of the many sprouting applications of large language models and how they are transforming various industries.
Natural Language Processing
One of the most significant applications of large language models is in the field of natural language processing (NLP). NLP is yet another (older) subfield of artificial intelligence that focuses on the interactions between humans and computers using natural language. LLMs have made significant contributions to NLP by improving the accuracy of language understanding, sentiment analysis, and machine translation.
Sentiment analysis is itself the process of identifying and categorizing opinions expressed in a piece of text. This has a wide utility for different contexts. It’s important for businesses as it helps them understand the sentiment of their customers towards their products or services. Political groups can also use this to learn more about what issues matter to their constituencies.
On the other hand, machine translation involves translating text from one language to another. Large language models can perform this task with decent accuracy and are employed by companies like Google and Microsoft.
LLMs can also be used for content creation. For example, OpenAI’s ChatGPT can write news articles, generate creative writing, and even increasingly write quality code. Several tools such as copy.ai have even popped up to help aspiring marketers reach their goals. Beyond generation LLMs are also used to assist with grammar and spell checking, restructuring already written thoughts, and even translation into other languages.
But they haven’t just found use with text content. Deep learning models that can generate artful and sophisticated imagery have also cropped up. An example is OpenAI’s Dall-E, which itself is based off of GPT-3. These images can then be used in everything from webtoons to advertisements, and yes, is even seen in the header for this very blog post.
Large Language Models have also proven to be a valuable tool in creating chatbots that can simulate much more natural conversations with users. As services and businesses move towards increasingly digital-first customer engagement, chatbots have become an essential asset in the toolbox. These LLM-infused chatbots can provide personalized responses to user inquiries and handle large volumes of customer interactions, freeing up human resources to focus on other important tasks.
Voice assistants such as Siri, and Google Assistant also are beginning to experiment and improve with the help of LLMs. It was recently unearthed that Amazon is even creating their own LLM to help run Alexa. These devices use NLP (mentioned earlier) to understand user commands and execute them. With the help of LLMs, voice assistants will become more accurate and efficient, turning them into an essential tool in the day-to-day lives of many people.
Near and dear to the team at Dart, Models like GPT-4 are also finding brand new and powerful applications in the field of project management. Since a lot of text information is created and stored in these tools, it only stands to reason that LLMs can help not just with the generation but also with search and structuring side of this data. At Dart LLMs help with filling out task properties such as descriptions, due dates, and even assignees. They can also help with breaking larger tasks into a discrete set of more easily manageable subtasks. With more to come this is certainly an exciting avenue of technological growth.
As we’ve seen, large language models (or LLMs) already have a wide range of applications across various industries. As these models continue to improve, we can expect to see even more exciting use cases in the near future. From improving natural language processing to enhancing content creation, chatbots, voice assistants and project management, large language models are proving to be a valuable tool across the board. As this new technology continues to improve and advance, it will become essential for businesses to leverage their power to stay competitive in a rapidly evolving digital landscape.