Almost all sectors use some type of large language model (LLM). This technology powers some of the most well-known artificial intelligence (AI) tools organizations use today.
This short guide will underscore LLMs’ most common use cases and the problems they solve. After reading, you will understand this technology better and how to use it to address difficulties in your organization.
What are large language models?
An LLM is a technology with a deep understanding of language and uses this capability to complete specific tasks. Examples of these tasks include the following:
- Generating content
- Conducting research
- Responding to queries
- Organizing data
These models are specialized deep neural networks trained to generate text, video, images, or audio. Its widespread implementation can be attributed to its broad applicability. They help boost AI’s reach across industries and could support a new wave of creativity, research, and productivity.
How do they work?
Large language models use vast volumes of data to learn new things. As its name suggests, LLM and its capacity to learn depends on the size of the dataset it’s trained on.
However, the definition of large is changing, with new LLMs using extensive data sets that include nearly all that has been posted on the internet for a long time.
Developers feed data into an AI algorithm using unsupervised learning, which occurs when a model receives a dataset without specific instructions on what to do with it. Through this process, an LLM discovers new words and their concepts.
For example, a model could learn to differentiate between the two meanings of the word “glasses” based on context.
Aside from its self-learning capabilities, an LLM can also apply its knowledge to generate content, like texts or images. Read below to learn how this technology revolutionizes processes across various industries.
5 Use Cases for Large Language Models
With the recent advancements in technology, there are almost infinite applications for LLMs. They are unlocking new possibilities in various industries, including marketing, medical research, and content writing. Read on to learn five use cases for LLMs.
1. Chatbots for businesses
With recent advances in artificial intelligence solutions, businesses are ready to invest capital in chatbots. According to recent data, the chatbot market could grow to $1.25 billion by 2025.
Online businesses use AI-based chatbots or virtual assistants to provide fast and efficient customer service. Using LLM, these bots respond to routine inquiries and allow employees to focus on more challenging and strategic work.
LLM-powered chatbots allow entrepreneurs to use their employees’ labor hours effectively. This advantage can save time for staff while also reducing costs.
One example is the IBM Watson Assistant. Much like ChatGPT, this tool is a conversational AI solution that supports customer management. The platform can respond to queries using machine learning (ML) models and uses simulated conversations to complete a user’s intended action.
2. Content writing
LLMs can summarize, rewrite, and generate text, all of which are valuable content-writing capabilities. For example, ChatGPT can function like a search engine that remembers previous conversations. This capability can be beneficial for marketers who need help developing optimized content.
Marketers can even use this platform to draft emails. They can use ChatGPT for Gmail and write messages their subscribers can easily understand.
Some publications use LLMs to generate earnings reports. Users only have to input financial data into the AI-powered platform, and the solution produces a summary of company performance.
Meanwhile, others use LLMs to get summaries of complex news articles. Users display these summaries on their homepage and mobile app to give site visitors a quick look at current events.
3. Medical and research applications
Members of the medical community are busy trying out potential applications of LLM in medical practice. Most medical professionals handle administrative documentation, which can be time-consuming. They aim to use LLMs to lighten the burden of administrative workload.
Using LLMs, doctors can do the following tasks:
- Generate letters to insurance companies
- Write medical reports
- Explain diseases to patients in terms that they can easily understand
Meanwhile, researchers have also identified use cases for LLMs. They use AI solutions to write the first draft of their scientific manuscript. They can also use the tools to summarize the contents of previously published works.
In a 2022 research article, researchers studied the potential of LLMs to support the early diagnosis of dementia. They also examined how GPT-3 can help provide specialized interventions to meet unique patient needs.
4. Legal applications
LLMs can also assist legal professionals. For example, a junior attorney can use GPT-4 to do the following tasks:
- Look for relevant legal regulations
- Determine potential contradictions in documents
- Identify missed arguments
With these capabilities, an LLM can help attorneys focus on higher-level tasks that require analytical and critical thinking skills.
Compliance officers can also use AI solutions to automate the development of standardized document templates. This advantage ensures consistency in formatting, structure, and language. Moreover, the tool can simplify legal jargon and explain complex terms.
5. Fraud detection
Federal Trade Commission (FTC) data shows consumers lost $8.8 billion to fraud in 2022. Given this number, organizations must establish an effective fraud management system.
The process involves identifying, detecting, preventing, and responding to fraudulent activities. Fortunately, AI and ML technologies can help companies in this process.
These technologies can study large amounts of data and detect anomalies that may indicate fraud. Users can identify and prevent payment fraud, identity theft, and phishing attacks through AI-powered systems. Moreover, these tools can also adapt and learn new fraud patterns, improving their detection capabilities over time.
Discover How Powerful LLMs Can Help Your Organization
LLMs are powerful tools that can benefit any organization. This tech can analyze massive amounts of data, make predictions, understand natural language, and identify patterns. These capabilities make them crucial assets for various applications, such as customer service and decision-making processes.
However, it is crucial to remember that LLMs and other AI tools require significant resources and expertise to maintain and implement. Before relying on these tools, you must first understand the biases, limitations, and ethical concerns associated with LLMs.
Yes, LLMs can be powerful tools if you integrate them into your processes. However, you must ensure that your use of these solutions aligns with your organization’s goals and values.
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