{"id":8921,"date":"2025-03-06T07:24:00","date_gmt":"2025-03-06T07:24:00","guid":{"rendered":"https:\/\/www.salesforce.com\/?p=8921"},"modified":"2025-03-06T07:23:39","modified_gmt":"2025-03-06T07:23:39","slug":"what-are-large-language-models","status":"publish","type":"post","link":"https:\/\/www.salesforce.com\/ap\/blog\/what-are-large-language-models\/","title":{"rendered":"What are Large Language Models (LLMs)?"},"content":{"rendered":"\n

As businesses look for ways to serve customers more efficiently, many are realising the benefits of generative AI<\/a>. This technology can help you simplify your processes, organise data, provide more personalised service, and more. What powers generative AI<\/a>? Large language models (LLMs) \u2014 which allow generative AI to create new content from the data you already have.<\/p>\n\n\n\n

Most importantly, generative AI technology<\/a> can save time on tedious processes, so you can provide better care for your customers and focus on big-picture strategies. Let\u2019s dig into how generative AI can help your business do more, and learn more about large language models.<\/p>\n\n\n\n

What are large language models?<\/h2>\n\n\n\n

Generative AI<\/a> is powered by large machine learning models that are pre-trained with large amounts of data that get smarter over time. As a result, they can produce new and custom content such as audio, code, images, text, simulations, and video, depending on the data they can access and the prompts used.\u00a0<\/p>\n\n\n\n

To put things into everyday context, large language models provide answers depending on how a question is phrased. For example, \u201c<\/strong>what are LLMs and how can they help my business?<\/em><\/strong>\u201d<\/strong> versus \u201cwhat are LLMs and what value can they bring to my business?\u201d<\/em><\/strong> will yield different results. Although the questions are similar, responses can vary by context.<\/p>\n\n\n\n

Because these models use natural language processing and machine learning capabilities, LLMs respond in a human-like, coherent, and relatable way. As a result, they excel in tasks such as text translation, summarisation, and conversations. <\/p>\n\n\n\n

With generative AI helping businesses perform these tasks<\/a>, trust has to be at the core of your efforts. To make sure you\u2019re using this technology responsibly, you can invest in a customer relationship management platform that has an AI-focused trust layer<\/a> \u2014 which anonymises data to protect customers\u2019 privacy.\u00a0<\/p>\n\n\n\n

A trust layer built into a generative AI landscape can address data security, privacy, and compliance requirements. But to meet high standards, you must also follow guidelines for responsible innovation<\/a> to ensure that you\u2019re using customer data in a safe, accurate, and ethical way.<\/p>\n\n\n\n

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State of the AI Connected Customer<\/h2>\n\t\t\t\t\t\t\t

Discover how the growing use of AI, including generative AI and agents, is shaping customer sentiment, expectations, and behaviours.<\/p>\n\t\t\t\n\t\t\t\n\t\t\t\t\t\t\t

\n\t\t\t\t\tGet the report<\/a>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\n\t\t
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How do large language models work?<\/h2>\n\n\n\n

Advancements in computing infrastructure and AI continue to simplify how businesses integrate large language models into their AI landscape. While these models are trained on enormous amounts of public data, you can use prompt templates that require minimal coding to help LLMs deliver the right responses for your customers.<\/p>\n\n\n\n

Furthermore, you can now create private LLMs trained on domain-specific datasets that reside in secure cloud environments. When a LLM is trained using industry data, such as for medical or pharmaceutical use, it provides responses that are relevant for that field. This way, the information the customer sees is accurate.   <\/p>\n\n\n\n

Private LLMs reduce the risk of data exposure during training and before the models are deployed in production. You can improve prediction accuracy by training a model on noisy data, where random values are added in the dataset to mimic real world data before it\u2019s cleaned. <\/p>\n\n\n\n

It\u2019s also easier to maintain an individual\u2019s data privacy<\/a> using decentralised data sources that don\u2019t have access to direct customer data. As data security and governance become a top priority, enterprise data platforms that feature a trust layer are becoming more important.<\/p>\n\n\n\n

Businesses can also leverage how LLMs work with other kinds of AI. Imagine using traditional AI to predict what customers may plan to do next (based on data from past behaviour and trends), and then using a LLM to translate the prediction results into actions. <\/p>\n\n\n\n

For example, you can use generative AI to build personalised customer emails with offers, create marketing campaigns for a new product, summarise a service case, or write code to trigger actions such as customer recommendations. <\/p>\n\n\n\n

These large language models save time and money by streamlining manual processes, freeing up your employees for more enterprising work. <\/p>\n\n\n\n

Now that you\u2019ve learned what generative AI can do, let\u2019s see how you can use it to help your business. <\/p>\n\n\n\n

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Learn about ethical AI<\/h2>\n\t\t\t

AI technology is only as good as the data it draws from. With this lesson on Trailhead, Salesforce\u2019s free learning platform, discover how you can remove biases from your data and develop AI in your company responsibly.<\/p>\n\t\t\t\n\n

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4 ways generative AI can help your business<\/h2>\n\n\n\n

The sky’s the limit when it comes to ways you can use generative AI for your business<\/a>.\u00a0<\/p>\n\n\n\n

LLMs are great at recognising patterns and connecting data on their own. Predictive and traditional AI, on the other hand, can still require lots of human interaction to query data, identify patterns, and test assumptions.<\/p>\n\n\n\n

Feeding from customer data in real time, generative AI can instantly translate complex data sets into easy-to-understand insights. This helps you and your employees have a clearer view of your customers, so you can take action based on up-to-date information.<\/p>\n\n\n\n

Now let’s dive into some use cases where large language models can help your business.<\/p>\n\n\n\n

Using sentiment analysis to gain context into post-purchase actions<\/strong><\/h3>\n\n\n\n

Sentiment analysis can help marketing, sales, and service specialists understand the context of customer data for post-purchase actions. For example, you can use LLMs to segment customers based on their data, such as using poor reviews posted on your brand\u2019s website. These insights can help you act immediately on negative feedback. A great marketing strategy would be sending a personalised message offering the customer a special deal for a future purchase. <\/strong>This can help improve <\/strong>brand loyalty, customer trust, retention, and personalisation.<\/p>\n\n\n\n

Generating email text for marketing campaigns<\/strong><\/h3>\n\n\n\n

Text generation can help marketers reduce the time that they spend preparing campaigns. Generative AI can produce recommendations, launch events, special offers, and customer engagement opportunities for your social media platforms. Then, you can polish up the text to make sure it\u2019s in your company\u2019s voice and tone. For example, you can use the copy produced by generative AI to deliver personalised emails informing customers about a new product launch. This helps to improve personalisation, giving your customers a more consistent experience.<\/p>\n\n\n\n

Surfacing related cases for service agents <\/strong><\/h3>\n\n\n\n

Case summarisation can help service agents to quickly learn<\/a> about customers and their previous interactions with your business. Cases provide customer information such as feedback, purchase history, issues, and resolutions. Generative AI can help with recommending similar customer cases, so an agent can quickly provide a variety of solutions. This results in faster resolutions, time and cost savings, and happier customers. <\/p>\n\n\n\n

Automating basic code generation<\/strong><\/h3>\n\n\n\n

Automation helps developers and integration specialists generate code for basic but fundamental tasks. For example, you can use code written by large language models to trigger specific marketing automation tasks, such as sending offers and generating customer message templates. This way, the overall language is consistent, personalised for the customer, and in your company\u2019s voice. Automation can save time and improve productivity, allowing developers to focus on tasks that require more attention and customisation.<\/p>\n\n\n\n

When used as part of a hybrid AI strategy<\/a>, large language models can complement various predictive capabilities<\/a> and drastically improve productivity. While generative AI can do so much, this technology still needs human guidance to be most effective for businesses. Generative AI can surface the insights you need to make decisions that can move your business forward. <\/p>\n\n\n\n

Think of it like a smart, automated assistant for your company, handling time-consuming tasks so your employees can work on complex problem-solving. When you blend the power of generative AI with the knowledge and expertise your company can provide, you\u2019ll be able to do more for your customers.<\/p>\n\n\n\n

Urvi Shah, Staff Technical Writer, contributed to this blog post.<\/em><\/p>\n","protected":false},"excerpt":{"rendered":"

Generative AI can help businesses run more efficiently and better connect with customers. Learn more about large language models, the technology that powers it all.<\/p>\n","protected":false},"author":466,"featured_media":8920,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"sf_justforyou_enable_alt":true,"optimizely_content_id":"76ddd2906e09434e9e5d056469b2dc7b","post_meta_title":"","ai_synopsis":"","_jetpack_memberships_contains_paid_content":false,"footnotes":""},"sf_topic":[528,5,479,28,4,540,18,73,24,14,561,482,23,666],"sf_content_type":[],"coauthors":[307],"class_list":["post-8921","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","sf_topic-salesforce-platform","sf_topic-marketing","sf_topic-automation","sf_topic-customer-experience","sf_topic-marketing-cloud","sf_topic-data","sf_topic-digital-transformation","sf_topic-innovation","sf_topic-future-of-work","sf_topic-it","sf_topic-personalisation","sf_topic-generative-ai","sf_topic-artificial-intelligence","sf_topic-mulesoft"],"yoast_head":"\nWhat Are Large Language Models (LLMs)? | Salesforce<\/title>\n<meta name=\"description\" content=\"Generative AI can help businesses run more efficiently. 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