Overview of Large Language Models (LLMs)

Understanding Large Language Models

If these are the questions you’ve been mulling over, you’ve come to precisely the right place. On this page, we’ll cover:

  • What are large language models?
  • How do large language models work?
  • What are the business benefits of large language models?
  • Large language model examples

Keep reading to find out more.

What are large language models?

Large language models, or LLMs, are a sub-type of artificial intelligence capable of generating and analyzing text or code (among other capabilities). The basic idea is that a human user enters a question or prompt, and the LLM then produces an answer that sounds as though it was human-written.

Large language models are powerful tools for businesses looking for efficiencies in redundant or repetitive tasks related to content generation, question-answering, summarization, translation, and more. Models like GPT-4 or Google’s PaLM models are capable of a dizzying array of tasks that can improve efficiencies within a team or make current teams productive. 

How do large language models work?

Large language models, OpenAI, Anthropic, Meta, or Google, built rely on the same general architecture. LLMs

LLMs are trained on massive datasets of existing text containing text from websites, books, wiki data, etc.  To train an LLM, developers feed this vast amount of human-written content so the model can learn the patterns and relationships between the words themselves (a more technical explanation can be found in OpenAI’s documentation). By analyzing that content, the LLM learns how to emulate human writing.

That’s not to say that the LLM understands the content it learns from, nor does it understand the meaning of the text it produces. It simply learns which words are statistically most likely to follow certain other words. That enables it to mimic the way humans write convincingly.

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Examples of Popular Large Language Models

Over the past year, there have been a significant number of large language models introduced to the public, both by private and public organizations. We’ll review the most popular below; however, this is not an exhaustive list. It is highly likely that, as a business, you’ll want to utilize one of the models that has ongoing investment.

  • GPT-4 & GPT-3.5 by OpenAI – These are, by far, the most widely-used models available as they’re used in OpenAI’s ChatGPT. They’re also the front-runner in capabilities at the time of writing, with GPT-4 being one of the most effective in generating text and GPT-3.5 being a faster, cheaper alternative.
  • Claude by Anthropic – Anthropic has released Claude Instant and Claude 2, powerful large language models with capabilities rivaling OpenAI’s models. Where they stand above OpenAI is in the context window, or how much text you can include in your message to the model.
  • PaLM (Bison / Gecko) by Google – Google has been at the forefront of LLMs, introducing the concept of transformers and making the industry feasible. Google offers two models, Bison and Gecko, to the public, which are roughly equivalent in effectiveness and cost to OpenAI’s GPT-4 and GPT 3.5. You can access a version of this through Google’s Bard for free.
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Examples of Platforms Built to Interact with LLMs – 

  • ChatGPT – OpenAI built ChatGPT and offers GPT-3.5 and GPT-4, some of the most commonly used LLMs due to ChatGPT’s popularity. GPT-3.5 is known for being much faster, while GPT-4 has access to much more advanced data. ChatGPT includes a wide array of third-party plugins that create additional functionality within the platform. The downside of ChatGPT is that it is limited to OpenAI models and is not organized around team collaboration but rather a single user.
  • Poe – Quora built Poe and has a range of models from the OpenAI suite to Anthropic’s Claude Models. It is priced similarly but does not offer team collaboration or organizational features required for businesses.
  • TeamAI – TeamAI is explicitly built with team collaboration in mind. It’s model-agnostic, meaning you can use OpenAI, Google, or Anthropics models and even bring your API keys. It offers the same functionality as ChatGPT and Poe but is designed for businesses.

What’s the significance of Large Language Models to Business Leaders?

Generative AI is applied to content creation, customer service chatbots, code generation, and more. As the technology continues improving, more use cases will emerge across industries. 

For most business leaders, the possibilities may still seem unclear or vague. Nevertheless, the power to scale your operations, streamline tasks and add capacity to current staff is unquestionable. Generative AI offers significant potential to boost business productivity, efficiency, and revenues through the automation of tasks and enhanced decision-making.

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Let’s explore the specifics of how it may impact your team’s future:

  • Streamlined work activities: Generative AI can take over certain repetitive or rules-based work activities, while complementing human capabilities on more complex tasks. This could transform many occupations over time.
  • Collaboration with Customers and workforce: Generative AI acts as a collaborative tool for workers and provides personalized experiences for customers. Adoption considerations around trust, capabilities and change management exist and should be considered carefully.
  • Potential for Innovative Approaches: Advances in AI, particularly LLMs, allow many industries and sectors to innovate with their process or even strategic approaches to their product or service delivery. 

Generative AI offers immense potential value but also disrupts existing ways of working. 

TeamAI was built for business use cases.

Are you looking for an AI tool you can use to help you generate content and streamline your business processes? TeamAI is the perfect solution. 

TeamAI is that it’s model-agnostic. That means it can always harness the best LLM, and if a different LLM becomes the best next week, TeamAI can switch to using that LLM.

TeamAI offers collaborative tools from prompt libraries to simple use organizational message architecture. This allows you to collaborate within a ChatGPT-like environment with your entire team.

Check out your free workspace now!

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