ChatGPT/LLMs for Corporates
What is the current hype about for ChatGPT?
ChatGPT is like the real life version of Iron Man’s Jarvis. It possesses the knowledge of the internet, allowing you to ask questions and get answers, create content, get recommendations, and even code!
From a technical perspective, ChatGPT is a Large Language Model (“LLM”) created by Open AI. LLM is a type of natural language processing model that is based on deep learning and trained on massive amounts of text data (basically the entire internet).
Over the past couple of years, companies have been using LLMs to solve typical NLP use cases such as question/answer, chatbot, sentiment analysis, summarization of articles and classification of text.
ChatGPT takes LLMs to the next level by creating a chat version of a LLM that respond with human like answers to many types of questions.
In summary, LLMs is a more general term that describes a class of language models, while ChatGPT is a specific model designed for conversational applications. While ChatGPT is a type of LLMs, not all LLMs are designed for conversational applications like ChatGPT.
What are some usecases for corporates using LLMs and ChatGPT?
LLMs, such as ChatGPT, have a wide range of potential use cases for corporates, including:
Chatbots and Virtual Assistants:
ChatGPT/LLMs can be used to create chatbots and virtual assistants that are much better than previous chatbots. LLMs understands and generates very human-like answers that makes you think you are talking to a human.
Here are some examples:
Knowledge Management: This allows ChatGPT/LLMs to answer questions that is specific to a company. By feeding PDFs and Word documents to ChatGPT/LLMs, ChatGPT/LLMs can learn a corporation's internal knowledge base, thereby allowing employees and clients to ask questions and receive accurate answers quickly and easily.
Customer Service: ChatGPT/LLMs can be used to improve customer service by providing intelligent and personalized responses to customer inquiries. By analysing customer messages and providing relevant and accurate responses, ChatGPT/LLMs can help companies provide fast and efficient customer support.
Lead Generation: ChatGPT/LLMs can be used to engage with potential customers and generate leads by acting human-like as well as persuading the client to be interested in the company.
ChatGPT/LLMs can be used to quickly generate high-quality content, such as product descriptions, social media posts, and even entire articles. Currently, many digital marketing and content generation companies are leveraging ChatGPT extensively.
Here are some examples:
Blogging: ChatGPT/LLMs can be used to generate ideas for blog posts and even draft entire articles. By providing the AI language model with a topic, it can produce a well-written, informative article that can be used for a company's blog.
Social Media: ChatGPT/LLMs can be used to generate social media posts for platforms like Twitter, LinkedIn, and Facebook. These posts can be tailored to the brand's voice and style, while also incorporating keywords for search engine optimization (SEO).
Email Marketing: ChatGPT/LLMs can be used to generate subject lines and body copy for email marketing campaigns. By providing ChatGPT with information about the audience and campaign objectives, it can create personalized and engaging emails.
Product Descriptions: ChatGPT/LLMs can be used to generate product descriptions that are informative and engaging. This is particularly useful for eCommerce companies that have a large number of products and need to create descriptions quickly.
Writing tenders, proposals and any text related documents: ChatGPT/LLMs can be used as a reference for best practices in writing tenders or proposals. By asking ChatGPT/LLMs for ideas, companies can reduce time spent writing tenders, proposals or text related documents by half. For example if you need to write an internal procedure, you can ask ChatGPT/LLMs what is the best practice for the procedure and reference it to write the rest.
ChatGPT/LLMs have also been helping programmers to program faster. As ChatGPT/LLMs been trained on numerous code and programs, it can leverage the best practices to help programmers to do the following:
Code Generation and Code Completion: ChatGPT/LLMs can be used to create code from scratch as well as suggest code completion options. By analysing the code and the programmer's style, ChatGPT/LLMs can suggest the most appropriate options, thereby saving time and reducing errors.
Optimizing code: There are programmers who feed in their code to ChatGPT/LLMs and ask how ChatGPT/LLMs can improve and optimize the code. ChatGPT/LLMs will find new ideas to improve the code and make the entire program more efficient.
Documentation: ChatGPT/LLMs can be used to generate documentation for code libraries, APIs, and other software projects. For example, a programmer can feed ChatGPT a program and ask it to help comment the code or to create a document that explain how to use such code. It will save the programmer a lot of time in creating such documentations.
Project and Knowledge Management:
ChatGPT/LLMs can help with knowledge management in a company. ChatGPT/LLMs has the knowhow in different project management tools and can provide guides and best practices on how best to use them.
Here are some examples:
Documentation: ChatGPT/LLMs can be used to generate documentation, such as meeting notes, project plans, and reports. For example, a user can put in raw meeting notes into ChatGPT and ask it to create a detailed report.
Standard Operating Procedures: If you let ChatGPT/LLMs know what tools you use such as Google Workspaces, Notion or Quickbooks, ChatGPT/LLMs can write out standard operating procedures with a step-by-step guide. This allows the company to keep track of finance, workload, milestones and others.
Above are just a sample of use cases with ChatGPT and LLMs. Overall, LLMs have the potential to enhance a wide range of corporate processes and functions, by improving accuracy, increasing efficiency, and reducing costs.
What are some limitations for ChatGPT/LLMs and problems for corporate use of ChatGPT/LLMs?
Inability to Reason/ Hallucination: While ChatGPT/LLMs can generate text that appears human-like, they do not actually understand the meaning of the text or have the ability to reason about it. This means ChatGPT may generate nonsensical or inaccurate responses if the input is ambiguous or the context is not clear. ChatGPT are known to hallucinate and make up things and pretend it’s true. This will have a negative effect on the client when it cannot trust the contents.
Limited Context: ChatGPT/LLMs have a limited understanding of context and may not be able to accurately capture the meaning of complex or nuanced text. This can lead to errors or misunderstandings in language translation, sentiment analysis, and other tasks. As of Feb 23rd 2023, ChatGPT has a context of only 3000 words and will forget things after, hence it is crucial to have AI consultants to guide ChatGPT/LLMs to the correct answer. (Link)
Resource Intensive: ChatGPT/LLMs require significant computing resources to train and deploy, which can be a barrier for smaller organizations or those with limited resources. With ChatGPT and GPT-3.5 it will be almost impracticable for a SME to host a server that is on 24/7 as the resources is very costly. If the SME would like to retrain the model, it will be even more expensive.
Fail in simple scenarios: While ChatGPT/LLMs can generate text that appears human-like, they will fail in many simple logic tests such as simple mathematics that a calculator can easily do. That is because ChatGPT is created to predict the next word, but it does not understand its logic.
Limited to Training Data: LLMs will only understand knowledge that it is being trained on unless it is given outside prompts. In ChatGPT’s case, it is only trained up to data from 2021, so it will not respond to answering questions on a more recent context.
Bias: LLMs may reflect the biases of the data used to train them. If the training data contains biased or discriminatory language, the model may reproduce these biases when generating or analysing text. This is a problem for companies as the LLM might say things that does not reflect the corporate image.
Personal Data: If you use paid LLM APIs or ChatGPT APIs, your personal data and your client’s personal data will be sent to the company that owns the API. Most of the time your client’s data will be used as data for the company to train on and might potentially be leaked to the world.
It's important to be aware of these limitations and to use LLMs in combination with human expertise and judgment to ensure the best possible outcomes.
Does ChatGPT/LLMs understand different languages?
Yes, ChatGPT has been trained on a large dataset of text from multiple languages, so it can understand and generate text in many different languages. However, its ability to understand and generate text in a particular language may depend on the amount and quality of training data available in that language.
Some of the languages that ChatGPT is particularly confident on include English, Spanish, French, German, Italian, Portuguese, Chinese, Japanese, Korean, and Arabic, as there is a large amount of high-quality training data available for these languages. However, it can still understand and generate text in many other languages to varying degrees, depending on the availability and quality of training data for those languages.
How can a AI consultancy like ThinkCol help you with ChatGPT/LLMs?
An AI consultancy like ThinkCol can help you with ChatGPT/LLMs in several ways, including:
Identifying Use Cases: An AI consultancy like ThinkCol can help you identify potential use cases for ChatGPT/LLMs within your organization, and determine where these models can be most effective in improving operations, customer experience, or other key metrics. ThinkCol will also guide you on where the limitations are with the ChatGPT/LLMs and what you have to be careful about.
Solving ChatGPT/LLMs Limitations and ethical considerations: As mentioned above, there are a lot of limitations with ChatGPT/LLMs such as data privacy, bias, hallucination, expensive deployment and limited context. However, ThinkCol have already came up with solutions that have solved these problems, which will allow corporations to use ChatGPT/LLMs with confidence.
Integration with Existing Systems: An AI consultancy such as ThinkCol can help you integrate ChatGPT/LLMs with existing systems and processes, such as CRM, ERP, and other enterprise applications. They can also help you develop custom applications and interfaces for ChatGPT/LLMs to make them more accessible and user-friendly for your employees or customers.
Prompt Engineering: Prompt engineering involves designing and crafting high-quality prompts, which are the text inputs given to the ChatGPT/LLMs to generate its responses. Well-crafted prompts can help guide the ChatGPT/LLMs towards generating more accurate and relevant responses, while poorly designed prompts can lead to inaccurate or irrelevant responses. Here at ThinkCol, we have the relevant experience in crafting the right prompts to ensure you leverage the most out of ChatGPT/LLMs.
Overall, an AI consultancy like ThinkCol can provide expert guidance and support for all aspects of ChatGPT/LLMs development and implementation, helping your organization get the most out of this powerful technology.
How much internal data needs to be given to ChatGPT/LLMs to learn?
If your company wants to build a ChatGPT or LLM catered to your language and to your company’s specific information (i.e. creating a ABCCompanyGPT), there are two ways of doing it.
For the first option, you can try to train the existing model on a dataset that is specific to your domain of interest. This helps the model to learn the specific language and terminology related to the domain, and improve its performance on tasks related to that domain. However currently as of February 23rd 2023, ChatGPT does not allow you to train on top of it. Other LLMs may also requires a lot of machine compute and resources that most SME will not have.
Another option is to leverage on an AI consultancy like ThinkCol and use their expertise to help you with prompt engineering. Prompt engineering and embeddings can be used to help GPT3.5 or other LLMs to understand a corporate domain by providing it with examples of typical questions and answers that might be encountered in that domain. This can be done through the creation of a prompt, which is a specific set of instructions or questions given to the model to help it understand the context and purpose of a particular task.
For example, if you want to build an ABCCompanyGPT that answers questions from clients about a particular company, you might provide it with a set of prompts that include information about the company's products, services, history, and policies. You could also include examples of common questions that clients might ask, such as "What are your hours of operation?" or "What is your return policy?".
ThinkCol specializes in using Machine Learning and NLP techniques to find the relevant information based on a question and feed that into a prompt. This allow the LLM to understand the context and answer with relevancy.
How can we use ChatGPT in Hong Kong ?
As of February 23rd, 2023, ChatGPT, along with other GPT models, are blocked in Hong Kong. However there are a couple ways that you can get around that. 1) Since Microsoft has a partnership with OpenAI, you can apply for access through Azure. Microsoft will approve such access on a case by case basis. However, as of February 23rd, even if you are approved by Microsoft, you will only have access to GPT 3.5 and not ChatGPT. Microsoft promise that in the future, ChatGPT will be avaliable through Azure but they are currently unsure about the date. 2) Unoffically, you can sign up for an account in another country. This requires a phone number in the other country during sign up.
There are of course additional ways that you can access ChatGPT in Hong Kong. Please contact us if you would like to learn more!
How can ThinkCol help you with your ChatGPT and LLM needs?
As mentioned above, ChatGPT/LLMs have a lot of limitations that ThinkCol has expertise to circumvent. ThinkCol has been using GPT and LLM since 2020, and have been doing NLP projects since 2016. ThinkCol have extensive research into prompts and leveraged Open AI APIs to create solutions for different clients. For example we have pitched a Hong Kong movie director to write a story using GPT-2 back in 2020. We also have multiple use cases where we leverage LLM technology to perform NLP tasks for a real estate conglomerate, a government organization, a multinational bank as well as a large retail store.
We have the solution and expertise to bypass the limitations of LLM and ChatGPT such as data privacy, pricing, bias, hallucination as well as LLM’s limited context.