Large Language Models (LLMs) have been making headlines in the world of artificial intelligence (AI) and natural language processing (NLP). These models can generate human-like text, answer complex questions, and write articles with minimal human input.
With recent technological advancements, LLMs have become more powerful than ever, raising excitement and concerns about their potential impact on society.
This article will explore what LLMs are, how they work, and their application in OpenChatKit, a popular open-source chatbot. We will also discuss the potential of using LLMs in Neurond’s projects.
What Is Large Language Models?
The recent growth of large distributed and parallel computational infrastructure, big data, and advanced Deep Learning architecture like Transformer has facilitated the development of Large Language Models (LLMs). This technology consists of a neural network with many parameters (approximately billions of parameters).
These models are trained on large quantities of unlabelled and curated text datasets using self-supervised learning. As mentioned, LLMs perform well on various tasks such as natural language understanding, question and answering, machine learning translation, name entity recognition, summarization, coding, and more.
Although LLMs have had a booming development recently, their upstart has been since 2018, with the original Transformer architecture. This led to a series of next deep learning architecture like BERT, RoBERTa, BART, T5, Flan T5, GPT-2, GPT-3, BLOOM, OTP, LLaMa, Alpaca, etc. The critical causality led to a new type of AI chatbot generation which is smart, descent, sentinel, and ethical in their responses. They made vibrant about the unlimited capability of supporting human beings in multi-disciplinaries.
Large Language Models’ Application: OpenChatKits
Coming as an open-source project, OpenChatKit provides a robust base to create specialized and general-purpose chatbots for various applications. It contains four key components:
- An instruction-tuned large language model
- Customization recipes to fine-tune the model
- An extensible retrieval system to augment the model with live-updating information
- A moderation model to filter inappropriate or out-of-domain questions
It costs you a monthly fee to approach this AI chatbot as it’s built for commercial purposes with the aid of big-tech companies like Microsoft, Google, Facebook, etc.
About the author
OpenChatKit is a collaboration between Together, LAION, and Ontocord. Together provides open-source foundation models for natural language understanding and generation. LAION, meanwhile, offers high-quality data annotation and curation services. The other company delivers data engineering and machine learning solutions.
Data input
These companies worked together to create the OIG-43M and moderation datasets. The former is a collection of 43 million high-quality instructions for conversational interactions. The latter combines inappropriate questions for chatbots.
Model architecture
OpenChatKit’s base model is GPT-NeoXT-Chat-Base-20B, a 20 billion parameter large language model based on EleutherAI’s GPT-NeoX model. It’s fine-tuned with the OIG-43M dataset, focusing on functions like multi-turn dialogue, question answering, classification, extraction, and summarization.
What Can Neurond Do with LLMs and OpenChatKit?
As a high-fidelity chatbot, OpenChatKit works in multiple languages. Thus, it can make a reliable response based on the context that we supplied to them.
Neurond has sagaciously customized and adapted OpenChatKit to our projects. We’ve achieved a new resounding success on our grounding product for financial customers to mine their huge document resources. Our Neurond AI Assistant is a highly professional communication tool with the exceeding ability to aid you in efficiently talking with your documentation dataset.
Our comprehensive test of OpenChatKit over a wide range of realistic documentation demonstrated its high competency in extracting essential information from both long-context and short-context forms that could reach 99% accuracy in our test cases dataset.
Regarding information summarization, we applied LLMs and OpenChatKit to summarize long-context office forms into condensed and coherent paragraphs efficiently. This saved the time of the client’s customers to capture the general meaning without the loss of critical data. The overall content is still nearly preserved with a high amount of intact information percentage while reducing the extreme form’s length.
The following specific use cases prove how we applied OpenChatKits in actual project situations.
Neurond’s Projects
Neurond can have LLMs run on different datasets and apply this technology in various of our use cases, from recruitment products to wealth and financial management projects.
#1 Question and Answering on Curriculum Vitae Forms:
Take our Dr.Parser as an example. The tool helps extract candidate information from resumes.
In this showcase, we forward a context to ChatBot, which describes the information of an applicant who applies to an IT company. It consists of the most important aspects of the candidate, like personal details, work experience, skills, education, and hobbies.
To extract the key information from the form, a set of standard questions will help mine them. For example: Below is the candidate’s CV. In the Answer section, you can ask about personal information to achieve the result.
Context
-------- Tran Minh Duy Automation - IOT Engineer Date of birth: August 7, 1998 Gender: Male Phone: 0941781010 Email: minhduy.tran0708@gmail.com Address: Ho Chi Minh city, Viet Nam Website: https://www.facebook.com/profile.phpid=100007077526120 -------- OBJECTIVE - Short term: have a stable job, gain experience and skills. - Long term: become an expert in the field of Technology and have the opportunity to become a manager or team leader. -------- EDUCATION August 2016 - August 2020 Ho Chi Minh University of Technology Major: Control And Automation GPA: 7.81/10 -------- WORK EXPERIENCE September 2020 - Present Công ty TNHH Hệ thống Tự Động New Ocean Automation - IOT Engineer Main responsibilities: - Directly participate in the company's projects. - Research and develop suitable solutions for customers. July 2019 - September 2019 Công ty Cổ phần Công Nghệ TTB Intern - Participate in Daiwa Lance project - Research and develop application for monitoring, control and data collection on the basis of cloud computing. August 2016 - August 2020 Ho Chi Minh University Of Technology Student - Completing graduation thesis - Project title: Process simulation, control and SCADA for pumping stations based on VPS centralization - Regularly implement big projects and assignments in the remaining school years -------- ACTIVITIES June 2017 - July 2017 Bach Khoa Green Summer Volunteer Campaign Volunteer -Together with other volunteers and local people in Ben Tre to build rural concrete roads and light up country roads. -Organize activities and distribute gifts to local children. -------- CERTIFICATIONS 2017 TOEIC Certificate with score 705 -------- SKILLS Programming Language C#, Python (basic) Database Microsoft SQL Server, MongoDB (basic) Big Data Hadoop (basic), Apache Spark (basic) Mobile Development Xamarin Form (basic), Flutter (basic) Web Development ASP.Net Core, HTML, css, js Microsoft Office Word, Excel, Powerpoint, Visio PLC, Scada Siemens, Rockwell, Delta Other tools Git, Docker (basic) © topcv.vn
Answer:
Q: What is the candidate’s name? A: Tran Minh Duy Q: What is the date of birth of the candidate? A: August 7, 1998 Q: What is his email address? A: minhduy.tran0708@gmail.com Q: What is his phone number? A: 0941781010 Q: What is his address? A: Ho Chi Minh City, Viet Nam Q: What is his website? A: https://www.facebook.com/profile.phpid=100007077526120 Q: Summarize his objective A: Short term: have a stable job, gain experience and skills. Q: What is the candidate’s education at the university? A: Ho Chi Minh University of Technology Q: What is his major? A: Control And Automation Q: What is his GPA score? A: GPA: 7.81/10
#2 Summarizing Customer financial form
The contract and registration forms are sometimes very long, preventing customers from capturing the main points. An explicit prompt initialization will provide the context and asks to summarize the input context so we can solve this problem.
For example, this is a LifeWRAP Individual Policy section which is extracted from Insurance Guide. The summary result of this section is as below:
Context:
LifeWRAP Individual Policy LifeWRAP is an insurance offering enabling members to access individual life insurance (including Death and TPD) and Income Protection insurance through the Fund. You can choose from a range of insurance products offered by a number of approved insurers. LifeWRAP Individual Policies are issued by the insurer and are subject to the terms and conditions of the particular policies taken out by us with the insurer on behalf of each individual member. Each policy is held by us as trustees of the Fund. In some cases, you may be able to purchase optional benefits from the insurer that are offered outside the Fund under separate or linked policies issued in your name. These benefits will be held by you directly rather than by us on your behalf. The insurance products are available under a LifeWRAP Individual Policy and are listed on our website. For more information regarding a particular product, please refer to the insurer’s product disclosure statement from the insurer or your financial adviser. Before considering a LifeWRAP Individual Policy, we recommend that you seek advice from a licensed or authorized financial adviser. Payment of benefits Access to insurance benefits: Insurance benefit payments may be paid to us as trustees of the Fund. Refer to page 22 for more information about accessing benefits when you make a claim. Under a LifeWRAP Individual Policy, if you satisfy the conditions for the payment of an insured benefit, the benefit may be paid to us as trustees of the Fund. For example, under the terms of a life insurance policy, if you die or if you become totally or permanently disabled, you will be paid a lump sum. Under the terms of an income protection policy, we may be paid the income payments from the insurer, or the insurer may pay the income payments directly to you. How to apply A LifeWRAP Individual Policy is only available through an adviser who is authorized by the insurance company that provides the policy. Your adviser will provide you with a quotation detailing the policy you wish to purchase and assist you with the application process. To apply for insurance, you first need to read this Insurance Guide and the rest of the PDS for the Fund as well as the product disclosure statement of the relevant insurance product. You then need to complete the insurance application for the relevant insurance product and send it to the insurer. The insurer will contact us to arrange payment of your premiums. Commencement of cover Insurance cover will commence only when the insurer has accepted your application for insurance. This may not be immediate. You should read the product disclosure statement for the relevant insurance product for information about when cover will commence. Paying your premiums Warning: Continuing insurance cover is dependent on premiums being paid and being up to date. LifeWRAP insurance cover may cease if you do not have sufficient funds in your account to pay your premiums. By selecting a LifeWRAP Individual Policy, your insurance premium will be paid from cash available in your cash account until either: • the insurer receives written notification from you that the payment should cease; or • your insurance policy ceases for any reason. It is your responsibility to ensure that there are sufficient funds available in your account to cover the insurance premiums for your LifeWRAP policies as they fall due. If at the time an insurance premium is due, there are insufficient funds available in your cash account, then the insurance premium will not be paid. The insurer will notify you of any outstanding premiums and how they can be paid to avoid your policy lapsing or being canceled. You should read the product disclosure statement for the relevant insurance product to obtain further information about the consequences of non-payment or late payment of premiums. We will monitor your cash account each month to determine if you satisfy the ‘minimum cash requirement’, which requires that funds be available to pay one monthly insurance premium or one quarterly insurance premium (as applicable). If your premiums are payable less frequently, then the amount of the premium will not be provided for in the minimum cash requirement. If required, you can sell down liquid investments or make extra contributions directly (or via your employer) to your cash account to maintain a sufficient account balance to pay your premiums.
Summarize the above information into a single paragraph
Answer:
LifeWRAP is an insurance offering that enables members to access individual life insurance (including Death and TPD insurance) and Income Protection insurance through the Fund. You can choose from a range of insurance products offered by a number of approved insurers. LifeWRAP Individual Policies are issued by the insurer and are subject to the terms and conditions of the particular policies taken out by us with the insurer on behalf of each individual member. Each policy is held by us as trustees of the Fund. In some cases, you may be able to purchase optional benefits available from the insurer that are offered outside the Fund under separate or linked policies issued in your name.
#3 Answer the Client’s Email
Our client wants a system supporting customer service in email communication. The tool will help CS staff generate emails to claim insurance, open a new account, renew a contract, and answer contract terms. We use LLMs and OpenChatKit to create templates and custom emails for individual situations.
Context:
Take the ‘Thanksgiving Thank You Email’ as an example. The input is “I want to write a thank you letter to our customers about how much the company appreciates their loyalty when using our insurance pension service.”
Answer:
Dear ... customers, I would like to take this opportunity to express my gratitude for your loyalty to using our insurance pension service. Your dedication and commitment to the project have been invaluable in helping us understand our client needs better and provide them with the best possible service. I am very grateful for your dedication and commitment to the service. I look forward to continuing to work with you all in the future.
Final Thoughts
Large Language Models can potentially revolutionize how we interact with technology and each other. LLMs can benefit businesses and individuals by generating creative content to improve customer service.
Still, as with any new technology, there are also ethical concerns to address. It is important for developers and users of LLMs to consider the potential consequences of their actions and strive to create models that are transparent, unbiased, and respectful of privacy. With careful consideration and responsible use, Large Language Models can help us achieve new heights in communication and innovation.
We’ve walked you through how Neurond takes advantage of LLMs and OpenChatKit to deal with various use cases. These projects also prove our deep understanding of LLMs technologies. Based on this, we’re confident in training the models on different datasets to suit your business best.
Still have any questions about LLMs or their applications, drop an email to let us know.