We used ChatGPT to create our 2022 yearly review.

“Dear valued Drivible users,

We are excited to announce several new updates to our platform! Firstly, we have just launched the ability to search for any word within your documents, making it easier than ever to find exactly what you're looking for.

In addition, we have developed the ability to send payment requests for deal deposits, service invoices, and parts invoices directly through our platform. This feature will streamline the payment process for our car dealership partners and make it more convenient for you.

We are also pleased to announce that we have recently onboarded some big dealers and we are looking forward to partnering with them in 2023.

Looking ahead to next year, we have several exciting new features in the works. South Australian dealers will soon have the ability to batch check registration expiry dates, and our [your] accounts department will have the ability to save accounts payable invoices. We will also be introducing electronic signatures and launching a new user interface that centers all of your data around your clients, much like a CRM.

We would also like to take a moment to recognize and thank our hardworking development team for their contributions this year. Their dedication and efforts have been instrumental in bringing these updates to fruition, and we are grateful for their commitment to improving Drivible for our users.

Thank you for choosing Drivible for your document and data storage needs. We are constantly working to improve our platform and bring you new and useful features.

Sincerely, The Drivible Team”

What is ChatGPT?

“As a large language model trained by OpenAI, I am able to understand and generate human-like text, which makes me well-suited for tasks such as answering questions, providing information, and assisting with language-related tasks. I can provide quick and accurate responses to a wide range of questions and topics, and I am able to generate text that is coherent and flows naturally.

In addition, I am available 24/7, which means I can assist you at any time of day or night. Whether you need help with a specific question, some general guidance, or assistance with a language-related task, I am here to help. So, if you have any questions or need assistance with something, please don't hesitate to ask. I'll do my best to help you.”

The above was also generated with ChatGPT - www.openai.com

Firstly I should point out that I am not an expert in machine learning, but I think I know enough to give you a simple explanation. Because at its core, Machine Learning is simple.

It is important however, to point out exactly what Machine Learning is and what it isn’t. Machine Learning isn’t Artificial Intelligence (AI). Intelligence infers learning and applying that to new and completely different and creative situations, Machine Learning only has limited capacity in different situations.

I have two young children and when they were very young (<2 years old) I found it fascinating how they would learn by pointing at objects and people, as parents we would respond “tree”, “dog”, “bird”. After time they would repeat back verbalising as they pointed at objects, slowly refining what they pointed at and making less mistakes. This is Machine Learning. In time, humans progress past this type of learning and become more intelligent.

Feeding examples of images, words or data and labelling those pieces of data into a neural network is what Machine Learning is today. If you give the model enough data and accurate labelling, it can provide predictions based on the patterns that the neural network detects with new data, even if it has never seen that exact data before.

Machine Learning has produced many breakthroughs that we take for granted today, for example Speech Recognition, Translation, Text Recognition (OCR) and more recently object detection and soon fully Autonomous cars.

The biggest downside of Machine Learning is the huge samples of data that are needed and the human input required to label that data accurately. As mentioned before, humans are the greatest Machine Learners on the planet, so who better to teach the machines.

This can take a lot of time and can be expensive. But innovative ways have been created to make labelling less laborious. The best systems for data labelling are the ones that get humans to label text or images without ever knowing it. Remember the reCaptcha (the squiggly letters)? The problem that was being solved was to stop automated bots from accessing websites, but the scaled solution was teaching a machine to learn letters that had previously been missed by its OCR models. Humans were inadvertently teaching a machine! And in the process digitising books and archives.

early machine learning input

More recent examples are spotting images of road signs, stop lights and pedestrian crossings. You are actually teaching self-driving cars objects that are found along the pathways of an Autonomous Car.

Raw computing power and the ever-increasing storage of data is the primary reason Machine Learning is starting to become widespread within many technology solutions today. Whereas in the past you would have to write a program to recognise many different nuances, scenarios and data relationships, not to mention the foresight to recognise those patterns in advance. Today you can simply feed in well labelled data and ‘teach’ your machine to do a task.

Amazing future solutions are imagined to be, spotting cancers in scans, better weather forecasting, more efficient case law and detecting fraud in banking.

At drivible our intentions are a little less ambitious, but just as revolutionary for car dealers. We have begun to use Machine Learning within our program to more efficiently process test drives and soon will use our expertise to organise dealer’s data and sales processes.

The future is very exciting.