Emerging Technologies that are reshaping business

Technologies Reshaping Business

After GPT/ChatGPT, what technologies are next to reshape business?

While still in its infancy, it appears the recent releases of GPT models are the most significant advancements in technology since the advent of the Internet.  No other technology has leapfrogged us forward into the future, faster than the possibilities of what the AI and GPT models present us.  Not only are we able to immediately find answers we are looking for, but we can have discussions to debate merits, challenge, and have AI models find weaknesses in our theories and analysis.  We can have AI models digest data to help us more easily identify content, opportunities, and issues.  At this moment, it appears we have yet to understand how far-reaching this GPT technology can take us, but with caution, since the technology is still relatively new, and the content issues are not yet fully known.

In this article, we will example several emerging technologies that show promise after GPT models and could potentially have the next significant impact in the future for how we conduct business. Here are a few possibilities:

  1. Quantum Computing: Quantum computers have the potential to solve complex problems much faster than classical computers by leveraging quantum phenomena. If scalable and reliable quantum computers are developed, they could revolutionize fields like cryptography, optimization, drug discovery, and more. For example, drug manufacturers used quantum computing to help advance COVID vaccines in months, rather than the years they would have typically taken to develop (e.g. Moderna and IBM).
  2. Augmented Reality (AR) and Mixed Reality (MR): AR and MR technologies overlay virtual content onto the real world, enhancing our perception and interaction with the environment. As these technologies continue to advance, we can expect transformative applications in areas such as gaming, education, healthcare, design, and remote collaboration. For example, instruction manuals can be viewed through an AR application on your phone and can walk you through a setup of a device in real time, as opposed to reading poorly written paper copies that were included in the device (e.g. TechSee).
  3. Internet of Things (IoT) and Edge Computing: IoT refers to the network of interconnected physical devices that can collect and exchange data. As IoT devices become more prevalent, the need for efficient data processing and analysis increases. Edge computing brings computational power closer to the devices, reducing latency and enabling real-time analysis. These technologies can enhance automation, smart cities, industrial processes, and more. For example, a connected home has a IoT smoke detector that can identify smoke and shut down the IoT thermostat, so smoke doesn’t enter the ventilation system, then alert the fire department (e.g. Google Nest)
  4. Blockchain and Decentralized Applications (dApps): Blockchain technology enables secure and transparent transactions, and it has gained popularity through cryptocurrencies like Bitcoin and Ethereum. In the future, blockchain could be utilized beyond cryptocurrencies, enabling decentralized applications, digital identity systems, supply chain management, and secure voting systems. Blockchain probably has the highest degree of impact on the future of business, because of the digital transaction certainty, which finally allows for integrated business to business transactions.  While cryptocurrency transactions have been executed, the technology of digitizing transactions is still in its infancy, with no clear winner of the cryptocurrency to be used to conduct business transactions.  Also, security is still an issue that will require greater controls.
  5. Artificial General Intelligence (AGI): While ChatGPT represents a significant advancement in natural language understanding, AGI refers to highly autonomous systems that can outperform humans across a broad range of tasks. AGI aims to create machines with human-like intelligence, capable of understanding and learning any intellectual task. Achieving AGI would have profound societal and technological implications, which has the potential to cause more damage than good, if not carefully and thoughtfully implemented.

These are just a few possibilities, but the next impactful technology could emerge from a completely new technology or be an advancement in an existing technology. While we cannot predict the future, we know that breakthroughs can come from unsuspecting places, such as when the Kellogg brothers Kellogg, changed breakfast forever when they accidentally flaked wheat berries, which led to Kellogg’s Corn Flakes.

ChatGPT is changing intelligent automation and RPA

Chat Bot in RPA/Automation

Everything you need to know about ChatGPT and how ChatGPT is changing intelligent automation and RPA.

What is ChatGPT?

You can’t talk about ChatGPT without talking about GPT, or Generative Pre-Trained Transformers, which is a type of Large Language Model (LLM).  GPT refers to a family of machine learning models developed by OpenAI. GPT models, like GPT-4, are based on the transformer architecture, which is a deep learning model primarily used for natural language processing (NLP) tasks.

GPT models are “generative” because they are designed to create human-like responses by predicting the most likely next word or sequence of words in a sentence without losing context. GPT models are pre-trained on large amounts of publicly available text from the internet, allowing them to learn the statistical patterns, grammar, and contextual relationships between words. This pre-training helps the models to acquire a broad understanding of language and context.

Chat GPT Self-attention Model

GPT models (and Large Language Models) use a Transformer architecture, which is a method in artificial intelligence that teaches computers to process data like the human brain (also known as “neural networks”).  Transformer models excel at handling sequential data, such as text, and employ self-attention mechanisms to capture relationships between words and encode them into contextualized representations.

Once pre-training is complete, GPT models can be fine-tuned on specific tasks, such as text completion, translation, summarization, or question-answering, by providing them with task-specific training data. The models use a technique called “unsupervised learning” during pre-training and then transition to “supervised learning” during fine-tuning.

GPT models have achieved significant advancements in various Natural Language Processing (NLP) tasks, demonstrating their ability to generate coherent and contextually relevant text. They can be used for a wide range of applications, including chatbots, content generation, language translation, virtual assistants, and more.

Overall, GPT models are highly flexible and powerful language models that have gained significant attention due to their ability to understand and generate human-like text in a wide range of contexts.

So, what is ChatGPT?

ChatGPT is a chatbot powered by an Artificial Intelligence (AI) model that was developed by OpenAI.  The ChatGPT chatbot is accessible from a website, where you can engage and converse (via typing) with an AI model and get instant responses to your questions.  Where Google search will give you results to questions by connecting you with relevant websites, ChatGPT will give you the answers to your questions.  ChatGPT will also allow you to follow-up on your questions with additional questions, keeping your entire history of questions and responses relevant to the subsequent questions.

ChatGPT launched in December 2022, with GPT-3.5, which was trained on 175 billion parameters, whereas ChatGPT-4 is estimated to be trained on 1 trillion parameters.

OpenAI is an American company, founded in 2015, as a non-profit, open-source company, by a large group of Artificial Intelligence scientists and investors.  OpenAI has transitioned from a not-for-profit company to a for-profit company and has a partnership with Microsoft, as its primary investor, investing over $1 billion with an additional $10 billion committed to OpenAI for further research and development.

How should questions be asked to ChatGPT?

  • Keep it simple. Ask straightforward questions.
  • Be specific. Include specific details with your questions.
  • Use keywords. Use specific keywords in your questions to help refine the results.
  • Refine questions and regenerate. ChatGPT allows you to regenerate responses if you want ChatGPT to write another response.  Alternatively, if ChatGPT is not returning the desired response, try asking the question with an alternative approach.

What can ChatGPT be used for?

  • Brainstorming and ideation.
  • Get personalized recommendations.
  • Understand complicated topics.
  • Use as a writing assistant.
  • Summarize research.
  • Assistance with coding and debugging.
  • Translate text from 95 different languages.
  • Create multiple choice questions on a variety of topics and varying difficulties.
  • Get assistance with travel plans, such as restaurants, cultural attractions, flights, and more.
  • Analyze sentiment and tone for positive, negative, or neutral.
  • Find data sets for research, business intelligence, training machine learning models, and more.
  • Train ChatGPT on your own data.
  • Interview preparation and job preparation.
  • Write songs, poems, and stories.

How can ChatGPT be used in RPA/Automation?

ChatGPT can be used in Robotic Process Automation (RPA) in several ways to enhance automation capabilities and improve the interaction between bots and users. Here are a few examples:

  1. Improved solution design. ChatGPT can be used to help explore and consider alternative technologies.  Recently, we worked with a client that was capturing personal information in an Excel form.  We are experienced enough to identify this is not a secure or compliant process to automate as-is, so we suggested and agreed with the client to build a web-based form.  We have seen too often that RPA firms will just automate the as-is process without consideration for best practices, security, or compliance, so process owners, subject matter experts, and RPA CoEs can consider ChatGPT for improving their solution design capabilities.
  2. ChatGPT can help write Excel Marcos, Excel Formulas, Regular Expressions (RegEx), SQL Queries, Python, JavaScript, C++, C#, HTML/CSS, R, Ruby, Java, and more.  You can also use ChatGPT to summarize the code into human language to help with business process owner reviews to ensure the coding is meeting the requirements of the business case.
  3. Intelligent Chatbots. ChatGPT can be integrated into chatbot frameworks used within RPA systems. These chatbots can understand natural language inputs from users and provide context-aware responses, allowing for more intuitive and conversational interactions.
  4. Data Extraction and Validation. ChatGPT can assist in extracting and validating data from unstructured sources such as emails, documents, or web pages. By training the model on specific data extraction tasks, it can automate the process of understanding and extracting relevant information accurately.
  5. Process Documentation and Training. ChatGPT can be used to generate process documentation or training materials by converting technical information into easily understandable language. This can be beneficial for onboarding new employees or documenting complex workflows in a more user-friendly manner.
  6. Exception Handling and Error Resolution. In complex RPA workflows, exceptions and errors can and will occur. ChatGPT can help identify the nature of the issue and suggest appropriate actions for error resolution. It can also provide real-time troubleshooting assistance, reducing the need for human intervention.
  7. Workflow Optimization and Decision Making. ChatGPT can analyze large sets of data and provide insights for optimizing RPA workflows. By processing and interpreting data from various sources, it can make intelligent recommendations for process improvements, resource allocation, or decision making.
  8. User Support and Self-Service. ChatGPT can handle user queries, provide assistance, and offer self-service options within RPA systems. It can guide users through various tasks, answer common questions, and help troubleshoot issues, reducing the need for manual intervention and improving user experience.

It’s important to note that while ChatGPT can enhance RPA capabilities, it’s crucial to consider its limitations and ensure appropriate safeguards are in place to handle scenarios where the model may provide incorrect or misleading information.  We find that ChatGPT is very good on common knowledge, but abstract thinking is still rudimentary in some areas.  ChatGPT is still evolving and growing, so many of these limitations will continue to be resolved.

 

References:

  1. Open AI: OpenAI is an AI research and deployment company
  2. The Best Examples Of What You Can Do With ChatGPT
  3. Image Source: Cheng et al., 2016. https://arxiv.org/pdf/1601.06733.pdf