A guide to the three most important AI technologies
Artificial intelligence, machine learning, and large language models are three of the most important technologies in the world today. AI is a broad term that refers to the ability of transformative technologies to perform tasks that are typically associated with human intelligence, such as learning, reasoning, and problem solving.
Artificial intelligence (AI) is a branch of computer science that deals with the creation of intelligent agents, which are systems that can reason, learn, and act autonomously. AI research has been highly successful in developing effective techniques for solving a wide range of problems, from game playing to medical diagnosis. One of the most important challenges in AI research is to create systems that can learn from experience. This is where machine learning comes in.
Machine learning (ML) is a subset of AI that deals with the development of algorithms that can learn from data without being explicitly programmed. ML algorithms are trained on large datasets, and they can then be used to make predictions or decisions on new data. There are many different types of ML algorithms, but they all work by finding patterns in data. Once an ML algorithm has identified a pattern, it can use that pattern to make predictions about new data.
Large language models (LLMs) such as ChatGPT, Bing and Bard, are a type of AI that are trained on massive amounts of text data. This allows them to generate human-like text, translate languages, write different kinds of creative content, and answer your questions in an informative way.
The Future of AI, ML, and LLMs
AI, ML, and LLMs are rapidly developing technologies, and they have the potential to revolutionize many aspects of our lives. AI systems are already being used in a wide range of applications, from healthcare to finance. In the future, we can expect to see AI systems being used in even more applications, and we can expect ML and LLMs to play an increasingly important role in the development of AI.
Here are some examples of how AI, ML, and LLMs are being used today:
- Healthcare: to develop new diagnostic tools, to personalize treatment plans, and to improve the efficiency of healthcare delivery.
- Finance: to develop new investment strategies, to detect fraud, and to automate customer service tasks.
- Retail: to personalize product recommendations, to optimize inventory management, and to automate customer service tasks.
- Manufacturing: to improve product quality, to automate production processes, and to optimize supply chain management.
- Transportation: to develop self-driving cars, to improve traffic management, and to optimize logistics operations.
We can expect to see these technologies being used in even more applications, and we can expect them to have a profound impact on our lives.
Conclusion
As these technologies continue to evolve, it is crucial to recognise that they are tools at our disposal. It falls upon us to regulate their use appropriately and ensure they are employed to improve humanity. While embracing these transformative technologies, we must also remain mindful of the potential risks they pose.
Over the past 15 years of research projects, I have been leading commercialisation efforts and industry engagements using ML algorithms trained for example on early detection of human and plant diseases. The algorithms are trained on a dataset of relevant images. Once trained, they can identify new diseases in humans and plants in new images taken in hospitals or in the field.
I now use LLMs, including ChatGPT, Bing, and Bard every day as my research assistant. LLMs answer my questions comprehensively and informatively to create a framework of text content that is then curated with further research and inputs. I find myself using different LLMs in different ways to arrive at results.
We find ourselves in an exciting time where running a private advisory practice specializing in driving business growth through transformational change is truly possible. In this pursuit, technologies like AI, ML, and LLMs have become indispensable assets in my everyday toolkit.
About: Gary Morgan is an experienced board director, CEO, consultant, and corporate advisor with expertise in strategy, innovation, and growth across various sectors. His focus is on driving business growth through transformational change, leveraging emerging AI technologies. Gary is a Fellow of the Governance Institute of Australia and serves on the Griffith University Industry Advisory Board for the ICT School. Gary has co-authored papers published in leading entrepreneurship and medical journals.
Acknowledgment: This article was composed in part using AI technology.
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