Delve into the fundamentals of artificial intelligence with our blog series. Explore key AI types, how large language models (LLMs) work, the role of training data, and the challenge of LLM hallucinations. Learn about transformer architectures, neural networks, and the difference between generative and analytic AI, with practical explanations and real-world examples for beginners and experts alike.
A sign that most of us barely understand the way that LLMs work is illustrated by the trend for “prompt engineering”, where merely rewording a prompt to a large language model (LLM) would produce a better answer. There is lots of advice on this subject. Be as detailed as possible in your prompt, give context…
Large language models (LLMs) are noted for their fluent and confident answers. They increasingly perform well in a range of tests and benchmarks. For example, LLMs score highly on benchmarks like MMLU-Pro, which was specifically designed to challenge LLMs in a range of around 12,000 general knowledge tests. LLMs these days also score well on…
The idea of a “digital twin”, a virtual replica of a physical object, is not a new one. In the 1960s NASA built computer simulations of spacecraft for the Apollo missions. The idea was that the telemetry from real-world sensors on the Apollo craft would be fed into the simulator, in order to see what…
Large language models (LLMs) have developed significantly since ChatGPT burst onto the public scene in late 2022, built on the GPT-3 model. There have been increases in scale, with GPT-4 being several times larger than GPT-3 in terms of the numbers of parameters. Context windows increased from a few thousand tokens to over a million.…
Large language models (LLMs) such as ChatGPT have excellent linguistic skills, but to use them for a specific business process, they need additional knowledge. For example, a customer service chatbot would not be much use unless it knew things like the products that the company sold and who had purchased them and when. To supplement…
You may be aware that a large language model (LLM) is trained on data, but did you know that there is a multi-billion-dollar industry of human data labelling that supports this? Behind every LLM lies an invisible workforce that toils away, labelling files, images and videos to help train the AIs. A large language model…
We are all being deluged by news stories about artificial intelligence (AI) and the large language models (LLMs) at the heart of the latest AI trend, generative AI. But how do they actually work? Some level of understanding of this would seem quite useful for a technology that now creates over half of the content…
There have been several studies that show that the current failure rate of AI projects is shocking. The highest profile one is a 2025 MIT study, involving hundreds of interviews, finding that the failure rate of AI projects was 95%. This stark number is not actually so different from other estimates, which have ranged from…
We are used to dealing with multiple sensory inputs: the information from our senses of sight, hearing, taste, touch and smell. We combine this information to make decisions easily and unconsciously. By contrast, artificial intelligence (AI) chatbots based on large language models (LLMs) have been mostly restricted to a single mode of communication – text.…
As the large language models (LLMs) that underlie artificial intelligence chatbots like ChatGPT permeate more and more of daily life, people are increasingly coming to depend on them. Students use LLMs to help with their homework, programmers use LLMs to debug code or write new program code, and marketers to write descriptive content about their…