As a disruptive “upstart” deploying the power of machine learning and deep domain knowledge to drive big productivity improvements in the $2 trillion global food and drink manufacturing sector, we share the UK science minister’s view that the sudden appearance of China’s DeepSeek on the tech stage means that artificial intelligence is no longer “going to be dominated by two or three players. We’re now in a truly competitive era”.
Lord Vallance of Balham – a former Chief Scientific Advisor to government and the most senior civil servant running the science and technology portfolio in Whitehall declared in The Times this week: “I think what it does is create a real environment in which small upstarts can come and change things. We’re going to see more companies. We’re going to see more innovation.”
As an innovative “upstart” using machine learning to help the UK’s largest manufacturing sector – food and drink – IntelliAM are also at the forefront of the AI revolution. What marks us out from the crowd is our powerful combination of rich domain knowledge, hard won through decades of service on production lines around the world, combined with a super-talented team of data engineers who can turn billions of untapped data points on a production line into a laser accurate, early warning and governing system to prevent costly machine downtime and boost throughput efficiency, whilst reducing waste streams.
This has already made us the go-to AI partner for five of the top ten food manufacturing companies in the world. What they get is the colossal data crunching power of ML, combined with IntelliAM’s on-the-ground knowledge of our customers’ assets, which is also unlocking market-winning improvements in shop floor productivity in a way that the big tech majors are unable to do using smart software alone.
So what is machine learning (ML)? And how is it different from the mass market, large language models (LLM) that have been making the headlines since January 27th following the unveiling of China’s DeepSeek which deploys these models?
One neat way to view this is to see LLM is as a subset of Machine Learning, which itself is a subset of Artificial Intelligence. Compared to machine learning, LLM is a relatively new kid on the block, made possible by big improvements in data storage and computational power brought about by the widespread adoption of GPUs (think Nvidia), affordable data storage and collection methods and state subsidies.
It’s exciting, and sometime scaring, the markets because its full power and potential remain open to conjecture and speculation. In other words, we are in currently in the hype phase of its development. ML, by contrast, is a much more robust and mature tech, but one that continues to evolve and improve.
At IntelliAM PLC , our ML solutions are specifically tailored for productivity and reliability insights. Unlike LLMs, which process natural language for general applications, our approach is rooted in actionable, data-driven insights designed to optimise performance, improve uptime, and drive measurable outcomes in industrial environments. ML is the perfect tech for this. As a result, we are empowering our manufacturing partners to:
– Predict equipment failures before they happen.
– Optimise production processes with precision.
– Reduce costs and increase operational efficiency.
Of course, as ML tech “upstarts” we keep a weather-eye on other developments in artificial intelligence ensuring our customers are never caught out in the rain. But this latest storm on the American markets proves what we at IntelliAM have known for a long time: like climate change, the advent of AI and its derivatives is not something industry and manufacturers can avoid. It is coming whether we like it or not.
For now, you might trust an AI chatbot to help with your teenager’s geography homework, but to let it loose on a factory floor would get you expelled from the market place. We are a long way yet from the idea of a factory being run by one man and his dog. The man being there to feed the dog. And the dog to stop the human touching any of the machines. But disruptive change has been unleashed.
As the director of the MIT Center for Deployable Machine Learning Aleksander Madry says: “Machine learning is changing, or will change, every industry, and leaders need to understand the basic principles, the potential, and the limitations.” The hidden message here, and one the UK industry needs to tune in to, is that the ML Artificial Intelligence revolution is coming whether they get or board or not. If they don’t heed the message, it’s very unlikely that their businesses will be able to compete with those that do.
Which is where IntelliAM comes in. Our combination of industry-specific domain knowledge – invaluable IP that cannot be machine learned – alongside our ability to deploy the immense data processing power of machine learning to the production line and factory floor, is making us the go-to-team for some of the biggest manufacturers on the planet.
China and DeepSeek have suddenly and dramatically reduced the cost of deploying AI in the marketplace, revealing yet again Beijing’s undisguised determination to become the dominant manufacturing superpower in the world, and confirming that China’s relationship with the United States and its tech titans will be the defining feature of the age. IntelliAM’s role in this drama may be more modest, but it is still vital. It is to ensure that our industrial partners around the world get the maximum value from the data driven technologies emerging from under the AI umbrella and that they never get caught out in the storm.