The technology buzz over the last year has been mainly about AI. The explosive emergence of Large Language Models (ChatGPT, Bard etc) has brought AI into the mainstream. That’s often the way; a strand of technology innovation bubbles along, developing at pace but broadly unnoticed in the background until, seemingly overnight, it emerges in a consumer application. And then whoosh, it takes off like a rocket.
But AI has not just happened overnight, it’s been developing, morphing and evolving over 80 years. We’ve compiled a timeline of how it’s developed, with some of the key milestones.
At Carbon Re, we use various kinds of machine learning and deep learning, specifically deployed in the ‘foundation’ industries such as cement manufacture. Our core expertise is ‘reinforcement learning’: an advanced form of Artificial Intelligence where an AI agent learns through repeated play in a virtual environment to optimise a reward function. It outperforms ‘supervised learning’ (90% of all AI machine learning applications) such as ‘Model Predictive Control’ used by other ‘AI’ control systems being developed for cement production.
Reinforcement learning is one of the most promising branches of AI, able to work with very complex systems and solve problems requiring sophisticated strategies.
Our team undertakes continuous R&D with the highest level of scientific rigour and very strong connections to the top AI researchers and research labs. We are uniquely positioned to not only translate the latest AI research into value-creating applications for the cement and building industry, but also to advance the state-of-the-art of what AI can achieve in the industry with our in-house research expertise.
We’re constantly striving to build on the breakthrough thinking that has gone before us and move things forward.
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