Better Futures: Helping small enterprises to adopt AI

Deep Dive
Better Futures

What percentage of manufacturing companies do you think have adopted artificial intelligence (AI) in some way to drive business value? According to the US Census Bureau, just 4%. 

The disconnect is there for all to see. Data companies are coming out with the technology, but on the flip side 96% of manufacturers and engineering leaders say: “I don’t know what AI is and it is too abstract to even start beginning to think about implementation.”

For the past 15 years Anthony Mc Loughlin, CEO and founder of startup Better Futures, has been helping blue-chip manufacturers like Airbus, Daimler and Mercedes adopt advanced analytics and generative design – the foundations of what we all know today as AI.

Again and again, Mc Loughlin has witnessed the disconnect between AI technology and its adoption due, in large part, to high complexity and costs of implementing the technology. Leveraging breakthroughs in LLMs (large language models) and generative pre-trained transformers (more commonly known as GPT), Mc Loughlin is building a bridge that enables small and medium enterprises to work out where AI could improve their operations and achieve first successes in a new simpler approach.

“Entry levels for the adoption of AI, to get that first win, are far too high,” says Mc Loughlin. “The knowledge and access to experts is completely fragmented and siloed. Number two, until now traditional AI use cases such as predictive maintenance or condition monitoring are very complex, requiring significant upfront investment in IT and resources. We are talking about typically six figures and a year of implementation at least.”

Electric aircraft developers are well suited to leverage the Better Futures platform, especially as they progress nearer to type certification and entering commercial service, according to Mc Loughlin. “As these companies move from certification to production, they are generating a lot of  knowledge and documentation.This will drive up their ‘knowledge administration’ and reduce their innovation potential.” 

Recent breakthroughs in GPT large language models – think ChatGPT, Microsoft Copilot and Google Bard – have made Mc Loughlin’s vision possible. He says his team is now helping clients adopt AI up to 10 times faster, cheaper and with less risk.

“Due to the GPT breakthrough and emergence of LLM models, now at the press of a button, you can access external data expertise in real time for a few cents, to help you with key tasks to be successful with AI. Secondly, one can extend the power of LLMs to provide instant access to internal documents and knowledge from across an organisation at the press of a button. This opens up a complete new dimension of quick win simple AI use cases.”

“LLMs as incredible as they are, are just ‘the engine’, engineers and manufacturers need dedicated AI assistants that integrate into their complex ecosystems in a controlled manner. One needs to add expert and company knowledge in a safe protected manner. One needs standardised workflows, automated reporting and governance. You don’t just throw AI systems around a company, you need to control them just like any other methods and tools in the organisation.

“We have built the world’s first dedicated AI assistant and platform for manufacturers to close these gaps. To empower engineers and manufacturers to rapidly deploy AI Assistants without coding and without needing to know data science.”

Free to try out initially for business to consumer users, the Better Futures platform is offered via subscription. On the platform, engineers can explore use cases, such as reducing machine downtime, and access a demonstration of a manufacturing AI assistant. There is also an enterprise pricing model of business to business clients that offers deployment of an AI system to utilise a company’s expert data. Mc Loughlin describes it as the “first dedicated AI assistant to help you adopt AI”.

“We know how hard it can be to adopt AI, not least because of the jargon that seems to come out everyday at the moment. In the last months we realised that nobody is understanding what an AI assistant is. So we decided the best plan of action was to build a live demonstrator. This means in 30 seconds any engineer can login and try out an AI assistant based on a wind turbine. As I know myself being an engineer, we only understand something by playing with it and trying to break it. So please feel free to sign up, find some use cases and we can help you implement them.” 

According to his research, Mc Loughlin estimates that up to 30-40% of an engineer’s time can be spent on this ‘knowledge administration’ (things like finding the right knowledge, the right document and reporting).

“AI assistants open up a new dimension of simple use case you can rapidly deploy, especially around reducing knowledge administration. For example a ‘Machine AI Assistant’ which can dramatically reduce downtime. When an assembly line halts unexpectedly due to a machine failure, every minute of downtime translates to significant financial losses. An AI assistant can quickly screen through internal databases to find similar incidents, retrieve the relevant repair documentation and identify the right experts who resolved similar issues. This drastically cuts down the time taken to diagnose and fix problems, potentially saving hundreds of thousands to millions of euros.”

“What we are really trying to drive home is that with AI assistants it has never been easier to unlock the promise of AI, for any manufacturer of any size. Visit our website and in less than a minute you can get started with your AI journey.” he says.

Better Futures came out of stealth earlier this year and is based out of University College Dublin’s hub for new ventures known as NovaUCD. It has invested around €500,000 to date to commercialise its first minimal viable product with funding coming from founders and local Irish investors.

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