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GoSmarter AI Blog

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About this Section

About this Section

The GoSmarter blog covers AI and digital transformation from a metals manufacturing perspective. Practical use cases, implementation guides, industry strategy, and plain-English takes on the tech that actually matters on the shop floor.

No fluff. No thought-leadership waffle dressed up as insight. Just practical articles written for people who run metal cutting, distribution, and processing operations.

Topics covered include mill certificate automation, rebar cutting optimisation, scrap rate reduction, EN 10204 compliance, inventory management for steel stockholders, and the practical realities of replacing spreadsheets with AI-powered workflows. The blog also covers industry news relevant to UK and European metals manufacturers — tariffs, standards changes, and technology developments that affect your margins.

Articles are written for production managers, quality managers, operations directors, and business owners in metals manufacturing. Each post focuses on a specific, solvable problem: how to reduce scrap on a saw line, how to stop losing mill certificates, how to automate the cert-to-stock link without an IT project.

For deeper, structured guides on specific topics, see the GoSmarter hub pages — pillar content covering cutting optimisation, mill cert automation, yield tracking, and more.

AI Winters and hype

This is not the first time AI has been all the rage in the business world. In particular, AI was big in the eighties with solutions called expert systems. Will AI be a passing fad now?

Read More: AI Winters and hype

How IoT technology can be used to improve UK public transport

There is no shortage of possible applications when it comes to Artificial Intelligence (AI) in the public sector, but while the UK government is investing heavily in AI in the private sector, what are they actually doing to implement it themselves? Some fear that governments using AI will result in a dystopian future of constant surveillance, but in reality, public sector applications of AI are far more pragmatic.

Read More: How IoT technology can be used to improve UK public transport

DataOps for everyone at #DataOpticon

If there’s one thing that our CEO Steph Locke is passionate about, it’s data. Getting businesses’ data AI-ready, sharing knowledge around data skills and processes, and generally empowering people through data. Back in September 2019, Steph hosted the first ever DataOpticon in London, with a simple goal: to help people who work with data do it better.

Read More: DataOps for everyone at #DataOpticon

Sealing the gap in education poverty with AI & EdTech

Could education be the industry that has seen the least change over the years? While we’ve seen big changes in the accessibility of education, there is still a long way to go, and as pointed out by The World Bank, being in school is not the same as learning. Often pupils are unengaged, teachers are failing to hold everyone’s attention in class, and drop out rates and grades are proving that the one-size-fits-all approach to learning is outdated.

Read More: Sealing the gap in education poverty with AI & EdTech

The AI Hierarchy of Needs meets the Minimum Viable Product

Two of my favourite pyramids are the Data Science Hierarchy of Needs and the Minimum Viable Product. Combining them helps us build effective artificial intelligence (AI) proof of concepts in businesses. It also supports building AI competency at the same time as demonstrating Return on Investment (ROI).

Read More: The AI Hierarchy of Needs meets the Minimum Viable Product

How to score your first AI quick wins: Intelligent Insights

There’s no doubt that going ahead with Artificial Intelligence (AI) can be risky. We’ve seen numerous AI fails from major companies including IBM, Amazon and Microsoft which landed them in hot water, something big companies can often bounce back from, but could be more of a problem for the smaller players. The trick to getting started with AI is to start small, which is where our quick win AI projects come into play.

Read More: How to score your first AI quick wins: Intelligent Insights

Mastering AI in manufacturing: the three levels of competency

Manufacturers have been facing continual pressure to improve their technology base, reduce costs, and improve quality since the Industrial Revolution. Manufacturers are used to change but not every manufacturer can or will embrace it at the same rate. Also, no manufacturer jumps straight to being an expert at the new thing they're needing to adopt. The same goes for Artificial Intelligence (AI) as an emerging change in manufacturing.

Read More: Mastering AI in manufacturing: the three levels of competency

Industry IoT, smart factories and AI in manufacturing

The world of manufacturing is on the brink of another revolution due to the Internet of Things (IoT) and Artificial Intelligence (AI) applications. Aside from clear use cases like robotics and automation, big data applications are coming into play, thanks to industrial time series data collected by data historians. Thriving on all this data, AI systems can be built to send early warnings, optimise processes, predict maintenance and enforce quality control. By collecting the right data, manufacturers can get really creative with their AI solutions, and it can set them apart from the competition.

Read More: Industry IoT, smart factories and AI in manufacturing

A partnership of Machine Learning and AI with healthcare professionals

Healthcare has always been a data-rich area, but with new technologies for processing and structuring, and new ways of collecting data, such as using sensors, like many other industries, the available data is growing exponentially. Artificial Intelligence (AI) makes it possible to analyse all this data in real-time by combing Machine Learning (ML) and Natural Language Processing (NLP), in order to gain valuable insights.

Read More: A partnership of Machine Learning and AI with healthcare professionals

Expert Perspectives: Enhancing business with data and AI

This week we spoke to Dr. Leila Etaati, co-founder, data scientist, consultant and mentor at RADACAD, about what she thought was the key to success with AI for businesses, and how her business was implementing these beliefs. The RADACAD team work with other companies to deliver expert training and consulting around all things data, with a passion for helping businesses improve by listening to their data.

Read More: Expert Perspectives: Enhancing business with data and AI

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