How to Make AI Work in Your Business
Chris Knight, Founder & CEO, CKX, discusses how businesses can make AI work.
Artificial Intelligence is not a new idea, but it IS a different form of programming. To see how it contrasts with traditional programming we should perhaps start by asking ‘what is intelligence’? According to one dictionary, it is “the ability to acquire and apply knowledge and skills”. Humans are already wired to do this, but the machines have to be shown the way.
With AI, instead of telling systems exactly what to do, we programme them to learn from the data we give them. Back in the early 2000s my first AI effort involved a thousand images of men and women and a plan to distinguish between them. It worked! It was marginally better than a human on a specific dataset, but where it didn’t do so well was when using non lab-condition images. The arrival of big data, however, has given us enough data points to create effective AI models. The learning process uses data-intensive algorithms and improves output as new data is fed in. These models not only interpret current data, but can also make predictions.
For example; the Chinese territorial game GO was the game-changer for AI. The options are equivalent to the theoretical number of particles in the universe. So in order to beat humans at GO, the system has to know how to learn. The AI then invented a brand new move, dubbed ‘move 37’. This strategy had never been seen before in a game over 2,500 years old. The new move is often used as an example of a potential sign of creativity or original thinking by AI.
So how can you take this new form of programming and apply it to your business? There are three things to consider; efficiencies, data, proof-of-concept.
Right now AI is best at making your current processes more efficient, or taking over mundane tasks. It would be useful in spotting financial fraud in bank accounts for example. An AI model can set a baseline of usual activity in the bank’s accounts. It can then monitor them for anything unusual and report this up to a human to make a decision. Rather than having to review hundreds of thousands of accounts, bank workers now have a much smaller set of flagged risk accounts to review.
For example; AI is resolving a skills shortage issue in farming. In our project for Agribot, the AI model detects plant diseases, pests and water levels by aggregating data from sensors and high-resolution cameras (robots!). In large farms it’s hard for workers to know what’s going on in every corner of every field. AI can learn to recognise disease, or under-watered plants and alert farm workers to the problem. In this case, on a valuation data set of 11k images it is 99.98% accurate.
Big data has been a driver of Artificial intelligence, so you need to consider your data before you plan your project. Having established where your problem is, take a look at the data you have, and what you need. AI makes big data useful, but it also needs it to function. As I discovered in my early images project, a thousand images is not enough. So if you don’t have the data, do you need to set up a project to harvest it, or is it available elsewhere? Identifying the right data is vital to the success of your project.
Proof of concept
With AI, everything starts off as an R&D project, so a pilot project is a way to validate your data and your hypothesis. There’s no guarantee that there is going to be a pattern that the model can recognise and learn from. A short project allows you to find the right data and develop a model. Approaching an AI project like this can help to convince others in the business that it’s not a vanity project; it’s just another solution
For example; we developed an app for a business lunch supplier in Denmark which is the first step in making the business AI-ready. The app digitised the database of their clients’ lunch preferences. It’s now possible to share this complex information across the company, which is helping to increase customer choice, boosting retention and thus revenue.
Combining AI with big data has created a whole new way of solving problems and creating efficiencies for businesses. But it’s important to consider how it will work for your business, with your problem. AI is a new approach to programming with practical benefits, but it’s not a cure-all. That said, there are huge possibilities for AI to be a serious force for good in your business.
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GfK and VMware: Innovating together on hybrid cloud
GfK has been the global leader in data and analytics for more than 85 years, supplying its clients with optimised decision inputs.
In its capacity as a strategic and technical partner, VMware has been walking GfK along its digital transformation path for over a decade.
“We are a demanding and singularly dynamic customer, which is why a close partnership with VMware is integral to the success of everyone involved,” said Joerg Hesselink, Global Head of Infrastructure, GfK IT Services.
Four years ago, the Nuremberg-based researcher expanded its on-premises infrastructure by introducing VMware vRealize Automation. In doing so, it laid a solid foundation, resulting in a self-service hybrid-cloud environment.
By expanding on the basis of VMware Cloud on AWS and VMware Cloud Foundation with vRealize Cloud Management, GfK has given itself a secure infrastructure and reliable operations by efficiently operating processes, policies, people and tools in both private and public cloud environments.
One important step for GfK involved migrating from multiple cloud providers to just a single one. The team chose VMware.
“VMware is the market leader for on-premises virtualisation and hybrid-cloud solutions, so it was only logical to tackle the next project for the future together,” says Hesselink.
Migration to the VMware-based environment was integrated into existing hardware simply and smoothly in April 2020. Going forward, GfK’s new hybrid cloud model will establish a harmonised core system complete with VMware Cloud on AWS, VMware Cloud Foundation with vRealize Cloud Management and a volume rising from an initial 500 VMs to a total of 4,000 VMs.
“We are modernising, protecting and scaling our applications with the world’s leading hybrid cloud solution: VMware Cloud on AWS, following VMware on Google Cloud Platform,” adds Hesselink.
The hybrid cloud-based infrastructure also empowers GfK to respond to new and future projects with astonishing agility: Resources can now be shifted quickly and easily from the private to the public cloud – without modifying the nature of interaction with the environment.
The gfknewron project is a good example – the company’s latest AI-powered product is based exclusively on public cloud technology. The consistency guaranteed by VMware Cloud on AWS eases the burden on both regular staff and the IT team. Better still, since the teams are already familiar with the VMware environment, the learning curve for upskilling is short.
One very important factor for the GfK was that VMware Cloud on AWS constituted an investment in future-proof technology that will stay relevant.
“The new cloud-based infrastructure comprising VMware Cloud on AWS and VMware Cloud Foundation forges a successful link between on-premises and cloud-based solutions,” says Hesselink. “That in turn enables GfK to efficiently develop its own modern applications and solutions.
“In market research, everything is data-driven. So, we need the best technological basis to efficiently process large volumes of data and consistently distill them into logical insights that genuinely benefit the client.
“We transform data and information into actionable knowledge that serves as a sustainable driver of business growth. VMware Cloud on AWS is an investment in a platform that helps us be well prepared for whatever the future may hold.”