Reflections on five use cases from IBM Innovation Evening 2024

On Thursday, 14th November, IBM hosted a Technology Innovation Evening at their offices in London.

With attendees from a variety of businesses present, IBM showcased how it continues to be at the forefront of innovation, demonstrating the latest advancements in its generative AI models. This included strong focus on real world applications, with IBM providing several use cases to explain how these models can make people’s lives and jobs easier and more efficient, and thus how generative AI can be a force for good in the world.

The ever-increasing real-world applications also mean that there is exponential market growth potential. Indeed, Bloomberg predict that the generative AI market is poised to explode, growing to $1.3 trillion over the next 10 years from a market size of just $40 billion in 2022 as more and more real-world uses of AI become available.

Of the use cases being demonstrated on the evening by IBM, these were five of the most interesting.

Spot the Boston Dynamics-Robot Dog:

Spot the Agile Mobile Robot Dog is changing how organisations are monitoring and operating their sites.

Using IBM Maximo, Spot can function in hazardous environments, gathering data and flagging issues in places it would be incredibly difficult and dangerous, and thus often expensive or impossible, for humans themselves to reach.

Naturally, this has numerous real-world applications, with the most significant being around the support, protection and management of businesses’ assets. For example, Spot can be used to monitor power systems, collecting readings on the heat and vibrations of these to immediately flag if there are concerns in functionality.

Spot can also be used in help emergency workers in dangerous situations. Imagine an explosion at a chemical plant, resulting in fires and potential chemical leaks. Spot, being equipped with advanced sensors, can detect a range of chemicals, sending data in real-time to emergency crews who can then take requisite action without having to venture into the unknown. Spot can also use thermal imaging to map the intensity and spread of fires, aiding firefighters in their containment efforts.

Alongside Spot, IBM also highlighted how Maximo is used in drones to monitor civilian infrastructure such as bridges. The Great Belt Fixed Link, for instance, is an 11-mile bridge and tunnel combination in Denmark, the largest construction project in Danish history. Previously, Sund & Bælt Holding A/S, the company that owns and operates the bridge, conducted manual inspections, hiring mountaineers to scale the sides and take photographs for examination in an inspection process that could take up to a month. Using drones with Maximo software, however, Sund & Bælt can gather data from photographs, with AI being able to carefully and efficiently analyse data to identify cracks, rust, corrosion, displacement and stress.

Both Spot and the use of drones with Maximo technology therefore highlight the significant increase in efficiency and safety that AI is leading. It also shows advancements in sustainability, with smarter operations being conducted.

Synthetic Persona Generation:

Using InstructLab and wastonx.ai, IBM ran a pilot project with a financial services client to synthesise personas with their own detailed individual traits and characteristics, amounting to the creation of bot versions of specific people.

These personas can help businesses with their market research. For companies wanting to know levels of interest in potential new products from people who would otherwise be hard to survey, these personas can act as these missing people, filling gaps in companies’ surveys.

This cuts costs, time and resources; with the technology to reach all corners of the market at their fingertips, businesses can choose to apply it where needed to overcome some of the time and labour-intensive processes of traditional market research.

Such is the quality and usefulness of these personas, one UK bank has already enlisted the use of them for the purpose of supporting their market research.

Human Resources queries:

In line with the overall theme of enhancing efficiency, IBM’s generative AI can also speed up employees’ HR queries.

By scanning for Frequently Asked Questions and related answers to these, watsonx can respond to an employees’ question swiftly and accurately. For instance, as demonstrated on the day, an employee can find out instantaneously how they can take an extended leave of absence simply by asking the chatbot what leave options are available to them.

The same applies for other HR queries, such as the amount of Annual Leave available to an employee or available bereavement policies and processes.

All in all, this reduces the long-winded process of a HR employee manually searching for information, making HR queries far more efficient.

Conversational Voice Building – Betting:

IBM, in collaboration with ABP, has been able to use generative AI – watson STT and watsonx.ai – to vastly decrease the time required to place bets on betting apps.

Previously, the creation of a betting slip would take an average of 4 minutes, with users themselves having to type, search and manually input the categories they wanted to bet on.

Now, using generative AI, this process has been reduced to an average of 30 seconds, with users able to place bets through just their voice. This is because the betting app records the user’s voice and automatically transcribes what was said.

The Large Language Model used in this process has even been trained to understand specific football lingo, thereby being able to differentiate between the names of players and teams and understand the nicknames of clubs.

Confirmation from the user by clicking a button is still required following the building of a bet slip using their voice, meaning any mistakes in transcription can be amended before the bet is placed.

Quantum Computing:

Perhaps the most impressive feature of the evening, the sheer power of IBM’s quantum computing system takes a lot to get your head around.

As was put on the night, it is not just faster than normal computers, it is something completely different; it’s not like comparing a car to a super car, it’s like comparing a car to a plane.

Quantum computing will therefore one day be used to solve big scale intractable issues. These include disaster management by public services, fraud monitoring in banking, and enhancing fuel efficiency for the aerospace sector. 

It also includes use cases that are not even known yet. In many instances, industries themselves do not currently know the problems they need solving and the power of quantum computing to solve them.

IBM’s quantum computer is reaching a point where it can be used to solve real world practical problems and is yet another example of how IBM continues to lead the world in innovation.

The above use cases have efficiency and innovation at their core. This, fundamentally, is what the sweeping age of AI is about and what IBM hope to capture in the technology they produce.

With negativity and fear towards the development of AI existing amongst the wider public, IBM’s showcase indicates that advancements can be a force for good. By demonstrating clear examples of this good in action, the hope is that public trust can be slowly but surely established.