RE-THINKING AI AT PANASONIC’S TOUGHBOOK INNOVATION FORUM
How will artificial intelligence (AI) change the way we work, innovate, and create in the future? Our recent TOUGHBOOK Innovation Forum in Stockholm delved into the real-life applications of AI and how it’s being used to revolutionise workflows across industries.
written by: ULRIKA STURK, REGIONAL MARKETING MANAGER (NORDICS) at Panasonic TOUGHBOOK
Our TOUGHBOOK Innovation Forum in Stockholm brought together the brightest minds from the region to explore how AI is moving beyond the buzzword and is making a difference – now and in the future. The agenda not only covered the latest TOUGHBOOK AI features, but the future possibilities of AI technologies, with insights from industry leaders that focus on use cases within sectors such as aerospace and defence, prehospital care, and IoT.
In addition to customers and partners such as Microsoft and Intel®, guest speakers included Marina Rantanen Modéer, Head of Autonomy and GNC at Saab Underwater Systems; Joanna Daffy Tiitus, Marketing and Communications Manager at Ortivus; and Nicklas Löthén, Head of IoT Product & Technology at Tele2. Here are their key takeaways.
1. Stop over-generalising AI
Likely due in no small part to popular Generative AI (GenAI) tools that were launched en-masse in 2022-3, AI has been thrust into the public consciousness in recent years. This has prompted an unprecedented wave of interest and experimentation in AI and machine learning (ML) solutions.
However, while GenAI is hitting the headlines, AI has now matured to the degree where businesses are implementing specific AI solutions within workflows across almost every industry to solve specific problems – but this is somewhat lost in the generalisation of AI.
For example, AI is now being used to explore how to use large language models (LLMs) to implement machine-based autonomy, enabling machines to communicate with each other and humans.
Reinforcement learning – one of the three principal ML paradigms – is also being used to educate machines on appropriate behaviours in any given environment to maximise output and rewards. Both of these problems use AI, but they are two very different applications of artificial intelligence which help to solve very different problems.
2. The AI boom
In the midst of the software boom that first started decades ago, few may have guessed that it would become a part of our everyday lives, and arguably taken for granted. The same can be said for the use of AI.
However, its journey into the day-to-day will be far shorter than software, as it’s used in an increasingly wide variety of applications,.
Whilst the concept of AI may still be uncomfortable for many, its increasing use in tangible, real-world solutions will help to change perceptions, leading AI to stop being viewed as a separate, visionary technology. Just how quickly AI takes to reach this inflection point will be fascinating to witness.
Whilst the concept of AI may still be uncomfortable for many, its increasing use in tangible, real-world solutions will help to change perceptions, leading AI to stop being viewed as a separate, visionary technology. Just how quickly AI takes to reach this inflection point will be fascinating to witness.
3. Data is (still) the new oil
Putting the array of consumer devices such as chatbots and virtual assistants to one side, AI will first have the biggest business impact behind the scenes.
As with any sector that deals with sensitive data or personably identifiable information (PII), the adoption of AI will be cautious in nature and more gradual. LLMs are already being used to streamline the collection and documentation of data, and other administrative tasks that chip away at productivity, in a variety of sectors.
For example, in healthcare and telecare, AI will be used to analyse medical records and information from multiple sources quickly and efficiently, helping medical professionals to quickly identify the required care for patients, which can ultimately help to save lives, or detect early onset of diseases.
Far from AI actually delivering the care, this is a prime example of AI technologies being used as a decision support tool, enabling humans to use vast amounts of data to derive actionable insights, and ultimately, decide what action to take.
AI adoption is accelerating and impacting a diverse range of sectors in very different ways. As we bear witness to the revolution, we should be wary of generalising and aware of the importance of establishing robust governance around AI use, enabling it to be safely leveraged to support people and processes.
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