AI has existed for over 70 years
The articles in the news act as if AI is completely new technology. Of course, nothing could be farther from the truth. The first attempts to use machines to mimic human intelligence emerged in the 1950s. The first scientific conference on the subject was held in 1956, when scientists from all over the world gathered in Dartmouth to discuss the possibilities of neural networks.
Explosion in possible applications
In recent years, things have suddenly been moving incredibly fast. This is of course because much more (cheap) computing power is available, and because storage in the cloud makes it possible to collect and use much more data. With this, models are getting better and the technology is becoming much cheaper. That means there are many more possible applications. But when you look at the bigger picture, you see that the foundations were laid much earlier. For example, ChatGPT builds on chatbots that have been used in contact centres for years. The difference is that the training dataset is much larger. That makes it possible to use much more historical data in predictive models, which increases their reliability.
Shorter development time
What has also changed is that many AI models are offered off-the-shelf, often even as open source. The model often still needs to be trained with your own dataset, but you no longer have to program the algorithm yourself. This significantly reduces development time. And, more importantly, you need far fewer highly qualified staff. Training a model is repetitive work that sometimes requires domain knowledge, but even that is by no means always the case. There even are models, Large Language Models like ChatGPT for example, that don’t require training anymore because they are generic. You can just use it right away.
Take inspiration
Unsurprisingly, AI is the IT trend of 2024. In the Conclusion Emerging Technologies Trend Report, we take a closer look at different forms of AI.Patrick Stevens, CTO at AMIS Conclusion, explains for instance the ways you can use AI in designing, developing, rolling out and managing robust software. Maartje Keulen, Head of Data Science and AI at Conclusion Mediaan, inspires readers with several examples of how AI can increase efficiency in a business. Bastiaan Sjardin, CTO and AI Strategist at Conclusion Future Facts, goes into more depth about generative AI to answer customer inquiries. While Michiel Tebbes from D&A Conclusion talks about how he uses ChatGPT to create rewrites in healthcare.
Are you wondering where the possibilities of AI lie in your business? Take inspiration from the Conclusion Trend Report.
