AWARENESS
THE AI APPROACH OF INFORM
Even though Large Language Models (LLMs) – with ChatGPT as the most popular representative – have attracted a lot of attention from the public lately, a whole range of technologies is now currently summarized under the term “AI”².
INFORM has always been building algorithms and software to optimize business processes using artificial intelligence technology, with strong roots in the advanced mathematics of operations research (OR). Based on the specific use case, we employ appropriate methodologies according to the task at hand, including search and optimization techniques and heuristics, supervised and unsupervised learning, or combinations of those. We call this “customer-centric strategy” in our Hybrid AI approach.
Our over 1,000 employees serve more than 1,000 current business customers worldwide, including container terminals, passenger airports, financial and telecommunication service providers, industrial operations, wholesalers, storage, and transshipment hubs, as well as shipping companies. We have more than 50 years of experience with business processes and AI methodology, including all of the above classes of AI algorithms. However, we are not only interested in AI technology. Our industry experts aim to leverage the potential of algorithms and software in close collaboration with our customers, as part of their digitalization and optimization initiatives. As part of our B2B approach, our AI applications typically apply to well-defined business contexts, which can typically be used to contain potential AI-related risks.
We believe that the above-mentioned AI methods will see even more widespread business adoption in the coming years and decades. We aim to leverage advancements in methodology and computing power even more, for the benefit of our customers. This includes AI that makes even more business data available (e.g., as part of privacypreserving perception AI) as well as exploitation of business data as part of focused-process AI use cases up to large-business AI models, and language models for human-computer interaction. We embrace the opportunities that research and technological advances bring and believe AI incorporates promises to increase human agency.
As an example, LLMs hold many positive promises, not only with regard to assisted authoring of texts, but in particular with regards to improvements of the human-machine interfaces to business systems. On the other hand, we are aware that AI advances may provoke fear and entail risks. All the more, we see the need to define the circumstances under which AI is used, as laid out in our Responsible AI Guidelines.
² See e.g. the AI definitions by OECD and the European Union