Most people have some intuitive idea of what AI is, but very few manage to boost this understanding to the next level: AI fluency. If more become truly AI literate, this will positively impact AI’s future. Thus, benchmarks for measuring and defining levels of AI literacy are key.

2023 could very well mark the rise of ‘ubiquitous’ AI, as the tech makes its presence felt in virtually every domain, and as more and more AIs show the ability to perform multiple general tasks, rather than just one or two specialized ones. AI expert Kirk Borne looks at 12 steps for data-driven medicine and healthcare, as well as 10 trends in AI to keep an eye on in 2023.

Last year, The Yuan contributor Kirk Borne predicted the evolution of AI in 2022. He takes a look to see whether 2022 has represented another year of growing macro trends in the global AI sphere, and whether it has continued the trend of opening up many new ways of thinking, surprising innovations, and more stable solutions to critical problems.

One often hears that AI is the future, and that it is poised to change the world in the coming years. However, such grandiose statements often lack clarity and are not helpful in trying to decipher which specific areas are advancing thanks to AI, which are lagging behind in the implementation of AI, and which are simply not living up to the hype.

Mistrust of data-sharing abounds, but its goals are ideally positive and potentially beneficial, and shared data is actually non-identifying to any specific person, and this is as true in the medical or health industry as in any other, DataPrime’s Chief Science Officer Kirk Borne explains, as he fetes Alan Turing’s 110th birthday for The Yuan’s Open Data 2022 series.

The Yuan contributor Kirk Borne presents the fourth article this week on The Yuan platform predicting the evolution of artificial intelligence in 2022. He predicts another year of growing macro trends in the global AI sphere which will open many new ways of thinking, surprising innovations, and more stable solutions to critical problems.

Multimodal artificial intelligence is the new kid on the AI block. It uses several data types, such as image, text, speech, and numerical data, and combines them with multiple intelligence processing algorithms to achieve higher performance. Data scientist and astrophysicist Dr Kirk Borne applies some context to multimodal AI’s ability to sense, understand, assimilate, synergize, and learn from multiple diverse inputs.

Kirk Borne discusses five exciting examples of valuable research advances recently announced that are either already associated with artificial intelligence or will be soon, including a new model able to predict how an infectious disease leaps from one species to another.

This cogent article by Kirk Borne employs mathematical reasoning to explore how smaller companies’ collective investments - the ‘long tail’ - drive the advance of artificial intelligence even more than outlays by bigger players, particularly in healthcare.