COVER STORY


‘Consciousness and intelligence are two very different things’


is amazing in its handling of completely unmanageable amounts of data and its ability to work out what the next meaningful word in a sentence should be, but it differs from consciousness in many ways, also by relying on intact hardware’s partitioning and software’s functioning. Consciousness, on the other hand, has an amazing resilience.


If a person loses a sense, for example, the sense of sight, the area of the brain that was involved in processing visual impressions can be repossessed and used for other purposes. If the two halves of the brain lose their connection, consciousness splits into two separate cognitive systems that function independently of each other to such an extent that one hand can try to inflict damage on a person or object while the other tries to protect. Consciousness and intelligence are very different entities.


Re-revolution


AI is a revolution in its own right, fascinating in its ability to support and replace human intelligence. We are facing another earthquake-like upheaval in the way people work, which corresponds to the effects of arable farming, industrialisation and digitisation. Completely new ways of working, organizing, and perhaps distributing that are as revolutionary as the Internet has been. And with the same business opportunities and threats. AI opens up new avenues, such as bionic design and biomorphic topologies, design fields inspired by structures, methods, and processes found in biological systems, using organic-parametric tools, see e.g. Hyperganic’s sunflower inspired design for a heat exchanger. Wouldn’t it be exiting to see a bionic designed washer extractor? Or nature’s process designs used on the washing process itself.


TRIUMPHANT RESULT: Hyperganic improved the performance of a Trumpf heat exchanger x 10


Think


Imagine if, at the beginning of the 1980s, you had been able to see what the internet would develop into and put your savings into a few of the big internet- based companies that we all know and take for granted today. Or if you could see today what your own company can develop into in 10 years, if you get it right, and what happens if you don’t. It is hard. The differences are big, just like the differences in producing horse-drawn carriages and cars. Both are vehicles, but don’t have much in common other than their mission statement. And the transition from horse-drawn carriages to cars is painful. It requires cannibalisation of one’s own business and establishing a new set of references; a radically different way of thinking and working. So, the thousand dollar question here is: If you wash surgical clothes for hospitals in washer extractors today, some of them perhaps 30 years old, how should your laundry look to be competitive and still thriving in 10 years? What should the factories of the industry’s suppliers look like? How big is the risk that a capital chain brings the right AI skills from other industries, and establishes itself with completely new development technologies, design methods, manufacturing principles and factory setups? What would it look like?


Cases


We’ve already seen intriguing and exiting uses of AI in other industries, where the solutions do not just improve performance 10% to 20%, but make them up to 10 times better. QuantumBlack has helped Vistra Corp – a large power generator in the USA – on its way to delivering $250-$300 million in identified EBITDA. One seasoned Vistra Corp operations manager says: “There are things that took me 20 years to learn about these power plants. This model learned them in an afternoon.” AI today is used in such diverse contexts as: Cancer treatment: Analysing medical images leading to earlier detection of tumors and anomalies, improving treatment options, and survival rates, Precision Agriculture: Optimizing irrigation, fertiliser use, and crop monitoring,


Natural disaster prediction: Analysing weather patterns and seismic data to predict disaster risks and design emergency response strategies, Lifespan predicton: Danish researches trained a transformer model (as used in the LLMs) on 5+ mio. Danish people to predict early mortality, the chance that someone will move, and personality nuances related to extraversion, based on medical history, education, job, income, marriage status, and so on.


In a forthcoming article, we go deeper and look at the technologies AI includes, and at the connections between data, tasks and applications. In this issue there is more to read about AI in laundries, pages 22-25


@LCNiMag May 2024 | LCNi 11


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