As we embark on the year 2024, we are taking a significant leap forward from Artificial Intelligence to Augmented Intelligence (AI), where humans and robots collaborate harmoniously. The concept of Adaptive Intelligence underscores the importance of adaptable leadership in unpredictable environments.
In this write-up, Dave Wild explores how LLMs unlock innovative possibilities through language, while MLMs recognize the role of human movement in leadership.
"You know the meaning of AI. How about LLM?
Of course when I say AI, I don’t mean Artificial Intelligence. You’ll gain greater organisational momentum in 2024 by reframing it as Augmented Intelligence. Moving beyond the ‘Artificial’ associations of fake and unreal. Elevating the cultural change needed, from people vs robots to people with robots.
Or maybe go a step further and talk about the new AI – Adaptive Intelligence. Now adaptive leadership skills have become critical for navigating and leading change in unpredictable environments.
Too often all this talk of AI remains at a surface level. Causing many leaders and teams to believe that the machines are now reasoning. Almost sentient. Getting ever closer to human levels of intelligence. Otherwise known as AGI – Artificial General Intelligence.
The reality is far more complex.
Stretching back in time over half a century, the development of artificial intelligence has passed through what are known as AI winters. Time and time again surprising leaps forward in capability occur, then new challenges – from hallucinations to energy demands – flatten out the exponential curve of progress.
Last year the AI season changed again. Five years after the development of GPT-1, ChatGPT’s exponential uptake was soon followed by Bard, Copilot and many other ways of accessing this new breed of generative artificial intelligence, GenAI.
This historical inflexion point depended on a pivotal breakthrough discovery:
That machines don’t need to reason, to be – or appear – intelligent.
Human reasoning and intelligence have been encoded over centuries in our languages. Learning to talk like a person bypasses the need to actually think like a person. So instead of learning to think and reason, machines took a shortcut by developing the computing ability to work out what… word… to… say… next.
With Large Language Models. LLMs.
Of course the neural science is far more complex than my passing summary suggests, with the models continuing to evolve and adapt. While very significant and complex barriers to finding the next S curve of growth remain ahead.
[If you’re thinking can’t AI just solve that complex problem – it might be better to instead think something like, can’t AI just construct some sentences that sound like highly plausible solutions, that might or might not prove to be correct.]
With all this change in mind, the critical question is:
How are you choosing to adapt this year?
Are you spending less time talking about superhuman intelligence and more time considering what innovations might now be possible through smart models, combined with your own unique language and data?
For our own business, recognising the inherent limits – and power – of our human minds we’re working not only with LLMs but also MLMs.
Moving Language Models.
Machines can store and compute far more data than our brains can ever accurately recall. However the machines aren’t even close to being able to move like people – whether it’s physically moving ourselves or emotively moving others.
Which is at the heart of great leadership.
Guiding and inspiring others with just a few short words. Whether it’s a reminder to “Amplify Hidden Voices” or encouragement to “Hold Strong Ideas Lightly.”