On the Edge of The Artificial Cognitive Age (Phase 4)

You catch me standing on a windswept ledge between now and what will become the much-hyped promise of a profound technological transformation that will change how businesses operate, innovate, and think.

Hardly a LinkedIn post passes without yet another AI evangelist promising limitless rewards just across the river Jordan.

Large language models (LLMs), like OpenAI’s GPT, claim to develop an entirely new approach to human cognition that opens avenues for creativity, efficiency, and strategic decision-making.

From GUI to LLM

Once beloved by 1990s comic-collecting geeks, the familiar graphical user interface (GUI) initially made computing accessible to all. Today, LLMs go beyond supporting tasks. They invite us to open Pandora’s Box of connected knowledge, taking our hands as cognitive partners.

This partnership promises to spark imagination, enhance customer experiences, and provide real-time insights previously reserved for those with years of experience or political power.

Cognitive Collaboration

As we consider the possibility of AI even usurping us as parents – for example, writing and reading kids' bedtime stories, we’re encouraged to embrace “cognitive collaboration.” This goes beyond the give-and-take of past transactional relationships. Instead, it supports partnerships that build on what exists rather than regret what hasn’t been.

Complex problems can be dissected and reimagined. Today, gathering and regenerating insights from data in real-time conjures up previously unimaginable discoveries.

Democratising Innovation and Strategy

LLMs level the playing field. While small businesses (SMEs) are agile, they rarely have the resources of global conglomerates. At the same time, large corporations are often trapped in bureaucracy, preventing swift action.

Suppose the tech giants behind AI models are to be believed. In that case, LLMs are ready for the next phase in tasks like further developing customer personas, creating more empathetic and stylistic content, and forecasting trends second nature. They promise to quickly craft personalised strategies, scale creative assets, and test new concepts without significant upfront costs.

Assuming they are to be believed.

A recent Gartner report suggests that one-third of generative AI (Gen AI) projects will be abandoned within eight months from today.

At scale, AI can be expensive.? Simple tasks like coding assistance using a Gen AI API can cost around $100,000 to $200,000 upfront, with an additional $550 per user annually. More complex AI models can require $5 million to $20 million upfront, with annual user costs ranging from $8,000 to $21,000. While some businesses report increased productivity, it is unsurprising that Gartner warns ROI from AI may be hard to quantify.

Cognitive Interfaces: The Next Evolution

Despite these challenges, innovators, early adopters, and salespeople trying to shift units rave about Cognitive User Interfaces (CUI), which enable faster, more innovative processes through conversational Neuro-Linguistic Programming (NLP) AI.

With the year 2030 fast approaching, they believe we are nearing "data ubiquity". Data will be embedded into systems, processes, channels, interactions, and decision points, driving automated actions overseen by professionals. In marketing, CUIs will align content with consumer sentiment, support real-time decision-making, and offer personalised experiences on a large scale.

Then, there are quantum-sensing technologies. These will produce even more accurate, real-time data on product performance, from cars to medical devices. AI will analyse data to recommend and perform targeted software updates. Generative AI (Gen AI) agents, equipped with detailed historical customer data, will interact with digital twins of customers to test personalised products, services, and offers before releasing them into the real world. Meanwhile, clusters of large language models (LLMs) will work together to analyse individual health data, enabling the creation and deployment of personalised medicines.

David Bowie

The Joys of Iteration

Balancing on the windswept cusp of now and tomorrow, I’ll bet on what dictionaries might announce as the word of the year. ?Whilst “LLM” has a good chance, my Crypto is on "iterate."

LLMs are about iteration — a back-and-forth Gyro-wheel between humans and machines to fuel creativity.

They are about building the future, not getting stuck in the past.

Leadership in the Artificial Cognitive Age?

Before embracing Xanadu's potential, we must ensure that AI tools enhance human creativity while maintaining accountability and decision-making. Stay open to balancing the practical uses of large language models (LLMs).

After all, the Artificial Cognitive Age remains an unknown and deep challenge.