LLMs, of which ChatGPT is the most well-known, are perhaps the most awesome tech invention of all time. Even experienced AI folk didn’t see this coming. Most if not all of us will have used ChatGPT. However understanding of how they work is for most people either totally missing or totally misled by anthropomorphic language – thinking, learning, hallucinating, learns like a human, is like your brain and so forth. None of which are actually true in the slightest.

In this super-special episode I reject all the utterly misleading language that is entirely off the mark and instead focus on what LLMs are schematically two programs that process data like all other programs using no different programming languages or technologies – well other than needing an astronomical computing power which so enriched Nvidia shareholders.

I explain using only a simple excel spreadsheet model how both of these programs ~the “training” program and the ~”Chatbot” program and how conceptually one could create one in Excel.

Having established that listeners will really know – in ways they can explain to others what LLMs are and not be misled by human terms which the currency of so many LLM descriptions.

LLMs appear to be a very recent and overnight success. However like the Beatles there was a long hard slog to get to say the Camp4 on Everest at which point they started to become noticed and from where it appeared to be a relatively short walk to the top of Everest and a mystery about how rapidly someone can get there.

But John Lennon and Paul McCartney were playing together in dive bars and village halls from 1957 until they summitted in 1963 with their first Number One.

The climbers on Everest may have gone all the way from London on the way to Everest.

And for ChatGPT phenomenally the journey started as far back as during World War 2 – an astonishing  81 years ago!

The road to ChatGPT was long and winding with all sorts of ups and downs including most of the specialist AI researchers deserting the field in the so-called “AI winter” from 1969 onwards.

It is a truly astonishing tale and, fascinatingly to the insanely hyped and utterly misleading human-related vocabulary surrounding LLMs, this dates back to a 1958 press conference (!) showcasing the US Navy’s Mark 1 Perceptron machine – a hardware-only machine which was created to aid the navy in image detection where as wikipedia says:

“In a 1958 press conference organized by the US Navy, Rosenblatt made statements about the perceptron that caused a heated controversy among the fledgling AI community; based on Rosenblatt’s statements, The New York Times reported the perceptron to be “the embryo of an electronic computer that [the Navy] expects will be able to walk, talk, see, write, reproduce itself and be conscious of its existence.”

The blurry photo on the left is of the perceptron and unsurprisingly none of it and its successors never did walk, talk, see, write, reproduce itself and be conscious of its existence.

Indeed it took perhaps fifty years to develop robots that could walk or computer programs that could see, write and talk but over 70 years to ones that could take or write intelligently as ChatGPT et al do.

Even then ChatGPT and other LLMs are like all other programs – they simply take input, do some computations and create output using no different technology from any other computer program. Their awesome abilities rely not on any magic simply the awesome human skill of creating new ideas after new ideas until after 81 years these achieve a critical mass and produce results that no-one expected – even the experts.

This Special is Part 1 of 2. In Part 2 we will look at the risks of this new technology – all new technologies come with benefits and problems – nuclear technology can be used to keep us warm or to atom bomb people for instance.

However as the world of risks in LLMs and AI in general is dominated by insane sci-fi visions the field is entirely ungrounded. To get to that episode it is necessary to understand the nature of an LLM and how it works. Only then, alongside its abilities as a program, can you start to form an opinion as to what it’s consequences are.

Will LLMs, as their capabilities and powers grow, decide – like WEF luminaries that the people users are “useless eaters” and start releasing gain of functioned viruses, feed us bugs and bankrupt us with so-called green taxes to funnel ever more money upwards? Or will LLMs not turn into the WEF and instead remain as a powerful tool on your desktop no more threat to you or I than Excel? Or something in between?

Tune in to the next episode to find out but first find out what LLMs actually are and the amazing 81yr tale of their creation.