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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 an 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 amount of 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 work and conceptually how 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 are 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 Camp 4 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 as 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, as to the insanely hyped and utterly misleading human-related vocabulary surrounding LLMs, this dates back to a 1958 press conference (!). This showcased 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 talk or write as 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 other than simply the awesome human skill of creating new ideas after new ideas until after 81 years these achieved a critical mass and produced 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 upsides and downsides – nuclear technology for instance can be used to keep us warm or to atom bomb us .

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 actual 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, their 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 me 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…

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The past decade has seen the most extraordinary innovation in any business sector in the UK and thence world since the industrial revolution . An amazing outburst of creativity and independent players emerged on the oldest and stodgiest sector of all – FS. The LFP was the first, and most blue-chip podcast to cover this scene starting in 2014. This episode is like a mini-documentary that takes us one fast-forward through the development and progress of Fintech as it happened and was perceived at the time.

A decade of the LFP represents a unique historical archive, a super-rare window, a time-machine to be able to look back in time and see how things were perceived at the time. However such is the volume of episodes that if you took on, as a full-time job, listening to every episode in order it would take you well over a man-month of full-on 9-5 listening to go through the whole evolution. I thought more preferable would be a one hour review of this exciting decade of innovation and entrepreneurialism instead 🙂

It is genuinely hard to recollect how much has changed without examining things from a contemporaneous perspective. Witness for example the following anecdote. Talking of chronology and the London tech scene, back in 2014 there was something called Silicon Drinkabout. That was great. Every Friday evening they got some company to sponsor drinks at some pub and one got not just beer but to hang out with tech folk. It’s these little things which really help oil an emerging scene. Anyway the point of recalling this is that even at such a scene the most common question I got when I said I was starting or had just started the London Fintech Podcast was “what’s a podcast?”…

And that was amongst London’s tech savviest folk! Things change so fast these days we tend to forget how fast they’ve changed.

Time does not permit me to cover all episodes – and every episode had many lessons – but I will cover the vast majority, enough to get a real-time on fast forward view of the scene. Doing this exercise certainly surprised me in many cases and I am sure it will too. It reminded me of doing annual appraisals – it was so hard for one’s perceptions not to be overly dominated by the most recent few months compared to rather earlier in the year.

In the next LFP 10th Anniversary Special Celebration Episode I will review the interaction of Tech at large and Society – a super-important topic contextualising not just fintech as such but all of our lives and society. But first let’s review 2014-2024 in the hottest of all scenes that absorbed the most capital.

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This is a super-short extraordinary LFP outside the usual programming schedule to alert listeners to the crime of mugging folks and then getting them to transfer under duress large sums of money to the thieves bank account. This is apparently on the increase in London and is well-known in countries such as Brazil and South Africa where people may routinely take burner phones with them when going into the City.

I initially learned about this risk in this Reddit thread.

Many people without reflection may in effect carry access to all of their money on a single device. We look at possible simple answers to avoid unnecessary risk.

There is also a shoutout for a Q& A in the 10th anniversary episode and instructions as how to send the Qs to me for answering in that episode.

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If you invent the world’s greatest Fintech App in your garden shed that’s impressive – but something only known to you. At which point you need to get the word out to relevant audiences. PR is an essential component in the modern world to help you refine and target that message and to get you and it into the relevant publications/podcasts et al that will reach your target clients and the market in general (think targets for next fund raise perhaps).

At a more macro level, the dark side of PR is that it is, as Musk said propaganda, and one often designed not in the recipients’ best interest, whether it be Bernays getting women to take up smoking or governments getting people to be injected more recently.

However that’s way above the Fintech space and in this episode Ben takes a very value-adding practical approach to what PR is, when you need it and when you don’t, what the value-add is, how to use it well and what to look out for when hiring a PR firm amongst many other insider-angles.

Ben is a long term player in the whole media and Fintech scene including the earliest days of Level39 and working at Balderton Capital VCs and formed his own boutique agency focusing on B2B Fintech and VC PR in 2017.

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One major way of innovating is to move into a domain with transferable and out of the box skills/ideas/technology. This presents obvious opportunities  for radical change yet naturally produces equally obvious challenges. In this episode we look at how 4 co-founders created a payments infrastructure Fintech that now connects an amazing 7.5 billion bank accounts, 6 billion cards, connect banks in 144 countries and have 620 employees with offices in 35 countries.

Ani came from FS and so understood not just how money currently moved but also the super-importance of understanding that its an incredibly regulated business.

The other three co-founders came from the telecoms world and had no idea of how money moved. However they brought in what the telecom industry does very well – namely builds at scale, can process small volume transactions and deliver them instantly.

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The Governance of FS as a whole affects all of our lives as we saw in 2008 let alone in many individual examples of FS/Fintech businesses failing and losing clients money. In our digital age virtually all of our money is digital and next to no-one sees a share certificate any more so all of our investments are digital. Thus what might appear to be a refined topic for a few is at the heart of all of our lives – money being used for roughly everything and savings equating to money saved for tomorrow.

As a result of this central role of money in economies, Boards in FS have always had to be – lets put this mildly – “rather more careful” than Boards of companies which if they fell over would “domino” not very far. Not only do many FS/Fintechs “take care of” clients money but money itself in the current financial model is created out of thin air by banks.

Add to these long standing issues the ever-increasing burden on Boards as a whole from the always metastasising Regulatory State, ever-greater minutiae in FS per se and the State using companies to enforce social agendas which even a decade ago would have seemed unlikely/bizarre and we have a very challenging cocktail.

Neil has 20 years expe4rience on Boards and Chairing sub-committees of FS and Fintech Boards and is thus well-placed to guide us through this labyrinth.

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The tech world focuses heavily on the “succeed fast or fail fast” model of tech growth. In part this is as VC firms generally have limited life funds and hence cannot handle slower models but is also as the tech press loves the hype/condemn cycle implicit in this. However generally most businesses do not follow this model. Whilst rapid success comes to a few, for more it takes rather longer and for many its a slow rocky path. After all hottie OpenAI (ClosedAI?) took quite some years to make a noticeable splash.

Ruzbeh founded City Falcon a decade ago and whilst, like us all, preferred rapid success, he has moved into the more marathon development model of the business. I was particularly enamoured of his very human/ethical perspective and clarity of the social costs of the “succeed or fail fast” model – namely that it comes at the price of burning your friends and family and employees just so that you can get onto your next gig as fast as possible.

With a huge desire worldwide to move on from all business being dominated by neoliberalism – you know, the “humans qua just another resource model” (with some virtue signalling perhaps as perfume to cover the heartlessness of seeing people as resources) – this is a good time to dive into the slower model. This slower model is definitely no picnic – the longer you hang out in business or in life the more tsunamis you will have to face.

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The Founder(s) is(are) at the heart of creating something new that literally never existed before.  However they very much do not do this in vacuo needing to entice and hire a team below them but also, less well understood, a team around them. The surround will at some point coalesce into a formal Board (as opposed to a pro forma Board for Day0 – and for many days after – NewCos).

In this episode experienced NED/Advisor/Mentor/Angel Nic Lenz and I discuss experience in this field with particular reference to formerly senior BigCo folk who wish to get involved in the SmallCo world attracted by the creativity, and let’s face it greater fun/thrills&spills but also to educating the first time founder, or potential founder who will naturally realise they need a CTO et al but may think that “the organogram below them and some dosh” is all they need.  It’s certainly the minimum viable organisation but is it the optimal organisation for their personal support/challenge as well as the company’s future?

Both Nic and I have seen countless examples of where the right “grey hair or no hair” experienced folk even though very much part-time contributing to the company can make all the difference between success and failure. We also discuss the challenges of transitioning from BigCo to SmallCo – which applies to both founders and venture accelerators – along with mentoring mentors and the key essences of both sides of the venture creator and the venture accelerator equation.

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As always there is a fascinating phenomenon when the globalised world of tech meets the localised worlds of custom, people, rules and regulations. As recently as LFP243 we dived in to the world of tech as a whole in Berlin and today we dive into Fintech in France. Needless to say France is a massive market, well banked and a real venue for Fintech. That having been said there are, as always, some downsides. In this episode we have a fascinating historical, philosophical and very practical conversation about the nature of Fintech in France.

Louis is well-placed to discuss these matters being not only a co-founder of Hokodo which is based in Paris and has more than 100 staff, most of whom are in London.

Furthermore he is very multicultural in a European sense having been brought up as first a German speaker in Champagne and then Strasbourg in Alsace which looks both east and west, not least of which as it has been part of Germany and of France at varying times. He moved from there to Paris and describes the Paris-isation of French students and the de-regionalisation process they go through. Furthermore he has worked in Switzerland – also rather Franco-German as well as the UK. Thus who better to lay out the pros and cons of Fintech in France?

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In this episode we take the opportunity to talk to one of the most credit risk experienced men in Fintech who has ranged from a dozen years at seminal Capital One through managing Barclay’s £40 bn portfolio, being CRO at Funding Circle to now founding his own Fintech to mechanise further short term SME liquidity financing, Jerome’s stats are that banks automate roughly 5% of this type of lending whereas he believes the vast majority to be automatable.

We discuss what credit risk is in the age of data, automation and Fintechs and dive into the multiplicity of models used in a credit pipeline not just for risk but for wider business management and portfolio management purposes as well as looking at the parameters of automation versus human input. We also look at Jerome’s experience of what is stable about the models value and what is not over significant economic dislocations.

Importantly there are a huge range of uses of credit models above and beyond the simple case of credit risk and Jerome gives us a flavour of these across his own career – a fascinating stat being the incarnation which had 25 models in operation :-!

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