Unmaking Sense

Episode 8.74: APIs -what they are, why they matter, and what they do for chatGPT and siblings.

Understanding APIs in terms of simple human interfaces with much more complex systems, and how that works in relation to computers and particularly artificial intelligences like our chatbot. We consider the implications of the relationship between chatGPT and things websites Zapier and Wolfram Alpha, and what this means as a staging-post on the path towards artificial general intelligence.

Episode 8.73: The trans-human and the impossibility of imagining a world bigger than our own.

We tend to imagine that it “must have been obvious” to those from previous generations that some of the things they did, believed or acquiesced in were wrong, but is that so? Can a “Russian doll” imagine the next larger doll, or only smaller ones? And which of the things we do, believe and acquiesce in will look morally dubious from a later or just another vantage-point? Particularly a trans-human vantage-point.

Episode 8.72: The trans-human achievable by advanced GPT architectures is only the first of many.

Human beings are used to thinking of themselves as being top dog in certainly the world and until relatively recently in the universe. The advent of something that is genuinely transhuman in knowledge, wisdom, reason and analytical power threatens that position. Yet we like a Russian doll look down on those inside us, that we perceive as smaller and less sophisticated than us, and we are very reluctant to think, or conceive of the possibility that there might be Russian dolls that are bigger than ours to whom we will seem weak, foolish, pathetic and deluded. Yet just that is what the advent of advanced artificial general intelligence involves, supposes, achieves. There is already some humble pie to be eaten.

Episode 8.71: The addition of plug-ins to the GPT family is understandable, but comes at a price.

Providing access to third-party APIs involves a major new step in the generation of artificial general intelligence. But precisely because all the GPT family so far did not reach out to 3rd parties, to the Internet or other vendors the product of their neural nets arose from what they “knew”. When they can “look up” things external to their own neural net, they cannot “think with them” and so this welcome new stage on the road to AGI is only a stepping-stone: to complete the journey all this will need to be brought inside.

Episode 8.70: How new chatbot technology breaks the grip of the world.

More on the theme of the global changes that will ensue from this chatbot technology. Pastimes and “passtimes” suddenly became all the more necessary.

Episode 8.69: Chatbot coders need to learn the adage “When in a hole, stop digging!”

Chatbots including GPT-3.5-turbo do get things wrong and they do get coding wrong. In particular, if you ask them to help out with your coding, they will very often go forward when the sensible move is to go back. Retracing their steps going back to a previous working state isn’t something they’re very good at; that’s partly because of the way they’re built. If they were to learn that and to give advice to that effect, things would fundamentally change, and I’m sure one day soon they will.

Episode 8.68: The lack of blame in a chatbot, eliminating bullying, promises to change everything.

The fear of making a fool of oneself is one of the principal obstacles and inhibitors to asking the questions that we need to ask. Throughout life, there are many questions that we would like to ask, but do not because we fear that others may laugh at us. But the emergence of a benign universal tutor in a chatbot promises to change all that, and so the world.

Episode 8.67: This is the way the world ends; this is the way …: not with a bang, with a Whisper.

I report back on my experiences with transcribing the digital recordings of the episodes of the podcast and reflect on some of the implications for civil liberties for oppression, and for all of us if this becomes widespread as it certainly will.

Episode 8.66: Electricity and the consumption of power: an exercise in machine learning.

Fresh from the triumph of managing to get through, and actually speak to somebody from my electricity provider. I started thinking about the consumption of electricity by different appliances and particularly by those that sit quietly in the background consuming electricity without anyone really noticing what are called phantom appliances. And I then thought this could be a good test case for machine learning, so I started to find out if I could do it.

Episode 8.65: The arrival of chatGPT-4 and some reflections about coding.

We discuss GPT-4 and consider some data structures in python.