Our bathroom cleaner announces in large letters that it removes ‘up to 100% of bathroom grime and limescale’. I suppose there could be a more meaningless claim, but really…?
Still, perhaps it’s actually a disclaimer to avoid legal action from those who believed that it would remove more than 100%.
My thanks to Kit Hodsdon, who, responding to yesterday’s post, pointed out that there was a name for a phenomenon related to something I discussed there: the Gell-Mann Amnesia Effect.
This term was first coined by Michael Crichton, and to quote the Wikipedia page linked above, it describes “the tendency of individuals to critically assess media reports in a domain they are knowledgeable about, yet continue to trust reporting in other areas despite recognizing similar potential inaccuracies.”
The page is worth reading for more info. For example:
‘The Gell-Mann amnesia effect is similar to Erwin Knoll’s law of media accuracy, which states: “Everything you read in the newspapers is absolutely true except for the rare story of which you happen to have firsthand knowledge.” ‘
And what about the name? Crichton said he had once discussed the effect with the physicist Murray Gell-Mann “and by dropping a famous name I imply greater importance to myself, and to the effect, than it would otherwise have”!
Regular readers might assume that I spurn all things AI-related, and this is not the case. I do use and occasionally derive benefit from the tools that tend to come under this all-embracing phrase du jour. But it does sometimes seem as if, for general questions, the LLMs can throw up wrong answers as often as right ones, and, like others, I then feel a compulsion to point this out. I had one week recently where three different ‘AI’ systems, in three completely different contexts, gave me three answers that were demonstrably wrong on key points.
So it’s important to know the answer before you ask them a question, in which case…
The real problem is the certainty with which assertions are made. There’s no expression of doubt, no humming and hawing, before the response.
Having been listening on my recent travels to the wonderful audiobooks of Patrick O’Brian’s stories, I thought it would be fun to ask ChatGPT about archaic naval terminology – did it know what was meant by ‘Three points off the larboard bow’.
It started with a cheery phrase along the lines of “Ah! Nautical terms! Always a source of interest.” and then went on to give various bits of authoritative information, even with helpful diagrams, but including the assertion that ‘A point in this context is one-eighth of a compass’s 360 degrees, so one point is 11.25 degrees.’
Mmm. Do a little calculation and you’ll see the problem.
I’m paraphrasing slightly, because when I went back to copy and paste the exact text, it had conveniently lost its history, and when I asked again, it made no mention of the ‘one-eighth’. (There are actually 32 ‘points’ on a compass, so the 11.25 degrees bit was correct. Four points are 45 degrees.) It’s a worrying thought: perhaps the system could detect that I was surprised and go back and cover its mistakes!
Anyway, it did get the rest of it right. ‘Larboard’ is an old word for ‘port’, which was abandoned in the mid-19th century because it sounded too similar to ‘starboard’. If yelled from the mast-top in the heat of battle in a gale, I guess this could cause problems. So ‘three points off the larboard bow’ means (roughly) 34 degrees to the left of the direction in which the ship is pointing.
Many, many years ago, when a couple of the projects I was working on started to get some press coverage, I remember noticing that, in general, every single article about my work contained errors. (There were a couple of exceptions — the Economist was one — but they were notable for their rarity.) These were generally unimportant mistakes, and they were made by well-intentioned journalists working for reputable papers back in the day when they could afford to do real research but who were, after all, humans. It was an important lesson for me in my youth: you can detect the errors in the things you know about, but remember that every article you read about anything is probably similarly flawed.
This is why I think it is important to keep taking note of the times we can detect wrong answers, because they will also happen in places that we cannot so easily detect. I wonder if adding more human-like phrases to the output of LLMs will enable us to take what they say with a pinch of salt, too? (Sea salt, of course.)
I realise that I should be slightly more cautious about my use of phrases like ‘today’ and ‘this morning’ in my posts, since quite a few of my readers receive them by email the following day. In the days of the Trump regime, phrases like ‘The news looks a bit better this morning’ have a very limited lifespan!
Ah well. Here’s yesterday’s (or the day before yesterday’s) Matt cartoon:
I came across an amazing article by Marcin Wichary at the weekend, about a font you’ve probably never heard of: Gorton. And that’s despite the fact that you probably encounter it very regularly.
The Hardest Working Font in Manhattan is a long web page, but even if you don’t read the whole thing, there’ll be plenty to catch your interest if you skip bits from time to time. There are even some interactive demos. But do read most of it, too.
It’s always good to be reminded, amidst so much of the online rubbish we see today, just how much brilliant work is also out there.
I probably use a Microsoft Office product only about once or twice a year, since, for ages now, I’ve preferred Apple’s Pages, Keynote and Numbers for normal day-to-day stuff. (I definitely recommend getting to grips with them if you’re in the Apple world and aren’t taking advantage of them yet.)
But Rose needs to use Word and so, like many others, we reluctantly pay for an annual Office 365 Family subscription, and a few months ago, the price of that went up by a little over 30%, from £80 to £105.
But here’s the thing. You don’t have to pay that new price.
You see, in a move that is particularly sneaky even by Microsoft standards, what they actually did was to add a new feature that not many people want: the Copilot AI system. They called this enhanced plan ‘Microsoft 365 Family’ and migrated everyone on the old ‘Microsoft 365 Family’ to it, charging them for the new facility.
If, like me, you positively dislike it when your software pops up and says, “Would you like me to write this letter for you?”, then you should know that you can switch to ‘Microsoft 365 Family Classic’ and go back to the old price, and this also gets you a new feature: the absence of annoying AIs!
They don’t make this option easy to find, though. In my case, I was set up for recurring payments, and on the web site I had to go to the ‘Manage subscriptions’, say I wanted to cancel the recurring payment for ‘Microsoft 365 Family’, and was then given the ‘Classic’ option at the old price of £79.95.
My sincere thanks to the AtomicShrimp YouTube channel for this video which alerted me to this dastardly practice!
I always love it when the more theoretical aspects of physics, so often the exclusive realm of mathematicians and those studying the origins of the universe, have a direct impact on our daily lives.
Take the GPS system, for example, which has so many challenges that it really shouldn’t work at all, as far as I can see. Quite apart from the very clever software and signal-processing needed to allow a weak radio signal, from a satellite tens of thousands of miles above you, to be diluted over a substantial chunk of the earth’s surface, and distorted by the ionosphere, and compromised by the weather, yet still be picked up by a small battery-powered device in your pocket when you’re sitting inside a moving metal box surrounded by lots of other noisy electrical signals… quite apart from all that, there’s another problem… and it involves Einstein.
Did you know you were using his Theories of Relativity whenever your satnav tells you how far it is to the next junction? I’ve always found this very pleasing.
GPS depends on being able to make very accurate time measurements, and the issue is that the satellites are travelling very fast, which means that time itself runs at a different rate for them than it does for the those of us down below driving round the M25. Their atomic clocks run more slowly than an equivalent on Earth. But a bigger effect comes from the fact they’re in a lower gravitational field, which causes them to run faster! Pleasingly, this means that both Special and General Relativity need to be taken into account by the GPS system, in order to work out these differences and stop a gradual drift, which would be visible over time on your satnav map and might make you think you were on the wrong road. Thanks for sorting that out, Albert!
However, for all the magic of GPS, it has its limitations, as you’ll know if you’re driving through a long tunnel, or between skyscrapers on the streets of Manhattan. And the delicacy of the GPS signal also means that it can easily be interfered with by, for example, an enemy on a battlefield. When the GPS signal is lost, navigation systems have to fall back on ready-reckoning using accelerometers and distance measurements to try and guess where you are. This is a process as old as navigation itself, but it is very fallible, because your knowledge of your current position is based on your position a little while before, and any errors in that process get magnified the further you go. The accuracy of accelerometers has greatly improved over time and become less dependent on things like the bearings of spinning gyroscopes, but it’s still a problem.
This is why a lot of people are awfully excited about the recent experiments with Quantum Positioning, which may offer a much more accurate way to do this in the future (and I would guess may be useful long before quantum computing!) Once again, theoretical physics may help us find out where we are. It may be rather a long time before you have this mounted on your dashboard, but perhaps not so long until it’s in ships, submarines and aircraft.
So how do you use quantum mechanics to work out your position? (Or, more precisely, your acceleration, from which changes in position can be derived?)
Fortunately, there’s a really excellent video by Ben Miles explaining the basics. Nicely done.
It’s easy for those of us who passed their UK driving test a long time ago to forget that the Highway Code is not a static document: it is updated from time to time and old drivers need to know about the changes as well as young ones.
For example, I didn’t know about all these changes in 2022, mostly to do with the interactions between different types of road users: drivers, cyclists, pedestrians and horse riders. Did you? They’re quite important.
In one of my YouTube videos, I talk about how I’ve wired up my solar/battery system to ensure the energy in my home battery isn’t ever used to charge my car (which has a much bigger battery, so doing this doesn’t normally make sense), while still allowing the car to be charged using any excess solar power.
I had a query from somebody who was confused about how it worked, so I did my best to answer, and we went to and fro in what became a decent-length conversation. He has a similar inverter to me, but had some fundamental misunderstandings about how it worked.
At first, I assumed this was because he had different goals: he lives in another part of the world where there’s a lot more sun and a much less reliable electricity supply, for example. But no, it turned out he wanted to do the same thing as me, but was convinced it wouldn’t work the way I had described it.
It turned out, in the end, that the source of his confusion was that he had asked four different LLMs (ChatGPT, Claude, Perplexity, and Grok) about how to configure the system, and they had all agreed that ‘battery power is never used to power loads on the “Grid” port’, which is actually incorrect.
What persuaded him, in the end, that my description was right, and that all four LLMs were wrong?
He read the manual.
A sombre mood here in our half-American household. The phrase that keeps running through my head is…
Elect me once, shame on me.
Elect me twice…
I’ve just come back from bobbing about in a small boat on the crystal blue waters of the Greek bit of the Mediterranean – a marvellous excerience!
I’m sitting in the tender here because, as anyone who has tried it will confirm, it’s much easier to land a drone on a boat that doesn’t have any rigging!
But just before I set off in the wake of Odysseus et al, I decided to spend a day in Athens visiting the Parthenon. Should you wish to spend a few minutes in my company doing the same, you can find a short video here.
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One of the surprising things about Octopus, the UK company from whom we purchase our gas and electricity, is that, despite growing to the point where they handle about a quarter of UK households, they continue to innovate.
For a long time, we’ve been on the ‘Octopus Go’ tariff, which means that for the four hours starting from 00:30 each night, we get electricity at less than one-third of the cost of the rest of the day. We make good use of this, charging our home batteries to the point where, combined with our solar, we very seldom use any normal (i.e. peak-rate) power.
We also charge our car during this time, meaning that our ‘fuel’ costs are about 2p per mile, and one of my favourite statistics is that, since it cost me about £600 to replace our car tyres recently after 30,000 miles, we pay almost exactly the same per mile for fuel as we do for tyre rubber.
All of this may sound very impressive, green and economical… just don’t ask me how much I’ve spent to get to this point! Still, I find it very satisfying.
One of the purposes of this post, by the way, is to remind anyone else also on Octopus Go that, from today, the cheap period has been extended to five hours: from 00:30-05:30. So go and reprogram your cars, car chargers, home batteries or whatever now, before you forget! For those of us who have a standard 7kW home charger, that means 35kWh of cheap-rate power per day, which probably translates into about 100-150 miles, depending on your car.
But Octopus also have some interesting features aimed at balancing the load on the grid during times of peak supply or demand. They’ve tried a few variants, and the availability of any particular one will be rather dependent on your postcode, but here we do quite well, as a result, I think, of generating vast amounts of wind power off the East Anglian coast and not yet having all the cabling that’s needed to distribute it effectively to other parts of the country!
One of these schemes is called ‘Saving Sessions‘, where, at times of peak demand, you can get paid surprisingly high rates per kWh for using less than your normal amount of electricity. At first, I ignored this because we use so little daytime grid power anyway that I thought it would be pointless, until a friend pointed out that even if your usage is normally zero, you can be paid for negative usage; in other words, for exporting to the grid.
“Oh ho!”, thought I, “I can do that!” And so, after a bit of programming, my home automation system notices whenever a Saving Session is active and starts discharging my house battery (and any excess solar) to the grid. These sessions only happen in the winter, and not very frequently, but we still managed to export 40kWh between November and March, earning us about £100. Yes, they really do pay as much as £2.50/kWh for energy we might have bought the night before for 9p. On rare occasions even more.
And finally, there are Octopus Power-Ups. When they think supply is going to exceed demand, they need to absorb it, and so they will let you consume as much as you want for free. Since this is primarily down to the weather forecast predicting strong winds, or lots of sunshine, or both, you don’t get very much notice: typically an email the day before or even on the same day. I just plug the times into my system, and when the moment comes, my car starts charging, my batteries start charging, my hot water starts heating, and so on. It costs me nothing, Octopus probably make more money the more I use, and everyone is happy. (Except my envious friends who don’t live in one of the blessed postcodes!) The main challenge was that I had expended so much effort over many months trying to configure the house to draw as little as possible from the grid, and I now had to set all of the components to do precisely the opposite for a short time and then revert! Still, that’s what home automation is for!
Octopus is a large company now, and like all organisations on such a scale, does have plenty of problems too. They suddenly realised at one point in the past, for example, that they had been billing me for gas but not electricity for nearly a year, and I got a very large bill that month. Also, I had smart meters installed for both gas and electricity, and the gas one has never worked, so I still have to go and read it manually. To be fair, this is a technical problem suffered at a lot of UK households by most providers, who didn’t realise that providing the electricity meter with connectivity and assuming that the gas meter could relay its reports through it using Zigbee wasn’t going to work when, as is often the case, the meters are on opposite side of a brick or stone house filled with competing 2.4GHz signals!)
But, in general, I’m a happy customer, and I hope they continue to explore new and interesting ways to optimise supply and demand. Further innovations will, of course, require me to keep tweaking my code, but, hey, everyone needs a hobby!
My thanks to my pal Gareth Marlow, who has a similar set-up and whose Home Assistant configuration helped me make mine much better! Gareth has also done some great YouTube videos analysing the costs and savings resulting from his home solar/battery system; perhaps the best I’ve seen on that topic for UK enthusiasts. Recommended.
© Copyright Quentin Stafford-Fraser
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