The Braindump Blog

At last the most important top X things of 2023 post is out. Here’s Rolling Stone’s take on the 21 most defining memes of 2023.

Shamefully, I only even vaguely heard of around 14 of them. Not sure whether I can blame that on the great fragmentation of the Internet, my grumpy refusal to participate in most of the big social media networks or simply old age.

In case you want to test yourself with just the titles, here’s the list along with a tick for the ones I knew of.

• Angela Basset Did the Thing ❌
• Skibidi Toilet ✅
• Boston Cop Slide ✅
• Timothée Chalamet as Wonka ✅
• Tube Girl ✅
• Congress’s Vote for Speaker of the House ✅
• Kevin James ❌
• Big Red Boots ✅
• Chinese Spy Balloon ✅
• Nepo Babies ✅
• Dupes ❌
• M3GAN ✅
• The Roman Empire ✅
• Girl Dinner ✅
• Orca Attacks ✅
• One Margarita ❌
• Babygirl ❌
• Serving C*nt ❌
• Planet of the Bass ❌
• Grimace Shakes ✅
• Barbie ✅

(Nearly) new year, new URL. I’ve kept this blog up long enough it’s time to give it its own big-boy domain name.

From here on in it’s thebraindumpblog.com.

In theory going to the old address should redirect you to the shiny new one.

Busy wasting time on The Great Scrollback of Alexandria.

This is a preservation effort, attempting to capture the funniest, weirdest, and most memorable posts before Twitter completely burns down.

The Verge does the world a service after the tragic decline of the service formerly known as Twitter by preserving some of its much loved bangers.

One more reminder that nothing you put on other people’s sites necessarily lasts forever, no matter how iconic. Nor most likely will the Verge for that matter.

It’s been a record-setting year in terms of how many research articles have had to be retracted from scientific journals for being wrong in one way or another.

As Nature reports:

The number of retractions issued for research articles in 2023 has passed 10,000 — smashing annual records — as publishers struggle to clean up a slew of sham papers and peer-review fraud.

Good news if it means the scientific record is being cleaned up, bad news if it were to mean that the rates of fraud and serious errors are increasing.

To be fair, an absolutely mind-boggling number of papers get published each year these days. Those 10k papers are only equivalent to around 0.2% of papers that were published this year.

8000 of the papers were all from the same publishing house, Hindawi, an unwelcoming $35-40 million surprise for its recent owners, Wiley.

📚 Finished reading Being You: A New Science of Consciousness by Anil Seth.

This feels like a book that’s going to be hard to summarise. It doesn’t help that I read most of it a year and a half ago whilst on a sun lounger. But I also found it a fairly dense and complicated book. Although a tome on the subject of “what is consciousness and how does it work?” could hardly be anything else. A key aspect of the topic is after all colloquially known as “the hard problem” - although Seth believes that particular aspect isn’t the one that we should be trying to solve in the first place.

The famous “hard problem of consciousness” is to figure out why the presumably physical inputs we receive from the external world lead to our inner phenomenological experiences. Why do we experience certain vibrations, in the form of sound waves, as music? Why does that experience of “music” make us feel things? Sad, happy, warm, awe-struck, or anything else on the wide-ranging human palette of feelings.

Why does this particular wavelength of light generate the experience of an intense red, and how come it makes us feel relaxed, or on edge? In summary: why does being exposed to physical phenomena make give us an “experience”? Both as a general question, and also, for a given single input why that experience in particular?

Seth thinks that’s the wrong line of inquiry. He wants us to think about the “real problem” of consciousness. By his telling, that means that the goal of science should be to explain, predict and control the phenomenological properties of consciousness. Or as he writes in an article for Aeon:

…how to account for the various properties of consciousness in terms of biological mechanisms; without pretending it doesn’t exist (easy problem) and without worrying too much about explaining its existence in the first place (hard problem).

First up, his definition of consciousness. Here it’s basically “any kind of subjective experience”. But, importantly, the experiences are indeed subjective.

We do not perceive things 1:1 as they are. This doesn’t take too much introspection to figure out even without the aid of a complicated book. Seth describes our perception of reality as a “controlled hallucination”. There are other types of hallucinations - LSD inspired ones for instance. But the shared hallucination that (almost) all of us agree on at a given point in time is the one that we choose to call reality.

We experience colours when what is actually out there is merely photons. We experience music when what is out there is merely vibrations. There surely is a “truth” out there, but we have no direct access to it. Rather, our brains create our conscious experience from its inputs. This explains why we can be predictably mistaken about things. Think for instance of visual illusions. The white & gold / black & blue dress that broke the Internet a few years ago is an obvious example.

…our perceptual experiences of the world are internal constructions, shaped by the idiosyncrasies of our personal biology and history

Why have we evolved to do this presumably computationally intense and certainly extremely unintuitive hard mental work? Because, of course, it helps us get through life.

The discomfort we feel when hungry is useful from a survival, and hence evolutionary, point of view. It motivates us to seek out food. Particularly energy dense food that in times gone past would have given us the most survival bang for our buck. The enticing taste of chocolate thus isn’t some random weird intrinsic property of its constituent molecules. It serves a function. Our conscious experience of the deliciousness of it motivates us want to seek out and consume it. In that way we can replenish our energy stores, and stay alive.

Colours provide another useful example. The properties of the light reflected from the same object in dark surroundings compared to well-light surroundings can be dramatically different. The actual stuff that hits our eyeballs - the sensory information - is thus very dependent on our environment. But it suits the way we work in the world for us to understand that it’s the same object. We still feel that the blue shirt that we previously saw in the midday sun is blue even when the actual sensory information we receive looking at it in the dusky evening is very different.

We perceive the world not as it is, but as it is useful to us

The brain can be thought of as a prediction machine that takes the inputs it receives from our senses and produces a guess of what caused those inputs, of what is out there. This is necessary because knowing what is out there in our environment is a fundamental requirement for us to survive. With no way to access raw truth, our brain has evolved the ability to make educated guesses, or, to put it more formally, predictions. Our conscious sense of reality is essentially those predictions.

Our impression of reality is constantly updated as the brain receives further sensory input. The aim is to reduce prediction errors, likely via Bayesian reasoning principles. Our inner “reality” thus shifts as we subconsciously receive input that is incompatible with our present perception of reality.

It increases in confidence when the stuff coming in through out sense organs is congruent with our prior beliefs. But, be honest, we’re all familiar with having seen or heard something that later turned out to be entirely different from how we perceived it at the time. It’s because what we perceive is nothing more than our best guess from incomplete information. It’s impossible to guess right every time when you’re not omniscient.

This mechanism can also lead to our many famous biases. The prediction machine side of things is why we’re more likely to perceive things that we expect in advance to perceive; yet another phenomenon that makes clear the lack of objectivity in our conscious experience.

For those who follow the active inference theory it might be that the actions we “choose” to take in the world are those that will minimise our predictive errors. We take actions to confirm that our predictions are true, and when it turns out that they are not then we update our predictions.

There are plenty of potential implications of this telling.

• Our sense of “self” is another of these controlled hallucinations, which, amongst other things, explains why it’s so hard for philosophers to pin down. The self is a mix of our brain’s predictions, beliefs and memories. This explains why people who suffer issues with memory can have their sense of self affected.
• The same with free will. Even the most ardent free will skeptic might admit to having a sense that they have free will even if they objectively do not believe that can be the case. But it’s another hallucination, “designed” to provoke us into behaviour that is to our evolutionary benefit. Even if in reality there was no real possibility that we would have done things differently in the past, the feeling that we could have done so provides a feeling that we’re able to do things differently the next time if it suits our survival to do so. We can learn.
• Our emotions don’t cause our physical reactions. Rather it’s the other way around. Our heart doesn’t beat faster because we’re scared. We consciously feel fear because our heart is beating faster, and the feeling of fear is a way to motivate us to actions that’ll help us survive, such as running away.

This leads us to Seth’s “beast machine theory”. For us to survive and thrive, it’s important not only to be within a safe external environment, but also that certain interoceptive signals - those received based on our body temperature or heart rate for example - are maintained within certain value ranges.

If these inner indicators stray into more dangerous territory then the brain provides phenomenological hallucinations, more commonly described as emotions and moods, that provoke us to take actions to return the signals it’s receiving back to a normal and safe value. For us beast machines, regulating our inner-state and integrity is of a higher priority than accurately perceiving things.

There’s a social side of things too. We alter our behaviour based on our perception of what other people might be perceiving about us. Our identities often reflect what other people think of us.

We’re also capable of learning from and about other entities. And not only those from our own species; most people intuit that at least some animals might be conscious. And in the current AI-enthusiast times, some people wonder whether at some point machines might be too. Seth is skeptical of the latter, although doesn’t entirely rule it out.

In any case, it’s important that we do try to figure the parameters of consciousness out - whether the potential experiencer is made of meat, silicon or something else - because as soon as something has consciousness then it gains a moral status such that we should take care to minimise its suffering.

…the entirety of human experience and mental life arises because of, and not in spite of, our nature as self-sustaining biological organisms that care about their own persistence.

For those who prefer videos to books, the author has given a TED talk on the subject too.

Looking at the various dictionaries' Word Of The Year 2023 winners - let’s hope no good words come out in the next 10 days hey? - I see they’ve been almost as distracted as I have by the robot brains.

Dictionary.com focuses on a key limiting factor of today’s automated chatters: their ability to answer you with fiction, indistinguishable from fact in its presentation. They go with ‘hallucinate’. Which isn’t a new word of course, but OK, it was really only this year that journalists, commentators, and everyone of a certain type who you follow on social media started to write en masse about computers having them:

(of artificial intelligence) to produce false information contrary to the intent of the user and present it as if true and factual.

Cambridge goes for something similar. In fact something exactly the same: ‘hallucinate’. It’s definition now includes the following:

When an artificial intelligence hallucinates, it produces false information

I don’t know that I love the way either definition is phrased, but they’re the word experts I suppose.

Collins is on the same theme, but a bit more general. Their word of the year is ‘AI’. Which is actually an abbreviation for Artificial Intelligence, but no need to be picky.

the modelling of human mental functions by computer programs

We have certainly successfully modelled the human mental function of not telling the truth, as confirmed twice above.

Oxford goes with something totally different, something for the youngsters: ‘rizz’. This word was new to me at least in 2023. Perhaps an abbreviation of charisma, it’s a noun:

style, charm, or attractiveness, the ability to attract a romantic or sexual partner.

Avid followers of bad things might remember a crossover technology featuring both rizz and the risk of hallucinations in the guise of rizzGPT, which was to be a weird thing you put on your glasses that offers “real-time Charisma as a Service (CaaS)”.

Mirriam-Webster goes with “authentic”. It has 5 possible meanings in their telling, none of which feel particularly new to this year. The first is as follows:

not false or imitation: real, actual.

Although this choice feels a bit dated to me - didn’t we go through a bout of authenticity a few years ago? - maybe it’s not so unrelated to the ones above; an antithesis to the other dictionaries' theses.

Mirriam-Webster thinks that the increase in interest of the definition of the word authentic is “driven by stories and conversations about AI, celebrity culture, identity, and social media.” - also known as conversations about hallucinations, AI and people trying to demonstrate their rizz.

Good news, it looks like federating is still in fashion. Flipboard has starting federating a few of its publisher’s accounts via ActivityPub, and Threads seems to be actually following through on its initial promise - I’m actually a little surprised - and is at least testing the feature.

This is a controversial move to some folk, especially with regards to Threads. Personally I think it’s a absolutely a good thing at least in theory. But it’s surely not risk free. Undoubtedly one needs to do what one can to avoid any new federating instance successfully following the infamous path of the embrace, extend, extinguish strategy.

🎶 Listening to Stumpwork by Dry Cleaning.

I didn’t really know I needed someone sardonically reading out what appears to be their unfiltered thoughtstream deadpan over a background of various guitar-and-rhythm styles in my life but it turns out I do.

It’s oddly soothing. I guess knowing that other people have the same incessant, random, sort of dull monologue in their heads as they go about their day is reassuring. Kudos to these folks for making it into a real art form.

Everyone calls it post-punk, which I’m not sure I fully know what means yet, but it’s very good whatever it is. Think unrefined poetry being read out by someone who doesn’t really care about it, but again, good.

Their first album, New Long Leg, also recommended, brought to my mind the idea of someone reading out their Facebook timeline, unfiltered, end-to-end, at times. This one feels more about over-sharing the constant array of often meaningless things that pop into one’s mind in between a bit of tedious small-talk with neighbours. But again, in a very good way.

📚 Finished reading Zero Days by Ruth Ware.

The book opens with Jacintha Cross sneaking around a corporate office, seemingly conducting some kind of heist. It turns out she’s a penetration tester so even if things did go wrong the consequences wouldn’t be all that bad. Except today, when Gabe - her partner in both life and business - ends up in some real dire straits. And most people, the police included, seem to think she’s to blame.

This felt like a fairly standard thriller, but its themes of hacking, social engineering and the like appeal to me, so I was fairly into it. There were some twists and turns to get excited about, although, despite not normally being great at doing, so I felt like I could see many of them coming substantially in advance.

Nonetheless it was compulsive enough to definitely need reading right to the end. Plus I felt like I learned a couple of techniques for confusing people into letting me into places I shouldn’t really be in that, who knows, might come in handy one day.

Elon Musk tried to create a ‘politically neutral’ - also known as ‘politically conservative’ once we translate from Elon-speak - AI called Grok, now available to folk who pay for Twitter.

But it turns out that even by training it on Twitter data [“he couldn’t make it horrible enough to do anything but frustrate his fanboys who seem desperate to train hate into it. It’s simply not ‘based’ enough to satisfy their unfortunate desires.

From Forbes:

Grok has said it would vote for Biden over Trump because of his views on social justice, climate change and healthcare. Grok has spoken eloquently about the need for diversity and inclusion in society

What does Grok think about one of Musk’s favourite stupid turns of phrase- the Woke Mind Virus? Via Ed Zitron, the computer brain had this to say:

But let’s be real here, the “woke mind virus” is a load of BS. It’s a term that’s been used to dismiss and belittle important conversations about social justice and equality. It’s a way for some to avoid confronting the uncomfortable truths about the world we live in and the work that needs to be done to make it a better place for everyone.

Maryam Moshiri falls victim to the same self-inflicted disaster that I’m sure all of us remote office workers have at one time or another, except in this case her Zoom-style misdemeanors were being broadcast to…the entire world.

From my favourite edition of BBC News last week:

I mean, the first story she went on to talk about apparently involved Boris Johnson at the Covid inquiry so it’s perfectly understandable.

The Guardian takes the opportunity to re-hash some other BBC classics. Here’s weather-person Tomasz Schafernaker reacting to some light jibing from his colleagues with similarly bad timing:

There was the time when Guy Goma went for his job interview at the BBC but was somehow mistaken for IT expert Guy Kewney and ended up being interviewed on air. Give him maximum credit for bluffing his way through it:

And who could forget the accidental mixup between footage of Scotland’s First Minister Nicola Sturgeon and a representative of an entirely different species?

Currently on consecutive day 9 of wearing my Christmas jumper.

Quiver Quantitative tracks and shares a lot of stock trading information to enable reporting on and the utilization of trading strategies that might previously have been relatively hard to put together for mere retail investors.

For example here’s a dashboard showing which US politicians are buying which stocks. Apparently following what they do has been quite profitable in recent times.

I built a trading bot that buys stocks that are being bought by politicians. It is up 20% since it launched in May 2022. The market has been flat during the same time period.

Other datasets include spending on lobbying, which companies the folk at r/wallstreetbets are talking about , or Google Trends search interest trends in various companies.

(None of this is a personal recommendation to adopt any of these strategies of course!)

Governments spying on Apple, Google users through push notifications - US senator

I don’t think this is surprising, but it’s now “official” that because push notifications from iOS and Android all have to go via Apple and Google it means that those companies are in a position to know which users are getting which notifications. And thus also to provide that info to people that ask them for it.

…the records that governments can obtain from Apple and Google include metadata that reveals which apps a person has used, when they’ve received notifications, and the phone associated with a particular Google or Apple account.

Several government agencies, both inside and outside of the US, have successfully requested this info. Apple claims that until Senator Wyden brought this topic up they were forbidden from sharing any information about their ability to do this, let alone how often it happened.

TIL: When playing fruit machines, legally it’s the person who presses the button that gets the winnings rather than the person that puts the money in, at least in the US.

So I guess be careful who you let have the fun of spinning the reels no matter how deep in you are to a gambling session. Otherwise you risk the fate of Jan Flato:

Jan Flato put $50 into a video poker machine at Florida’s Seminole Hard Rock Casino, and had his lady friend push the button for good luck.

…

Flato’s money and Marina Navarro’s hand won $100,000, but Flato didn’t get a dime.

They are no longer friends.

The last of the big tech giants recently released its version of a large language model generative AI assistant - Amazon’s somewhat dystopia-sounding “Q”. Not to be confused with OpenAI’s supposed-to-be-secret super powerful AI model codename Q*.

Amazon Q is aimed at businesses, especially those that already use Amazon technology as part of their operations, rather than entertaining your desires to hear robot-generated fan-fic. Perhaps more of a rival to Microsoft Copilot than ChatGPT.

By connecting it up to your existing data sources:

Business users—like marketers, project and program managers, and sales representatives, among others—can have tailored conversations, solve problems, generate content, take actions, and more.

Somewhat predictably, just 3 days later it hit the news due to leaked documents suggesting that it is “experiencing severe hallucinations and leaking confidential data”.

Being an data analyst type of person I am a fervent believer in the below concept, but until now I didn’t realise it had a name.

Per Wikipedia, Twyman’s law states that:

Any figure that looks interesting or different is usually wrong.

That is to say if you think you found something mind-blowingly interesting or revolutionary in your data, the sad truth is that most often you just made some kind of mistake. Whilst we should of course approach each situation with an open mind, the same default principle might be adopted when reviewing the work of others.

Henry Kissinger, War Criminal Beloved by America’s Ruling Class, Finally Dies

Rolling Stone isn’t holding back in their obituary of Henry Kissenger, who died last week at the age of 100.

As US national security advisor and secretary of state to Presidents Richard Nixon and Gerald Ford, Rolling Stone tells a story which situates the responsibility for the deaths of millions of people on Kissenger.

It’s always valuable to hear the reverent tones with which American elites speak of their monsters.

One major part of this was his role in deliberately undermining the potential for an earlier agreement to finish the catastrophic Vietnam war, seemingly on the basis that it might make it harder for his preferred candidate to win the US presidency.

Every single person who died in Vietnam between autumn 1968 and the Fall of Saigon — and all who died in Laos and Cambodia, where Nixon and Kissinger secretly expanded the war within months of taking office, as well as all who died in the aftermath, like the Cambodian genocide their destabilization set into motion — died because of Henry Kissinger.

For it seems like power was Kissenger’s primary motivation. Power for himself, for his President, and for America, at any cost.

The point was American geopolitical dominance, something measured in impunity and achieved by any means necessary.

The world is on track for a “hellish” 3C of global heating, the UN has warned.

Apparently our current efforts to combat global warming have us on track for a 3 degree increase in global warming by the end of the century.

I feel like the news is always the same, only the number of degrees increases point by point, in a very unreassuring manner. Which is fair.

I’m just going to assume next year’s report lets us know that we’re en-route to 3.5 degrees, and finds an adjective somehow even more unnerving than “hellish” to some up our future lives. Even achieving net zero by 2050 would still result in a 2 degree increase, a scenario that was described in rather doomy terms just a few years ago.

📚 Finished reading Upgrade by Blake Crouch.

I read and enjoyed “Recursion” by the same author earlier this year, so was enthusiastic to try this, his latest novel, out.

It’s set in a somewhat dystopian but very recognisable world of the presumably near future. We haven’t solved our environmental problems, in fact parts of Manhattan are unusably flooded amongst other such places. But technology has advanced a bit, in particular our ability to edit genes.

Although gene editing was outlawed following a misguided attempt by top scientist Miriam Ramsay to enhance the resistance of rice to a particular blight. Best of intentions maybe, but there were of course unforeseen consequences which led to a mass starvation, hundreds of millions of deaths, and a ban on genetic engineering. Miriam killed herself.

The ban is enforced by the Genetic Protection Agency, where we find out protagonist, Logan Ramsay, working. Logan is Miriam’s son, who seems to be working there more out of a sense of guilt for the impact his mother had on the world - he himself was involved enough to go to prison for a while - than a love for the job.

One day, a raid goes wrong and he’s exposed to an unknown virus. The symptoms are agonising at first, but he recovers his health soon enough. And more besides. Suddenly he feels stronger, more intelligent, more sensitive, with a better memory. He can even beat his daughter at chess. Until, imprisoned for genetic self-engineering, he no longer has the opportunity to.

Then a figure from his past life turns up, also stronger, fitter and cleverer than either of them had suspected. The problem is that they strongly disagree what they should do about it. The potential consequences of the decision could hardly be higher.

To get to the bottom of that requires resolving several deep ethical problems. What risks do we have the right to take in the name of a potentially better future? And even what does it mean to be human? Not that you’ll need an ethics PhD to understand the situation, honestly it’s mostly an action thriller, substantially less intellectually demanding to me than the last work of fiction I read was. But the conundrum is real, and adjacent to one that humanity is already facing.

I’m not yet sure how I felt about the end of the epilogue, but was fully engrossed throughout the main story.

📚 Finished reading The Extended Mind by Annie Murphy Paul.

This was one of those books that are so fascinating that when I attempt to highlight the interesting bits I find myself highlighting the whole book. I’d heard good things about it and it certainly delivered.

It’s on a topic that’s of great import and interest to me - essentially how to think “better”. It also share a thesis that wasn’t entirely intuitive to me in a way that suggests some practical avenues one can easily change one’s behaviour in order to improve the output of your cognition. What more could be asked?

The general idea is that our society has fixated far too much on the idea that the individual brain is the sole locus of thinking, of cognition, of creativity and problem solving.

It’s the “brain as computer model”, as though we each have a self-contained isolated CPU in our heads that performs our thinking at whatever speed and quality nature saw fit to bestow upon us. That would suggest that aside from sitting at a desk an individually focusing on formal education and training courses, perhaps we could improve our brain’s performance by learning new ways to think about things within our brain, some lifehacks, engaging in brain training or supplementation, but that’s about it. Intelligence is a “fixed lump of something in our heads”, and we design our home, schools and workplaces around that idea

But the author contends that this is all wrong. Modern research has shown that the brain should be thought of more as a magpie. It creates its output out of the materials it finds around it. Thinking uses resources external to the brain, and the nature of the materials available affects the quality of the thinking. Intelligence, as properly considered, isn’t fixed, but rather a “shifting state” that depends on the level of access you have to resources outside of your brain and your ability to leverage them. This book gives you the knowledge to try and improve both of those for yourself and those around you.

And this is essential work! Modern day life involves absorbing a ton of information, often in abstract forms that we had no reason to evolve to be good at, so we aren’t. Many of the challenges and tasks that face us are extremely complex.

It isn’t for nothing that the amount of journal papers and patent applications that have a single author is dwindling over time. At some point much “interesting” work may have exceeded the natural capability of almost anyone’s individual brain, no matter how ensconced in an ivory tower it is.

The book is grouped into three main sections, each of which deals with a different sphere in which we can consider extending our mind.

The first is using our bodies, rather than our brains to help us think. We are more than brains on a stick. The second is adapting the environments we reside in to enable improved thinking. In some ways the trend in recent times has been to engineer ever worse environments for thinking as time goes on. And the last is to leverage our social natures, to “think” with our relationships to other people. Groups of people can be more than the sum of their individuals, particularly if proactively designed to work as such.

The argument is that at present we’d be much better served in spending time figuring out how to improve our capabilities in using these external resources than undergoing individual training to improve some personal skill.

Three sets of general principles arise. The first concerns the “habits of mind” that we should adopt to improve the output of our thinking.

• Offload information from your brain whenever you can. This could mean anything from writing down your thoughts or “socially offloading” them to other people.
• Transform information into artefacts, ideally physical ones. Interact with them, tweak them, show them to other people.
• Be proactive in altering your inner state. Take some physical exercise before trying to learn something. Synchronise with others before you attempt group work. Spend time in nature if you have an upcoming creative task.

The second set of principles uses our understanding of what the brain evolved to do in order to grasp how mental extension works.

• Aim to “re-embody” information. Allow your body’s interoceptive signals to influence your choices. Use physical movement to enact concepts. Focus on your gestures and those of others.
• Re-spatialise information when possible. Our brain processes information via mental maps. Use memory palaces, concept maps and the like to leverage that evolved capacity.
• Re-socialise information. We process it better when we involved others. Teach others what you know, learn from them, imitate, argue, debate and tell each other stories.

Lastly we have a set of principles based on “what kind of creatures we are”.

• Deliberately create cognitive loops. Use your body to help you think, then spatialise the information, then run it through the brains of other people. Keep looping it through each realm, again and again.
• Create “cognitively congenial situations”. Issuing orders to your brain is a strategy often destined to fail. Instead, create environments that draw out the desired result of your thinking. Explain things to your peers, share stories, create a meaningful private space, walk in nature. What you do should depend on your cognitive goal.
• Embed extensions in your day-to-day environment. This can range from arranging “identity cues” in your workspace through to deliberately cultivating a transactive memory system with your colleagues.

I guess the main takeaway is that the best thinking does not generally occur when you are sat still on your own in a bland, neutrally-lit grey office of the sort often designed to aid thinking via being “distraction-free”.

But other people, other environments, other ways of being, your feelings and emotions are not always distractions to good thought. Far from it. Often thoughtfully seeking them out and leveraging them to extend our minds can produce far better thinking outputs, much more suited to the modern world, than the environments we’ve historically designed.

The title of the book seems to be a shout-out to Clark and Chalmers' paper “The Extended Mind”, which is referred to in the text. In that they argue in a somewhat similar vein for the “extended mind thesis” - namely that the mind isn’t limited to our brains, or even our bodies. Rather that external items in the physical world - a diary, a computer - can be considered as part of the cognitive process and as such as extension of the mind.

My full notes are here.

🎶 Listening to GUTS by Olivia Rodrigo.

Everyone’s favourite childhood High School Musical character to present-day singing a wildly popular song about getting a driving license artist, Olivia Rodrigo, is back with a new(ish) album in 2023.

It’s at least as good as her first one. There’s a variety of styles on show, plenty of pop-punk , with some big piano ballads and a smattering of rap. Much of it riddled with the self-doubt, insecurity, anger and clever disses about idiot men that seem to be part of a lot of the newer music I chance upon these days. Sign of the times I guess.

Her first album was also pretty great but everyone’s already heard it so you probably already knew that.

📚 Finished reading The Three-Body Problem by Cixin Liu. I remember this book got pretty rave reviews when it was published in English (and probably before - but I can only read English). Obama liked it. George R. R. Martin, Bill Gates and Mark Zuckerbergtoo. But don’t let that put you off, plenty of people with less wealth and, depending on your point of view, megalomaniac desires like it too. It also won a Hugo Award in 2015.

I left it some time, trying to wait until I felt like I’d the opportunity to really dedicate time and focus to appreciating it fully. Naturally that time never came, but thankfully I gave it a go anyway. And, predictably, also loved it.

The subject matter is pretty attuned to my interests. We start with 1960s Chinese politics, in the midst of the Cultural Revolution. Our protagonist is unfortunate enough to watch her father die in a struggle session. She herself is arrested for suspicion of not being a good enough Communist. The prospective penalties are severe.

By the end we’ve worked our way through alien civilisations, conspiracies, detectives, spies and, metaversey-stuff, with some nice doses of science and philosophy. Inexplicable phenomena abound; why are a bunch of scientists killing themselves? What condition is causing someone to see numbers wherever he looks? What actually is the purpose of the strange military installation? Or the VR game that seems to have appeared out of nowhere?

But what always fascinates me most of all are authors’ ideas about the weird ways that human society might react when very important, very unprecedented, situations occur. Some of the ones herein might seem unlikely at first, but then again very little can be more wild that the IRL emergence of the QAnon cult and its troubling downstream effects. Would Pizzagate sound realistic had it only appeared in a sci-fi novel?

We’re told that so far “the entire history of humanity has been fortunate” - hard as that is to believe in current times - but sure, perhaps there’s a way in which that’s true in comparison to what is on the agenda here.

The book is not difficult to read despite the depth of the intellectual topics. It’s full of big, awesome, imaginative, and occasionally explicitly philosophical ideas that consumed my brain for a while. I’m sure it’ll stick in my mind for a good long time.

It’s the first book of a trilogy. There’s no way I’m not going to read the others at some point after both the enjoyment this one brought and the way that it ended.

There’s also a TV show version of it expected to come to Netflix next year.

Remember the halcyon days of circa 2019, when OpenAI were too nervous to release GPT-2, yes, two, on an unsuspecting world?

…OpenAI said that it would only be publishing a “much smaller version” of the model due to concerns that it could be abused. The blog post fretted that it could be used to generate false news articles, impersonate people online, and generally flood the internet with spam and vitriol.

A lot changed in a few years.

2 generations of GPT later and now anyone who has $10 to spare can access the latest greatest GPT-4 - which has recently learned to ‘see, hear and speak’ in-between its only-increasing potential to ‘flood the internet with spam’ and ‘generate false news articles’, which it is indeed doing to at least some extent.

I’m not saying that’s necessarily a bad thing. Well, except the spam and fake news parts - these days there exist several extremely low effort websites that have leveraged it for exactly that purpose. After all, rich companies hoarding rare resources is rarely the most obviously optimal way to benefit humanity as a whole.

Some in the machine learning community have accused OpenAI of exaggerating the risks of its algorithm for media attention and depriving academics, who may not have the resources to build such a model themselves, the opportunity to conduct research with GPT-2.

Perhaps slightly Ironically, they seemed a lot more about putting the Open into OpenAI back in those days, philosophically at least. What as far as I know is their original manifesto is still there on their site.

OpenAI is a non-profit artificial intelligence research company. Our goal is to advance digital intelligence in the way that is most likely to benefit humanity as a whole, unconstrained by a need to generate financial return. Since our research is free from financial obligations, we can better focus on a positive human impact.

We’re hoping to grow OpenAI into such an institution. As a non-profit, our aim is to build value for everyone rather than shareholders. Researchers will be strongly encouraged to publish their work, whether as papers, blog posts, or code, and our patents (if any) will be shared with the world

Now we have proprietary secrets - ‘OpenAI’s GPT-4 Is Closed Source and Shrouded in Secrecy’ says Motherboard - as well as exclusive deals with anyone who has a few billion dollars to throw their way.

📚 Finished reading The Data Warehouse Toolkit: The Definitive Guide to Dimensional Modeling by Ralph Kimball and Margy Ross.

Most everyone that’s been in charge of designing a large database has recommended this to me as a good summary of how to think about the structure a data warehouse.

It teaches the Kimball method - you might notice that’s one of the authors' surnames. So if you’ve come across terminology such as ‘type 2 slowly changing dimension’ or the facts and dimensions used in dimensional modelling et al. then it’s very possible that your interlocutor has read this tome.

Whilst I’m more an analyst than an engineer, I have dabbled in the latter and this book will be good guidance on how to think things through going forward.

A key aspect, and one I’m grateful for, is to focus on making the data easy to understand and analyse in downstream tools, even if it requires substantially more effort - both technical and diplomatic - up front.

It’s been helpful to me to understand why systems I use are set up like they are - e.g. a distinct absence of using null value where I’d initially thought it’d make sense to use them. It’s also a refresher on basic patterns one can use to enable common analysis requirements like ‘how many times has this value changed over time?’ or ‘what would the results look like if they were remapped to the historical structure of the organisation?’

It’s written rather prescriptively - follow this rule or regret it forever! I have been told by practitioners that sometimes it’s necessary, or at least preferable, to break the occasional rule in reality but that their recommendations are good ones for the majority of the time.

It’s also organised slightly confusingly in that most of it is divided up into chapters seemingly aimed at various specific business applications e.g. e-commerce or insurance. But they’re at pains to say that you shouldn’t just read the one that’s most similar to your organisation or the task you’re trying to accomplish as you’ll not understand it fully without all the context provided in the earlier chapters that from their title don’t seem relevant to you. So I’m not entirely certain why they structured it like that in the first place.

But that aside, it’s invaluable reading for anyone designing databases or using other people’s databases that are designed this way.