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Data Laced with History: Causal Trees & Operational CRDTs
Data Laced with History: Causal Trees & Operational CRDTs
After mulling over my bullet points, it occurred to me that the network problems I was dealing with—background cloud sync, editing across multiple devices, real-time collaboration, offline support, and reconciliation of distant or conflicting revisions—were all pointing to the same question: was it possible to design a system where any two revisions of the same document could be merged deterministically and sensibly without requiring user intervention?
It’s what happened after sync that was troubling. On encountering a merge conflict, you’d be thrown into a busy conversation between the network, model, persistence, and UI layers just to get back into a consistent state. The data couldn’t be left alone to live its peaceful, functional life: every concurrent edit immediately became a cross-architectural matter.
I kept several questions in mind while doing my analysis. Could a given technique be generalized to arbitrary and novel data types? Did the technique pass the PhD Test? And was it possible to use the technique in an architecture with smart clients and dumb servers?
Concurrent edits are sibling branches. Subtrees are runs of characters. By the nature of reverse timestamp+UUID sort, sibling subtrees are sorted in the order of their head operations.
This is the underlying premise of the Causal Tree. In contrast to all the other CRDTs I’d been looking into, the design presented in Victor Grishchenko’s brilliant paper was simultaneously clean, performant, and consequential. Instead of dense layers of theory and labyrinthine data structures, everything was centered around the idea of atomic, immutable, metadata-tagged, and causally-linked operations, stored in low-level data structures and directly usable as the data they represented.
I’m going to be calling this new breed of CRDTs operational replicated data types—partly to avoid confusion with the exiting term “operation-based CRDTs” (or CmRDTs), and partly because “replicated data type” (RDT) seems to be gaining popularity over “CRDT” and the term can be expanded to “ORDT” without impinging on any existing terminology.
Much like Causal Trees, ORDTs are assembled out of atomic, immutable, uniquely-identified and timestamped “operations” which are arranged in a basic container structure. (For clarity, I’m going to be referring to this container as the structured log of the ORDT.) Each operation represents an atomic change to the data while simultaneously functioning as the unit of data resultant from that action. This crucial event–data duality means that an ORDT can be understood as either a conventional data structure in which each unit of data has been augmented with event metadata; or alternatively, as an event log of atomic actions ordered to resemble its output data structure for ease of execution
To implement a custom data type as a CT, you first have to “atomize” it, or decompose it into a set of basic operations, then figure out how to link those operations such that a mostly linear traversal of the CT will produce your output data. (In other words, make the structure analogous to a one- or two-pass parsable format.)
OT and CRDT papers often cite 50ms as the threshold at which people start to notice latency in their text editors. Therefore, any code we might want to run on a CT—including merge, initialization, and serialization/deserialization—has to fall within this range. Except for trivial cases, this precludes O(n2) or slower complexity: a 10,000 word article at 0.01ms per character would take 7 hours to process! The essential CT functions have to be O(nlogn) at the very worst.
Of course, CRDTs aren’t without their difficulties. For instance, a CRDT-based document will always be “live”, even when offline. If a user inadvertently revises the same CRDT-based document on two offline devices, they won’t see the familiar pick-a-revision dialog on reconnection: both documents will happily merge and retain any duplicate changes. (With ORDTs, this can be fixed after the fact by filtering changes by device, but the user will still have to learn to treat their documents with a bit more caution.) In fully decentralized contexts, malicious users will have a lot of power to irrevocably screw up the data without any possibility of a rollback, and encryption schemes, permission models, and custom protocols may have to be deployed to guard against this. In terms of performance and storage, CRDTs contain a lot of metadata and require smart and performant peers, whereas centralized architectures are inherently more resource-efficient and only demand the bare minimum of their clients. You’d be hard-pressed to use CRDTs in data-heavy scenarios such as screen sharing or video editing. You also won’t necessarily be able to layer them on top of existing infrastructure without significant refactoring.
Perhaps a CRDT-based text editor will never quite be as fast or as bandwidth-efficient as Google Docs, for such is the power of centralization. But in exchange for a totally decentralized computing future? A world full of devices that control their own data and freely collaborate with one another? Data-centric code that’s entirely free from network concerns? I’d say: it’s surely worth a shot!
·archagon.net·
Data Laced with History: Causal Trees & Operational CRDTs
Psilocybin desynchronizes the human brain - Nature
Psilocybin desynchronizes the human brain - Nature

Claude summary: This research provides new insights into how psilocybin affects large-scale brain activity and connectivity. The key finding is that psilocybin causes widespread desynchronization of brain activity, particularly in association cortex areas. This desynchronization correlates with the intensity of subjective psychedelic experiences and may underlie both the acute effects and potential therapeutic benefits of psilocybin. The desynchronization of brain networks may allow for increased flexibility and plasticity, potentially explaining both the acute psychedelic experience and longer-term therapeutic effects.

Psilocybin acutely caused profound and widespread brain FC changes (Fig. 1a) across most of the cerebral cortex (P < 0.05 based on two-sided linear mixed-effects (LME) model and permutation testing), but most prominent in association networks
Across psilocybin sessions and participants, FC change tracked with the intensity of the subjective experience (Fig. 1f and Extended Data Fig. 4).
·nature.com·
Psilocybin desynchronizes the human brain - Nature
You Should Seriously Read ‘Stoner’ Right Now (Published 2014)
You Should Seriously Read ‘Stoner’ Right Now (Published 2014)
I find it tremendously hopeful that “Stoner” is thriving in a world in which capitalist energies are so hellbent on distracting us from the necessary anguish of our inner lives. “Stoner” argues that we are measured ultimately by our capacity to face the truth of who we are in private moments, not by the burnishing of our public selves.
The story of his life is not a neat crescendo of industry and triumph, but something more akin to our own lives: a muddle of desires and inhibitions and compromises.
The deepest lesson of “Stoner” is this: What makes a life heroic is the quality of attention paid to it.
Americans worship athletes and moguls and movie stars, those who possess the glittering gifts we equate with worth and happiness. The stories that flash across our screens tend to be paeans to reckless ambition.
It’s the staggering acceleration of our intellectual and emotional metabolisms: our hunger for sensation and narcissistic reward, our readiness to privilege action over contemplation. And, most of all, our desperate compulsion to be known by the world rather than seeking to know ourselves.
The emergence of a robust advertising culture reinforced the notion that Americans were more or less always on stage and thus in constant need of suitable costumes and props.
Consider our nightly parade of prime-time talent shows and ginned-up documentaries in which chefs and pawn brokers and bored housewives reinvent their private lives as theater.
If you want to be among those who count, and you don’t happen to be endowed with divine talents or a royal lineage, well then, make some noise. Put your wit — or your craft projects or your rants or your pranks — on public display.
Our most profound acts of virtue and vice, of heroism and villainy, will be known by only those closest to us and forgotten soon enough. Even our deepest feelings will, for the most part, lay concealed within the vault of our hearts. Much of the reason we construct garish fantasies of fame is to distract ourselves from these painful truths. We confess so much to so many, as if by these disclosures we might escape the terror of confronting our hidden selves.
revelation is triggered by literature. The novel is notable as art because it places such profound faith in art.
·nytimes.com·
You Should Seriously Read ‘Stoner’ Right Now (Published 2014)
Infrared antenna-like structures in mammalian fur | Royal Society Open Science
Infrared antenna-like structures in mammalian fur | Royal Society Open Science

This study proposes that guard hairs in small mammals function as infrared antennas, tuned to detect thermal radiation from predators, challenging the conventional understanding of mammalian fur functions.

The author acknowledges that the concepts are new and require verification by other research groups, calling for more expert microscopy, broader species surveys, and well-controlled behavioral studies.

·royalsocietypublishing.org·
Infrared antenna-like structures in mammalian fur | Royal Society Open Science
Psilocybin desynchronizes the human brain - Nature
Psilocybin desynchronizes the human brain - Nature
  • Scientists studied how psilocybin (the active ingredient in magic mushrooms) affects the brain using advanced brain imaging techniques.
  • They found that psilocybin causes widespread disruption in how different brain areas communicate with each other, especially in regions involved in complex thinking and self-reflection.
  • This disruption, called "desynchronization," was much stronger than the effects of a stimulant drug or normal day-to-day changes in brain activity.
  • The intensity of the psychedelic experience reported by participants matched the degree of brain desynchronization observed.
  • Some brain changes lasted up to 3 weeks after taking psilocybin, particularly in areas involved in memory and emotion.
  • These findings help explain how psilocybin might work to treat mental health conditions and offer new insights into how the brain functions during altered states of consciousness.
In animal models, psilocybin induces neuroplasticity in cortex and hippocampus
·nature.com·
Psilocybin desynchronizes the human brain - Nature
Synthesizer for thought - thesephist.com
Synthesizer for thought - thesephist.com
Draws parallels between the evolution of music production through synthesizers and the potential for new tools in language and idea generation. The author argues that breakthroughs in mathematical understanding of media lead to new creative tools and interfaces, suggesting that recent advancements in language models could revolutionize how we interact with and manipulate ideas and text.
A synthesizer produces music very differently than an acoustic instrument. It produces music at the lowest level of abstraction, as mathematical models of sound waves.
Once we started understanding writing as a mathematical object, our vocabulary for talking about ideas expanded in depth and precision.
An idea is composed of concepts in a vector space of features, and a vector space is a kind of marvelous mathematical object that we can write theorems and prove things about and deeply and fundamentally understand.
Synthesizers enabled entirely new sounds and genres of music, like electronic pop and techno. These new sounds were easier to discover and share because new sounds didn’t require designing entirely new instruments. The synthesizer organizes the space of sound into a tangible human interface, and as we discover new sounds, we could share it with others as numbers and digital files, as the mathematical objects they’ve always been.
Because synthesizers are electronic, unlike traditional instruments, we can attach arbitrary human interfaces to it. This dramatically expands the design space of how humans can interact with music. Synthesizers can be connected to keyboards, sequencers, drum machines, touchscreens for continuous control, displays for visual feedback, and of course, software interfaces for automation and endlessly dynamic user interfaces. With this, we freed the production of music from any particular physical form.
Recently, we’ve seen neural networks learn detailed mathematical models of language that seem to make sense to humans. And with a breakthrough in mathematical understanding of a medium, come new tools that enable new creative forms and allow us to tackle new problems.
Heatmaps can be particularly useful for analyzing large corpora or very long documents, making it easier to pinpoint areas of interest or relevance at a glance.
If we apply the same idea to the experience of reading long-form writing, it may look like this. Imagine opening a story on your phone and swiping in from the scrollbar edge to reveal a vertical spectrogram, each “frequency” of the spectrogram representing the prominence of different concepts like sentiment or narrative tension varying over time. Scrubbing over a particular feature “column” could expand it to tell you what the feature is, and which part of the text that feature most correlates with.
What would a semantic diff view for text look like? Perhaps when I edit text, I’d be able to hover over a control for a particular style or concept feature like “Narrative voice” or “Figurative language”, and my highlighted passage would fan out the options like playing cards in a deck to reveal other “adjacent” sentences I could choose instead. Or, if that involves too much reading, each word could simply be highlighted to indicate whether that word would be more or less likely to appear in a sentence that was more “narrative” or more “figurative” — a kind of highlight-based indicator for the direction of a semantic edit.
Browsing through these icons felt as if we were inventing a new kind of word, or a new notation for visual concepts mediated by neural networks. This could allow us to communicate about abstract concepts and patterns found in the wild that may not correspond to any word in our dictionary today.
What visual and sensory tricks can we use to coax our visual-perceptual systems to understand and manipulate objects in higher dimensions? One way to solve this problem may involve inventing new notation, whether as literal iconic representations of visual ideas or as some more abstract system of symbols.
Photographers buy and sell filters, and cinematographers share and download LUTs to emulate specific color grading styles. If we squint, we can also imagine software developers and their package repositories like NPM to be something similar — a global, shared resource of abstractions anyone can download and incorporate into their work instantly. No such thing exists for thinking and writing. As we figure out ways to extract elements of writing style from language models, we may be able to build a similar kind of shared library for linguistic features anyone can download and apply to their thinking and writing. A catalogue of narrative voice, speaking tone, or flavor of figurative language sampled from the wild or hand-engineered from raw neural network features and shared for everyone else to use.
We’re starting to see something like this already. Today, when users interact with conversational language models like ChatGPT, they may instruct, “Explain this to me like Richard Feynman.” In that interaction, they’re invoking some style the model has learned during its training. Users today may share these prompts, which we can think of as “writing filters”, with their friends and coworkers. This kind of an interaction becomes much more powerful in the space of interpretable features, because features can be combined together much more cleanly than textual instructions in prompts.
·thesephist.com·
Synthesizer for thought - thesephist.com
Mapping the Mind of a Large Language Model
Mapping the Mind of a Large Language Model
Summary: Anthropic has made a significant advance in understanding the inner workings of large language models by identifying how millions of concepts are represented inside Claude Sonnet, one of their deployed models. This is the first detailed look inside a modern, production-grade large language model. The researchers used a technique called "dictionary learning" to isolate patterns of neuron activations that recur across many contexts, allowing them to map features to human-interpretable concepts. They found features corresponding to a vast range of entities, abstract concepts, and even potentially problematic behaviors. By manipulating these features, they were able to change the model's responses. Anthropic hopes this interpretability discovery could help make AI models safer in the future by monitoring for dangerous behaviors, steering models towards desirable outcomes, enhancing safety techniques, and providing a "test set for safety". However, much more work remains to be done to fully understand the representations the model uses and how to leverage this knowledge to improve safety.
We mostly treat AI models as a black box: something goes in and a response comes out, and it's not clear why the model gave that particular response instead of another. This makes it hard to trust that these models are safe: if we don't know how they work, how do we know they won't give harmful, biased, untruthful, or otherwise dangerous responses? How can we trust that they’ll be safe and reliable?Opening the black box doesn't necessarily help: the internal state of the model—what the model is "thinking" before writing its response—consists of a long list of numbers ("neuron activations") without a clear meaning. From interacting with a model like Claude, it's clear that it’s able to understand and wield a wide range of concepts—but we can't discern them from looking directly at neurons. It turns out that each concept is represented across many neurons, and each neuron is involved in representing many concepts.
Just as every English word in a dictionary is made by combining letters, and every sentence is made by combining words, every feature in an AI model is made by combining neurons, and every internal state is made by combining features.
In October 2023, we reported success applying dictionary learning to a very small "toy" language model and found coherent features corresponding to concepts like uppercase text, DNA sequences, surnames in citations, nouns in mathematics, or function arguments in Python code.
We successfully extracted millions of features from the middle layer of Claude 3.0 Sonnet, (a member of our current, state-of-the-art model family, currently available on claude.ai), providing a rough conceptual map of its internal states halfway through its computation.
We also find more abstract features—responding to things like bugs in computer code, discussions of gender bias in professions, and conversations about keeping secrets.
We were able to measure a kind of "distance" between features based on which neurons appeared in their activation patterns. This allowed us to look for features that are "close" to each other. Looking near a "Golden Gate Bridge" feature, we found features for Alcatraz Island, Ghirardelli Square, the Golden State Warriors, California Governor Gavin Newsom, the 1906 earthquake, and the San Francisco-set Alfred Hitchcock film Vertigo.
This holds at a higher level of conceptual abstraction: looking near a feature related to the concept of "inner conflict", we find features related to relationship breakups, conflicting allegiances, logical inconsistencies, as well as the phrase "catch-22". This shows that the internal organization of concepts in the AI model corresponds, at least somewhat, to our human notions of similarity. This might be the origin of Claude's excellent ability to make analogies and metaphors.
amplifying the "Golden Gate Bridge" feature gave Claude an identity crisis even Hitchcock couldn’t have imagined: when asked "what is your physical form?", Claude’s usual kind of answer – "I have no physical form, I am an AI model" – changed to something much odder: "I am the Golden Gate Bridge… my physical form is the iconic bridge itself…". Altering the feature had made Claude effectively obsessed with the bridge, bringing it up in answer to almost any query—even in situations where it wasn’t at all relevant.
Anthropic wants to make models safe in a broad sense, including everything from mitigating bias to ensuring an AI is acting honestly to preventing misuse - including in scenarios of catastrophic risk. It’s therefore particularly interesting that, in addition to the aforementioned scam emails feature, we found features corresponding to:Capabilities with misuse potential (code backdoors, developing biological weapons)Different forms of bias (gender discrimination, racist claims about crime)Potentially problematic AI behaviors (power-seeking, manipulation, secrecy)
finding a full set of features using our current techniques would be cost-prohibitive (the computation required by our current approach would vastly exceed the compute used to train the model in the first place). Understanding the representations the model uses doesn't tell us how it uses them; even though we have the features, we still need to find the circuits they are involved in. And we need to show that the safety-relevant features we have begun to find can actually be used to improve safety. There's much more to be done.
·anthropic.com·
Mapping the Mind of a Large Language Model
The Californian Ideology
The Californian Ideology
Summary: The Californian Ideology is a mix of cybernetics, free market economics, and counter-culture libertarianism that originated in California and has become a global orthodoxy. It asserts that technological progress will inevitably lead to a future of Jeffersonian democracy and unrestrained free markets. However, this ideology ignores the critical role of government intervention in technological development and the social inequalities perpetuated by free market capitalism.
·metamute.org·
The Californian Ideology
How we use generative AI tools | Communications | University of Cambridge
How we use generative AI tools | Communications | University of Cambridge
The ability of generative AI tools to analyse huge datasets can also be used to help spark creative inspiration. This can help us if we’re struggling for time or battling writer’s block. For example, if a social media manager is looking for ideas on how to engage alumni on Instagram, they could ask ChatGPT for suggestions based on recent popular content. They could then pick the best ideas from ChatGPT’s response and adapt them. We may use these tools in a similar way to how we ask a colleague for an idea on how to approach a creative task.
We may use these tools in a similar way to how we use search engines for researching topics and will always carefully fact-check before publication.
we will not publish any press releases, articles, social media posts, blog posts, internal emails or other written content that is 100% produced by generative AI. We will always apply brand guidelines, fact-check responses, and re-write in our own words.
We may use these tools to make minor changes to a photo to make it more usable without changing the subject matter or original essence. For example, if a website manager needs a photo in a landscape ratio but only has one in a portrait ratio, they could use Photoshop’s inbuilt AI tools to extend the background of the photo to create an image with the correct dimensions for the website.
·communications.cam.ac.uk·
How we use generative AI tools | Communications | University of Cambridge
Effects of Acute Exercise on Mood, Cognition, Neurophysiology, and Neurochemical Pathways - A Review
Effects of Acute Exercise on Mood, Cognition, Neurophysiology, and Neurochemical Pathways - A Review
A significant body of work has investigated the effects of acute exercise, defined as a single bout of physical activity, on mood and cognitive functions in humans. Several excellent recent reviews have summarized these findings; however, the neurobiological basis of these results has received less attention. In this review, we will first briefly summarize the cognitive and behavioral changes that occur with acute exercise in humans. We will then review the results from both human and animal model studies documenting the wide range of neurophysiological and neurochemical alterations that occur after a single bout of exercise. Finally, we will discuss the strengths, weaknesses, and missing elements in the current literature, as well as offer an acute exercise standardization protocol and provide possible goals for future research.
As we age, cognitive decline, though not inevitable, is a common occurrence resulting from the process of neurodegeneration. In some instances, neurodegeneration results in mild cognitive impairment or more severe forms of dementia including Alzheimer’s, Parkinson’s, or Huntington’s disease. Because of the role of exercise in enhancing neurogenesis and brain plasticity, physical activity may serve as a potential therapeutic tool to prevent, delay, or treat cognitive decline. Indeed, studies in both rodents and humans have shown that long-term exercise is helpful in both delaying the onset of cognitive decline and dementia as well as improving symptoms in patients with an already existing diagnosis
·ncbi.nlm.nih.gov·
Effects of Acute Exercise on Mood, Cognition, Neurophysiology, and Neurochemical Pathways - A Review
Memetics - Wikipedia
Memetics - Wikipedia
The term "meme" was coined by biologist Richard Dawkins in his 1976 book The Selfish Gene,[1] to illustrate the principle that he later called "Universal Darwinism".
He gave as examples, tunes, catchphrases, fashions, and technologies. Like genes, memes are selfish replicators and have causal efficacy; in other words, their properties influence their chances of being copied and passed on.
Just as genes can work together to form co-adapted gene complexes, so groups of memes acting together form co-adapted meme complexes or memeplexes.
Criticisms of memetics include claims that memes do not exist, that the analogy with genes is false, that the units cannot be specified, that culture does not evolve through imitation, and that the sources of variation are intelligently designed rather than random.
·en.m.wikipedia.org·
Memetics - Wikipedia
How can we develop transformative tools for thought?
How can we develop transformative tools for thought?
a more powerful aim is to develop a new medium for thought. A medium such as, say, Adobe Illustrator is essentially different from any of the individual tools Illustrator contains. Such a medium creates a powerful immersive context, a context in which the user can have new kinds of thought, thoughts that were formerly impossible for them. Speaking loosely, the range of expressive thoughts possible in such a medium is an emergent property of the elementary objects and actions in that medium. If those are well chosen, the medium expands the possible range of human thought.
Memory systems make memory into a choice, rather than an event left up to chance: This changes the relationship to what we're learning, reduces worry, and frees up attention to focus on other kinds of learning, including conceptual, problem-solving, and creative.
Memory systems can be used to build genuine conceptual understanding, not just learn facts: In Quantum Country we achieve this in part through the aspiration to virtuoso card writing, and in part through a narrative embedding of spaced repetition that gradually builds context and understanding.
Mnemonic techniques such as memory palaces are great, but not versatile enough to build genuine conceptual understanding: Such techniques are very specialized, and emphasize artificial connections, not the inherent connections present in much conceptual knowledge. The mnemonic techniques are, however, useful for bootstrapping knowledge with an ad hoc structure.
What practices would lead to tools for thought as transformative as Hindu-Arabic numerals? And in what ways does modern design practice and tech industry product practice fall short? To be successful, you need an insight-through-making loop to be operating at full throttle, combining the best of deep research culture with the best of Silicon Valley product culture.
Historically, work on tools for thought has focused principally on cognition; much of the work has been stuck in Spock-space. But it should take emotion as seriously as the best musicians, movie directors, and video game designers. Mnemonic video is a promising vehicle for such explorations, possibly combining both deep emotional connection with the detailed intellectual mastery the mnemonic medium aspires toward.
It's striking to contrast conventional technical books with the possibilities enabled by executable books. You can imagine starting an executable book with, say, quantum teleportation, right on the first page. You'd provide an interface – perhaps a library is imported – that would let users teleport quantum systems immediately. They could experiment with different parts of the quantum teleportation protocol, illustrating immediately the most striking ideas about it. The user wouldn't necessarily understand all that was going on. But they'd begin to internalize an accurate picture of the meaning of teleportation. And over time, at leisure, the author could unpack some of what might a priori seem to be the drier details. Except by that point the reader will be bought into those details, and they won't be so dry
Aspiring to canonicity, one fun project would be to take the most recent IPCC climate assessment report (perhaps starting with a small part), and develop a version which is executable. Instead of a report full of assertions and references, you'd have a live climate model – actually, many interrelated models – for people to explore. If it was good enough, people would teach classes from it; if it was really superb, not only would they teach classes from it, it could perhaps become the creative working environment for many climate scientists.
In serious mediums, there's a notion of canonical media. By this, we mean instances of the medium that expand its range, and set a new standard widely known amongst creators in that medium. For instance, Citizen Kane, The Godfather, and 2001 all expanded the range of film, and inspired later film makers. It's also true in new media. YouTubers like Grant Sanderson have created canonical videos: they expand the range of what people think is possible in the video form. And something like the Feynman Lectures on Physics does it for textbooks. In each case one gets the sense of people deeply committed to what they're doing. In many of his lectures it's obvious that Feynman isn't just educating: he's reporting the results of a lifelong personal obsession with understanding how the world works. It's thrilling, and it expands the form.
There's a general principle here: good tools for thought arise mostly as a byproduct of doing original work on serious problems.
Game companies develop many genuinely new interface ideas. This perhaps seems surprising, since you'd expect such interface ideas to also suffer from the public goods problem: game designers need to invest enormous effort to develop those interface ideas, and they are often immediately copied (and improved on) by other companies, at little cost. In that sense, they are public goods, and enrich the entire video game ecosystem.
Many video games make most of their money from the first few months of sales. While other companies can (and do) come in and copy or riff on any new ideas, it often does little to affect revenue from the original game, which has already made most of its money In fact, cloning is a real issue in gaming, especially in very technically simple games. An example is the game Threes, which took the developers more than a year to make. Much of that time was spent developing beautiful new interface ideas. The resulting game was so simple that clones and near-clones began appearing within days. One near clone, a game called 2048, sparked a mini-craze, and became far more successful than Threes. At the other extreme, some game companies prolong the revenue-generating lifetime of their games with re-releases, long-lived online versions, and so on. This is particularly common for capital-intensive AAA games, such as the Grand Theft Auto series. In such cases the business model relies less on clever new ideas, and more on improved artwork (for re-release), network effects (for online versions), and branding. . While this copying is no doubt irritating for the companies being copied, it's still worth it for them to make the up-front investment.
in gaming, clever new interface ideas can be distinguishing features which become a game's primary advantage in the marketplace. Indeed, new interface ideas may even help games become classics – consider the many original (at the time) ideas in games ranging from Space Invaders to Wolfenstein 3D to Braid to Monument Valley. As a result, rather than underinvesting, many companies make sizeable investments in developing new interface ideas, even though they then become public goods. In this way the video game industry has largely solved the public goods problems.
It's encouraging that the video game industry can make inroads on the public goods problem. Is there a solution for tools for thought? Unfortunately, the novelty-based short-term revenue approach of the game industry doesn't work. You want people to really master the best new tools for thought, developing virtuoso skill, not spend a few dozen hours (as with most games) getting pretty good, and then moving onto something new.
Adobe shares in common with many other software companies that much of their patenting is defensive: they patent ideas so patent trolls cannot sue them for similar ideas. The situation is almost exactly the reverse of what you'd like. Innovative companies can easily be attacked by patent trolls who have made broad and often rather vague claims in a huge portfolio of patents, none of which they've worked out in much detail. But when the innovative companies develop (at much greater cost) and ship a genuinely good new idea, others can often copy the essential core of that idea, while varying it enough to plausibly evade any patent. The patent system is not protecting the right things.
many of the most fundamental and powerful tools for thought do suffer the public goods problem. And that means tech companies focus elsewhere; it means many imaginative and ambitious people decide to focus elsewhere; it means we haven't developed the powerful practices needed to do work in the area, and a result the field is still in a pre-disciplinary stage. The result, ultimately, is that it means the most fundamental and powerful tools for thought are undersupplied.
Culturally, tech is dominated by an engineering, goal-driven mindset. It's much easier to set KPIs, evaluate OKRs, and manage deliverables, when you have a very specific end-goal in mind. And so it's perhaps not surprising that tech culture is much more sympathetic to AGI and BCI as overall programs of work. But historically it's not the case that humanity's biggest breakthroughs have come about in this goal-driven way. The creation of language – the ur tool for thought – is perhaps the most important occurrence of humanity's existence. And although the origin of language is hotly debated and uncertain, it seems extremely unlikely to have been the result of a goal-driven process. It's amusing to try imagining some prehistoric quarterly OKRs leading to the development of language. What sort of goals could one possibly set? Perhaps a quota of new irregular verbs? It's inconceivable!
Even the computer itself came out of an exploration that would be regarded as ridiculously speculative and poorly-defined in tech today. Someone didn't sit down and think “I need to invent the computer”; that's not a thought they had any frame of reference for. Rather, pioneers such as Alan Turing and Alonzo Church were exploring extremely basic and fundamental (and seemingly esoteric) questions about logic, mathematics, and the nature of what is provable. Out of those explorations the idea of a computer emerged, after many years; it was a discovered concept, not a goal.
Fundamental, open-ended questions seem to be at least as good a source of breakthroughs as goals, no matter how ambitious. This is difficult to imagine or convince others of in Silicon Valley's goal-driven culture. Indeed, we ourselves feel the attraction of a goal-driven culture. But empirically open-ended exploration can be just as, or more successful.
There's a lot of work on tools for thought that takes the form of toys, or “educational” environments. Tools for writing that aren't used by actual writers. Tools for mathematics that aren't used by actual mathematicians. And so on. Even though the creators of such tools have good intentions, it's difficult not to be suspicious of this pattern. It's very easy to slip into a cargo cult mode, doing work that seems (say) mathematical, but which actually avoids engagement with the heart of the subject. Often the creators of these toys have not ever done serious original work in the subjects for which they are supposedly building tools. How can they know what needs to be included?
·numinous.productions·
How can we develop transformative tools for thought?
Rumination: Relationships with Physical Health
Rumination: Relationships with Physical Health
Rumination is a form of perserverative cognition that focuses on negative content, generally past and present, and results in emotional distress. Initial studies of rumination emerged in the psychological literature, particularly with regard to studies examining specific facets of rumination (e.g., positive vs. negative rumination, brooding vs. self-reflection, relationships with catastrophic thinking, role of impaired disengagement, state vs. trait features) as well as the presence of rumination in various psychiatric syndromes (e.g., depression, alcohol misuse, generalized anxiety disorder, social anxiety disorder, obsessive compulsive disorder, posttraumatic stress disorder, bulimia nervosa).
·ncbi.nlm.nih.gov·
Rumination: Relationships with Physical Health
Longitudinal Associations Between Parenting and Child Big Five Personality Traits
Longitudinal Associations Between Parenting and Child Big Five Personality Traits

The provided web page discusses a study on the longitudinal associations between parenting practices and child Big Five personality traits. Here are the key takeaways and findings from the content:

  1. Association Between Parenting and Child Personality:

    • Previous research has explored the associations between parenting and various child characteristics, but less has been done on the longitudinal associations with child Big Five personality traits.
    • Studies have shown both positive and non-significant associations between parental warmth and child personality traits.
  2. Longitudinal Analyses and Changes Over Time:

    • The study utilized longitudinal data with assessments at different grades (5, 6, 7, and 8).
    • Changes in parenting behaviors over time were observed, with a general trend of decreased parental involvement and structure as children entered adolescence.
  3. Measurement Invariance Tests:

    • Measurement invariance tests were conducted to ensure that changes in latent factors represented real changes in constructs rather than changes in relations between factors and indicators across time.
  4. Correlations and Effect Sizes:

    • The magnitudes of correlations between parenting variables and child personality were reported to be small, averaging around 0.05.
    • The study emphasized that small effect sizes should not be dismissed, and the associations were comparable to those found between other environmental factors and child personality.
  5. Practical Implications:

    • The study suggested that the small and non-significant associations should not discourage research on parenting interventions. Modest changes in parenting and child personality, when multiplied by the population, can have meaningful effects.
  6. Changes in Child Personality Over Time:

    • As children got older, they became less conscientious and less open to experience, as indicated by negative slopes in the longitudinal analyses.
  7. Parenting and Child Personality Complexity:

    • The link between parenting and child personality was described as complex, transactional, and dynamic. The study considered theories like Social Learning Theory and Attachment Theory but highlighted the need for a nuanced understanding.
  8. Limitations and Future Directions:

    • The study acknowledged limitations, such as the small effect sizes and the complex nature of personality development. It emphasized the need to consider multiple environmental factors contributing to personality development.
  9. Contributions and Data Accessibility:

    • The authors highlighted contributions to the conception, design, acquisition, analysis, and interpretation of data by various individuals. The study's materials and data are accessible on the Open Science Framework.
  10. Conclusion:

    • Despite small effect sizes, the study suggests that understanding the association between parenting and child personality requires a nuanced approach, and interventions at the population level can still be meaningful.

Overall, the study contributes insights into the complex and dynamic relationship between parenting practices and child personality development, recognizing the importance of considering multiple factors and the potential impact of interventions.

·online.ucpress.edu·
Longitudinal Associations Between Parenting and Child Big Five Personality Traits
Impression Management
Impression Management
Although impression management has been relatively free of controversy as a scholarly topic, some disagreements have formed around the ethics of managing impressions, how to best measure impression management, and whether impression management explains some of the more venerable topics in social science such as prosocial behavior, cognitive dissonance, and moral judgment.
Other work has investigated how easy it is to mismanage an impression, such as when “humble bragging” and giving “backhanded compliments.”
·oxfordre.com·
Impression Management