1. What am I missing from church?
(Or, in general, by lacking a religious/spiritual practice I share with others)
For the past few months I’ve been thinking about this question.
I haven’t regularly attended church in over ten years. Given how prevalent it is as part of human existence, and how much I have changed in a decade, it seems like “trying it out” or experimenting is at least somewhat warranted.
I predict that there is a church in my city that is culturally compatible with me.
Compatible means a lot of things, but mostly means that I’m better off with them than without them, and they’re better off with me than without me.
Unpacking that probably will get into a bunch of specifics about beliefs, epistemics, and related topics—which seem pretty germane to rationality.
2. John Vervaeke’s Awakening from the Meaning Crisis is bizzarely excellent.
I don’t exactly have handles for exactly everything it is, or exactly why I like it so much, but I’ll try to do it some justice.
It feels like rationality / cognitive tech, in that it cuts at the root of how we think and how we think about how we think.
(I’m less than 20% through the series, but I expect it continues in the way it has been going.)
Maybe it’s partially his speaking style, and partially the topics and discussion, but it reminded me strongly of sermons from childhood.
In particular: they have a timeless quality to them. By “timeless” I mean I think I would take away different learnings from them if I saw them at different points in my life.
In my work & research (and communicating this) -- I’ve largely strived to be clear and concise. Designing for layered meaning seems antithetical to clarity.
However I think this “timelessness” is a missing nutrient to me, and has me interested in seeking it out elsewhere.
For the time being I at least have a bunch more lectures in the series to go!
Can LessWrong pull another “crypto” with Illinois?I have been following the issue with the US state Illinois’ debt with growing horror.Their bond status has been heavily degraded—most states’ bonds are “high quality” with the standards agencies (moodys, standard & poor, fitch), and Illinois is “low quality”. If they get downgraded more they become a “junk” bond, and lose access to a bunch of the institutional buyers that would otherwise be continuing to lend.COVID has increased many states costs’, for reasons I can go into later, so it seems reasonable to think we’re much closer to a tipping point than we were last year.As much as I would like to work to make the situation better I don’t know what to do. In the meantime I’m left thinking about how to “bet my beliefs” and how one could stake a position against Illinois.Separately I want to look more into EU debt / restructuring / etc as its probably a good historical example of how this could go. Additionally previously the largest entity to go bankrupt in the USA was the city of Detroit, which probably is also another good example to learn from.
COVID has increased many states costs’, for reasons I can go into later, so it seems reasonable to think we’re much closer to a tipping point than we were last year.As much as I would like to work to make the situation better I don’t know what to do. In the meantime I’m left thinking about how to “bet my beliefs” and how one could stake a position against Illinois.
Is the COVID tipping point consideration making you think that the bonds are actually even worse than the “low quality” rating suggests? (Presumably the low ratings are already baked into the bond prices.)
Looking at this more, I think I my uncertainty is resolving towards “No”.Some things:- It’s hard to bet against the bonds themselves, since we’re unlikely to hold them as individuals- It’s hard to make money on the “this will experience a sharp decline at an uncertain point in the future” kind of prediction (much easier to do this for the “will go up in price” version, which is just buying/long)- It’s not clear anyone was able to time this properly for Detroit, which is the closest analog in many ways- Precise timing would be difficult, much more so while being far away from the stateI’ll continue to track this just because of my family in the state, though.Point of data: it was 3 years between Detroit bonds hitting “junk” status, and the city going bankrupt (in the legal filing sense), which is useful for me for intuitions as to the speed of these.
Intersubjective Mean and Variability.
(Subtitle: I wish we shared more art with each other)
This is mostly a reaction to the (10y old) LW post: Things you are supposed to like.
I think there’s two common stories for comparing intersubjective experiences:
“Mismatch”: Alice loves a book, and found it deeply transformative. Beth, who otherwise has very similar tastes and preferences to Alice, reads the book and finds it boring and unmoving.
“Match”: Charlie loves a piece of music. Daniel, who shares a lot of Charlie’s taste in music, listens to it and also loves it.
One way I can think of unpacking this is that there is in terms of distributions:
“Mean”—the shared intersubjective experiences, which we see in the “Match” case
“Variability”—the difference in intersubjective experiences, which we see in the “Mismatch” case
Another way of unpacking this is due to factors within the piece or within the subject
“Intrinsic”—factors that are within the subject, things like past experiences and memories and even what you had for breakfast
“Extrinsic”—factors that are within the piece itself, and shared by all observers
And one more ingredient I want to point at is question substitution. In this case I think the effect is more like “felt sense query substitution” or “received answer substitution” since it doesn’t have an explicit question.
When asked about a piece (of art, music, etc) people will respond with how they felt—which includes both intrinsic and extrinsic factors.
Anyways what I want is better social tools for separating out these, in ways that let people share their interest and excitement in things.
I think that these mismatches/misfirings (like the LW post that set this off) and the reactions to them cause a chilling effect, where the LW/rationality community is not sharing as much art because of this
I want to be in a community that’s got a bunch of people sharing art they love and cherish
I think great art is underrepresented in LW and want to change that.
How I would do a group-buy of methylation analysis.
(N.B. this is “thinking out loud” and not actually a plan I intend to execute)
Methylation is a pretty commonly discussed epigenetic factor related to aging. However it might be the case that this is downstream of other longevity factors.
I would like to measure my epigenetics—in particular approximate rates/locations of methylation within my genome. This can be used to provide an approximate biological age correlate.
There are different ways to measure methylation, but one I’m pretty excited about that I don’t hear mentioned often enough is the Oxford Nanopore sequencer.
The mechanism of the sequencer is that it does direct-reads (instead of reading amplified libraries, which destroy methylation unless specifically treated for it), and off the device is a time-series of electrical signals, which are decoded into base calls with a ML model. Unsurprisingly, community members have been building their own base caller models, including ones that are specialized to different tasks.
So the community made a bunch of methylation base callers, and they’ve been found to be pretty good.
So anyways the basic plan is this:
Extract a bunch of cells (probably blood but could be other sources)
Extract DNA from cells
Prep the samples
Sequence w/ ONT and get raw data
Use the combined model approach to analyze the targets from this analysis
Why I think this is cool? Mostly because ONT makes a $1k sequencer than can fit in your pocket, and can do well in excess of 1-10Gb reads before needing replacement consumables. This is mostly me daydreaming what I would want to do with it.
Aside: they also have a pretty cool $9k sample prep tool, which would be useful to me since I’m empirically crappy at doing bio experiments, but the real solution would probably just be to have a contract lab do all the steps and just send the data.
(Note: this might be difficult to follow. Discussing different ways that different people relate to themselves across time is tricky. Feel free to ask for clarifications.)
I’m reading the paper Against Narrativity, which is a piece of analytic philosophy that examines Narrativity in a few forms:
Psychological Narrativity—the idea that “people see or live or experience their lives as a narrative or story of some sort, or at least as a collection of stories.”
Ethical Narrativity—the normative thesis that “experiencing or conceiving one’s life as a narrative is a good thing; a richly [psychologically] Narrative outlook is essential to a well-lived life, to true or full personhood.”
It also names two kinds of self-experience that it takes to be diametrically opposite:
Diachronic—considers the self as something that was there in the further past, and will be there in the further future
Episodic—does not consider the self as something that was there in the further past and something that will be there in the further future
Wow, these seem pretty confusing. It sounds a lot like they just disagree on the definition of the world “self”. I think there is more to it than that, some weak evidence being discussing this concept of length with a friend (diachronic) who had a very different take on narrativity than myself (episodic).
I’ll try to sketch what I think “self” means. It seems that for almost all nontrivial cognition, it seems like intelligent agents have separate concepts (or the concept of a separation between) the “agent” and the “environment”. In Vervaeke’s works this is called the Agent-Arena Relationship.
You might say “my body is my self and the rest is the environment,” but is that really how you think of the distinction? Do you not see the clothes you’re currently wearing as part of your “agent”? Tools come to mind as similar extensions of our self. If I’m raking leaves for a long time, I start to sense myself as a the agent being the whole “person + rake” system, rather than a person whose environment includes a rake that is being held.
(In general I think there’s something interesting here in proto-human history about how tool use interacts with our concept of self, and our ability to quickly adapt to thinking of a tool as part of our ‘self’ as a critical proto-cognitive-skill.)
Getting back to Diachronic/Episodic: I think one of the things that’s going on in this divide is that this felt sense of “self” extends forwards and backwards in time differently.
I often feel very uncertain in my understanding or prediction of the moral and ethical natures of my decisions and actions. This probably needs a whole lot more writing on its own, but I’ll sum it up as two ideas having a disproportionate affect on me:
The veil of ignorance, which is a thought experiment which leads people to favor policies that support populations more broadly (skipping a lot of detail and my thoughts on it for now).
The categorical imperative, which I’ll reduce here as the principle of universalizability—a policy for actions given context is moral if it is one you would endorse universalizing (this is huge and complex, and there’s a lot of finicky details in how context is defined, etc. skipping that for now)
Both of these prompt me to take the perspective of someone else, potentially everyone else, in reasoning through my decisions. I think the way I relate to them is very Non-Narrative/Episodic in nature.
(Separately, as I think more about the development of early cognition, the more the ability to take the perspective of someone else seems like a magical superpower)
I think they are not fundamentally or necessarily Non-Narrative/Episodic—I can imagine both of them being considered by someone who is Strongly Narrative and even them imagining a world consisting of a mixture of Diachronic/Episodic/etc.
Priors are hard. Relatedly, choosing between similar explanations of the same evidence is hard.
I really like the concept of the Solomonoff prior, even if the math of it doesn’t apply directly here. Instead I’ll takeaway just this piece of it:
“Prefer explanations/policies that are simpler-to-execute programs”
A program may be simpler if it has fewer inputs, or fewer outputs. It might be simpler if it requires less memory or less processing.
This works well for choosing policies that are easier to implement or execute, especially as a person with bounded memory/processing/etc.
A simplifying assumption that works very well for dynamic systems is the Markov property.
This property states that all of the information in the system is present in the current state of the system.
One way to look at this is in imagining a bunch of atoms in a moment of time—all of the information in the system is contained in the current positions and velocities of the atoms. (We can ignore or forget all of the trajectories that individual atoms took to get to their current locations)
In practice we usually do this to systems where this isn’t literally true, but close-enough-for-practical-purposes, and combine it with stuffing some extra stuff into the context for what “present” means.
(For example we might define the “present” state of a natural system includes “the past two days of observations”—this still has the Markov property, because this information is finite and fixed as the system proceeds dynamically into the future)
I think that these pieces, when assembled, steer me towards becoming Episodic.
When choosing between policies that have the same actions, I prefer the policies that are simpler. (This feels related to the process of distilling principles.)
When considering good policies, I think I consider strongly those policies that I would endorse many people enact. This is aided by these policies being simpler to imagine.
Policies that are not path-dependent (for example, take into account fewer things in a person’s past) are simpler, and therefore easier to imagine.
Path-independent policies are more Episodic, in that they don’t rely heavily on a person’s place in their current Narratives.
I don’t know what to do with all of this.
I think one thing that’s going on is self-fulfilling—where I don’t strongly experience psychological Narratives, and therefore it’s more complex for me to simulate people who do experience this, which via the above mechanism leads to me choosing Episodic policies.
I don’t strongly want to recruit everyone to this method of reasoning. It is an admitted irony of this system (that I don’t wish for everyone to use the same mechanism of reasoning as me) -- maybe just let it signal just how uncertain I feel about my whole ability to come to philosophical conclusions on my own.
I expect to write more about this stuff in the near future, including experiments I’ve been doing in my writing to try to move my experience in the Diachronic direction. I’d be happy to hear comments for what folks are interested in.
When choosing between policies that have the same actions, I prefer the policies that are simpler.
Could you elaborate on this? I feel like there’s a tension between “which policy is computationally simpler for me to execute in the moment?” and “which policy is more easily predicted by the agents around me?”, and it’s not obvious which one you should be optimizing for. [Like, predictions about other diachronic people seem more durable / easier to make, and so are easier to calculate and plan around.] Or maybe the ‘simple’ approaches for one metric are generally simple on the other metric.
My feeling is that I don’t have a strong difference between them. In general simpler policies are both easier to execute in the moment and also easier for others to simulate.
The clearest version of this is to, when faced with a decision, decide on an existing principle to apply before acting, or else define a new principle and act on this.
Principles are examples of short policies, which are largely path-independent, which are non-narrative, which are easy to execute, and are straightforward to communicate and be simulated by others.
Thinking more about the singleton risk / global stable totalitarian government risk from Bostrom’s Superintelligence, human factors, and theory of the firm.
Human factors represent human capacities or limits that are unlikely to change in the short term. For example, the number of people one can “know” (for some definition of that term), limits to long-term and working memory, etc.
Theory of the firm tries to answer “why are economies markets but businesses autocracies” and related questions. I’m interested in the subquestion of “what factors given the upper bound on coordination for a single business”, related to “how big can a business be”.
I think this is related to “how big can an autocracy (robustly/stably) be”, which is how it relates to the singleton risk.
Some thoughts this produces for me:
Communication and coordination technology (telephones, email, etc) that increase the upper bounds of coordination for businesses ALSO increase the upper bound on coordination for autocracies/singletons
My belief is that the current max size (in people) of a singleton is much lower than current global population
This weakly suggests that a large global population is a good preventative for a singleton
I don’t think this means we can “war of the cradle” our way out of singleton risk, given how fast tech moves and how slow population moves
I think this does mean that any non-extinction event that dramatically reduces population also dramatically increases singleton risk
I think that it’s possible to get a long-term government aligned with the values of the governed, and “singleton risk” is the risk of an unaligned global government
So I think I’d be interested in tracking two “competing” technologies (for a hand-wavy definition of the term)
communication and coordination technologies—tools which increase the maximum effective size of coordination
soft/human alignment technologies—tools which increase alignment between government and governed
Did Bostrom ever call it singleton risk? My understanding is that it’s not clear that a singleton is more of an x-risk than its negative; a liberal multipolar situation under which many kinds of defecting/carcony factions can continuously arise.
I don’t know if he used that phrasing, but he’s definitely talked about the risks (and advantages) posed by singletons.
I seem to learn a bunch about my aesthetics of books by wandering a used book store for hours.
Some books I want in hardcover but not softcover. Some books I want in softcover but not hardcover. Most books I want to be small.
I prefer older books to newer books, but I am particular about translations. Older books written in english (and not translated) are gems.
I have a small preference for books that are familiar to me, a nontrivial part of them were because they were excerpts taught in english class.
I don’t really know what exactly constitutes a classic, but I think I prefer them. Lists of “Great Classics” like Mortimer Adler’s are things I’ve referenced in the past.
I enjoy going through multi-volume series (like the Harvard Classics) but I think I prefer my library to be assembled piecemeal.
That being said, I really like the Penguin Classics. Maybe they’re familiar, or maybe their taste matches my own.
I like having a little lending library near my house so I can elegantly give away books that I like and think are great, but I don’t want in my library anymore.
Very few books I want as references, and I still haven’t figured out what references I do want. (So far a small number: Constitution, Bible)
I think a lot about “Ability to Think” (a whole separate topic) and it seems like great works are the products of great ‘ability to think’.
Also it seems like authors of great works know or can recognize other great works.
This suggests that figuring out who’s taste I think is great, and seeing what books they recommend or enjoy.
I wish there was a different global project of accumulating knowledge than books. I think books works well for poetry and literature, but it works less well for science and mechanics.
Wikipedia is similar to this, but is more like an encyclopedia, and I’m looking for something that includes more participatory knowledge.
Maybe what I’m looking for is a more universal system of cross-referencing and indexing content. The internet as a whole would be a good contender here, but is too haphazard.
I’d like things like “how to build a telescope at home” and “analytic geometry” to be well represented, but also in the participatory knowledge sort of way.
(This is the way in which much of human knowledge is apprenticeship-based and transferred, and merely knowing the parts of a telescope—what you’d learn from an encyclopedia—is insufficient to be able to make one)
I expect to keep thinking on this, but for now I have more books!
Future City Idea: an interface for safe AI-control of traffic lightsWe want a traffic light that* Can function autonomously if there is no network connection* Meets some minimum timing guidelines (for example, green in a particular direction no less than 15 seconds and no more than 30 seconds, etc)* Secure interface to communicate with city-central control* Has sensors that allow some feedback for measuring traffic efficiency or throughputThis gives constraints, and I bet an AI system could be trained to optimize efficiency or throughput within the constraints. Additionally, you can narrow the constraints (for example, only choosing 15 or 16 seconds for green) and slowly widen them in order to change flows slowly.This is the sort of thing Hash would be great for, simulation wise. There’s probably dedicated traffic simulators, as well.At something like a quarter million dollars a traffic light, I think there’s an opportunity here for startup.(I don’t know Matt Gentzel’s LW handle but credit for inspiration to him)
I expect that the functioning of traffic lights is regulated in a way that makes it hard for a startup to deploy such a system.
AGI technical domains
When I think about trying to forecast technology for the medium term future, especially for AI/AGI progress, it often crosses a bunch of technical boundaries.
These boundaries are interesting in part because they’re thresholds where my expertise and insight falls off significantly.
Also interesting because they give me topics to read about and learn.
A list which is probably neither comprehensive, nor complete, nor all that useful, but just writing what’s in my head:
Machine learning research—this is where a lot of the tip-of-the-spear of AI research is happening, and seems like that will continue to the near future
Machine learning software—tightly coupled to the research, this is the ability to write programs that do machine learning
Machine learning compilers/schedulers—specialized compilers translate the program into sequences of operations to run on hardware. High quality compilers (or the lack of them) has blocked a bunch of nontraditional ML-chips from getting traction.
Supercomputers / Compute clusters—large arrays of compute hardware connected in a dense network. Once the domain of government secret projects, now it’s common for AI research companies to have (or rent) large compute clusters. Picking the hardware (largely commercial-off-the-shelf), designing the topology of connections, and building it are all in this domain.
Hardware (Electronics/Circuit) Design—A step beyond building clusters out of existing hardware is designing custom hardware, but using existing chips and chipsets. This allows more exotic connectivity topologies than you can get with COTS hardware, or allows you to fill in gaps that might be missing in commercially available hardware.
Chip Design—after designing the circuit boards comes designing the chips themselves. There’s a bunch of AI-specific chips that are already on the market, or coming soon, and almost all of them are examples of this. Notably most companies that design chips are “fabless”—meaning they need to partner with a manufacturer in order to produce the chip. Nvidia is an example of a famous fabless chip designer. Chips are largely designed with Process Design Kits (PDKs) which specify a bunch of design rules, limitations, and standard components (like SRAM arrays, etc).
PDK Design—often the PDKs will have a bunch of standard components that are meant to be general purpose, but specialized applications can take advantage of more strange configurations. For example, you could change a SRAM layout to tradeoff a higher bit error rate for lower power, or come up with different ways to separate clock domains between parts of a chip. Often this is done by companies who are themselves fabless, but also don’t make/sell their own chips (and instead will research and develop this technology to integrate with chip designers).
Chip Manufacture (Fabrication / Fab) - This is some of the most advanced technology humanity has produced, and is probably familiar to many folks here. Fabs take chip designs and produce chips—but the amount of science and research that goes into making that happen is enormous. Fabs probably have the tightest process controls of any manufacturing process in existence, all in search of increasing fractions of a percent of yield (the fraction of manufactured chips which are acceptable).
Fab Process Research—For a given fab (semiconductor manufacturing plant—“fabricator”) there might be specializations for different kinds of chips that are different enough to warrant their own “process” (sequence of steps executed to manufacture it). For example, memory chips and compute chips are different enough to need different processes, and developing these processes requires a bunch of research.
Fab “Node” Research—Another thing people might be familiar with is the long-running trend for semiconductors to get smaller and denser. The “Node” of a semiconductor process refers to this size (and other things that I’m going to skip for now). This is separate from (but related to) optimizing manufacturing processes, but is about designing and building new processes in order to shrink features sizes, or push aspect ratios. Every small decrease (e.g. “5nm” → “3nm”, though those sizes don’t refer to anything real) costs tens of billions of dollars, and further pushes are likely even more expensive.
Semiconductor Assembly Research—Because we have different chips that need different processes (e.g. memory chips and compute chips) -- we want to connect them together, ideally better than we could do with just a circuit board. This research layer includes things like silicon interposers, and various methods of 3D stacking and connection of chips. (Probably also should consider reticle-boundary-crossing here, but it kinda is also simultaneously a few of the other layers)
Semiconductor Materials Science—This probably should be broken up, but I know the least about this. Semiconductors can produce far more than chips like memory and compute—they can also produce laser diodes, camera sensors, solar panels, and much more! This layer includes exotic methods of combining or developing new technologies—e.g. “photonics at the edge”—a chip where the connections to it are optical instead of electronic!
Anyways I hope that was interesting to some folks.
“Bet Your Beliefs” as an epistemic mode-switch
I was just watching this infamous interview w/ Patrick Moore where he seems to be doing some sort of epistemic mode switch (the “weed killer” interview)
Moore appears to go from “it’s safe to drink a cup of glyphosate” to (being offered the chance to do that) “of course not / I’m not stupid”.
This switching between what seems to be a tribal-flavored belief (glyphosate is safe) and a self-protecting belief (glyphosate is dangerous) is what I’d like to call an epistemic mode-switch. In particular, it’s a contradiction in beliefs, that’s really only obvious if you can get both modes to be near each other (in time/space/whatever).
In the rationality community, it seems good to:
Admit this is just a normal part of human reasoning. We probably all do this to some degree some times, and
It seems like there are ways we can confront this by getting the modes near each other.
I think one of the things thats going on here is a short-term self-preservation incentive is a powerful tool for forcing yourself to be clear about your beliefs. In particular, it seems good at filtering/attenuating beliefs that are just tribal signaling.
This suggests that if you can get people to use this kind of short-term self-preservation incentive, you can probably get them to report more calibrated and consistent beliefs.
I think this is one of the better functions of “bet your beliefs”. Summarizing what I understand “bet your beliefs” to be: There is a norm in the rationality community of being able to challenge peoples beliefs by asking them to form bets on them (or forming and offering them bets on them) -- and taking/refusing bets is seen as evidence of admission of beliefs.
Previously I’ve mostly just thought of this as a way of increasing evidence that someone believes what they say they do. If them saying “I believe X” is some small amount of evidence, then them accepting a bet about X is more evidence.
However, now I see that there’s potentially another factor at play. By forcing them to consider short-term losses, you can induce an epistemic mode-switch away from signaling beliefs towards self-preservation beliefs.
It’s possible this is already what people thought “bet your beliefs” was doing, and I’m just late to the party.
Caveat: the rest of this is just pontification.
It seems like a bunch of the world has a bunch of epistemic problems. Not only are there a lot of obviously bad and wrong beliefs, they seem to be durable and robust to evidence that they’re bad and wrong.
Maybe this suggests a particular kind remedy to epistemological problems, or at the very least “how can I get people to consider changing their mind”—by setting up situations that trigger short-term self-preservation thinking.
 Context from 33:50 here:
A failure mode for “betting your beliefs” is developing an urge to reframe your hypotheses as beliefs, which harms the distinction. It’s not always easy/possible/useful to check hypotheses for relevance to reality, at least until much later in their development, so it’s important to protect them from being burdened with this inconvenience. It’s only when a hypothesis is ready for testing (which is often immediately), or wants to be promoted to a belief (probably as an element of an ensemble), that making predictions becomes appropriate.
Oh yeah like +100% this.
Creating an environment where we can all cultivate our weird hunches and proto-beliefs while sharing information and experience would be amazing.
I think things like “Scout Mindset” and high baselines of psychological safety (and maybe some of the other phenomenological stuff) help as well.
If we have the option to create these environments instead, I think we should take that option.
If we don’t have that option (and the environment is a really bad epistemic baseline) -- I think the “bet your beliefs” does good.
There seem to be two different concepts being conflated here. One is “it will be extremely unlikely to cause permanent injury”, while the other is “it will be extremely unlikely to have any unpleasant effects whatsoever”. I have quite a few personal experiences with things that are the first but absolutely not the second, and would fairly strenuously avoid going through them again without extremely good reasons.
I’m sure you can think of quite a few yourself.
The Positive and the Negative
I work on AI alignment, in order to solve problems of X-Risk. This is a very “negative” kind of objective.
Negatives are weird. Don’t do X, don’t be Y, don’t cause Z. They’re nebulous and sometimes hard to point at and move towards.
I hear a lot of a bunch of doom-y things these days. From the evangelicals, that this is the end times / end of days. From environmentalists that we are in a climate catastrophe. From politicians that we’re in a culture war / edging towards a civil war. From the EAs/Rationalists that we’re heading towards potential existential catastrophe (I do agree with this one).
I think cognition and emotion and relation can get muddied up with too much of negatives without things to balance them out. I don’t just want to prevent x-risk—I also want to bring about a super awesome future.
So I think personally I’m going to try to be more balanced in this regard, even in the small scale, by mixing in the things I’m wanting to move towards in addition to things I want to move away from.
In the futurist and long term communities, I want to endorse and hear more about technology developments that help bring about a more awesome future (longevity and materials science come to mind as concrete examples).