I’ve enjoyed Scott Young’s writing since he’s the kind of interested amateur who dips into all kinds of areas without committing to professional work. So it was interesting to read his impression of literature research; What if You Don’t Feel Smart Enough?

The expectation is that as you learn more and more, you’ll eventually hit a bedrock of irrefutable scientific fact. Except usually, the bottom of one’s investigation is muck. Some parts of the original idea get sharpened, others blur as more complications and nuance are introduced.

And it’s true that it’s not well appreciated how tentative scientific explanation is as new areas are explored. It’s been exciting for me to watch COVID-19 science develop in real time, so quickly. Yes, scary and polarized in ways that we generally don’t see in medicine, but a predictable back and forth on the properties of the virus, its propagation, and treatment.

We generally know what we know

Scott misses the important point that there is a bedrock of knowledge, the literature just doesn’t bother to discuss it. In neuroscience, the basic physical architecture and cellular makeup of the brain was established with great clarity over the last 100 years or so. As techniques have been introduced, new areas opened up and took a while to get settled into bedrock, but much of that is done now. In fact, my first published paper in 1983 was part of a major chapter in that story when labs used retrograde tracing techniques to map brain connections. My paper established the identity of all of the areas that sent connections to the motor trigeminal nucleus in the rat. That’s the collection of motor neurons that innervate the jaw closing muscles.

We’re in an in interesting era where cognitive science is successfully exploring its underlying neuronal circuitry. As is typical, the process is messy but the picture is getting filled out, even in some very tricky areas like working memory and perception.

It’s of little importance to my day job in drug development at this point, but these are the kinds of questions that sparked my interest in brain science at the beginning. So while I look on as a spectator, I’m spending time reading papers and developing at least a superficial understanding of the techniques and progress.

Building models to explore the unknown

Neuroscience Twitter is a great resource to keep up with trends across cognitive science. Case in point: I’m reading through Bayesian models of perception and action which is a draft of a book by Wei Ji Ma, Konrad Kording, and Daniel Goldreich, to be published by MIT press. I’ve been dipping into papers published by the three authors to get a feel for the deeper applications of the approach. I learned about it on Twitter

I think this is an important area to watch. I’ve talked about the idea that the brain, in order to control behavior, has to contain a model of the system. One approach is create computer models of circuitry based on observed connectivity and activity in animals when these systems are active. If some models can reproduce the brain activity, then they are candidates for hypothesized mechanisms and be used to make predictions about how the real neural circuits behave. Think about it like a physicist using equations to model physical laws and then testing the predictions from those equations against new observations. Except for the brain we don’t have any such equations, so we can use the immense computer power we have at our disposal to do the same kind of abstraction as the physicist.

Just like the equations of physics describe reality, but aren’t reality, these neural models describe little bits of the brain, they aren’t thinking. But interestingly, some of these brain inspired models can be put to work for real life tasks like image or speech recognition because the escape simple algorithmic approaches to analysis and classification.

It dawned on me yesterday, just like the developing “Creator Economy” we’re seeing the creation of the “Knowledge Worker Industry”.

A recent episode of Mac Power Users was full of the usual interesting workflow ideas and productivity hacks. But then it got real serious for me real fast.

You see, Sean McCabe for years has been using automation and workflow tools to improve his own productivity. Now he’s using it to gleefully industrialize knowledge work. His current company takes podcasts and videos and hacks them up to nice promo bites for social media. It’s the kind of work that takes some editing skill, editorial ability, and thought. If you can get that down to a process, an assembly line you have knowledge workers sitting in front of a screen doing industrial line work. Get an assignment, process it, send it down the line and get the next job on the line. It sounds so nerdy and innocent: Mac Power Users #613: The Future of Work, with Sean McCabe

David and Stephen talk with Sean McCabe about how he runs his businesses from what can only be described as a Mac battle station while stitching together macOS apps and several cloud services to be more productive.

But I can see how the productivity hack industry can be used to maximize the productivity of knowledge workers. And it brought to mind Cal Newport’s vision of a world without email. Rather than summarizing Cal’s latest book, here’s an interview where he makes the point: Cal Newport on an industrial revolution for office work

On Cal’s account, those opportunities are staring us in the face. Modern factories operated by top firms are structured with painstaking care and two centuries of accumulated experience to ensure staff can get the greatest amount possible done.

Our productivity grew 50x in the 20th century. Why? Because, the early 20th century is when we got really serious about process engineering. Like hey, wait a second. If we use an assembly line, we can build cars better. We really started to get serious about building things as a process we could get better and better at. And as he underscored, he’s like, 50x growth is almost inconceivably large.

I’m a highly paid knowledge worker because of my 40 plus year career in science, medicine and drug development. I work in a company that Cal thinks is a “hyperactive hive mind” when what it is a organization of shifting expert teams loosely tied together around the world by a combination of asynchronous (email, document sharing) and synchronous (Teams, Zoom, teleconferences) in which I leverage my knowledge by contributing in dozens of different ways every day.

This is how teams work. I understand that Cal, as an academic, wants to be left alone and leave the operational stuff to a theoretical knowledge industry. But I see that as a digital salt mine. Assembly line knowledge work like Sean’s company. Where creativity and improvisational problem solving go to die.

Just processing notes and blog posts has clarified some of my recent interests. In neuroscience, it’s issues of mapping, perceptual decisions and genetic influence on cognition. Then there’s fitness and workflow and some tech news discussion.

One of the functions this casual blogging has is providing a way for me to write in short form about some of the big ideas I have in the ODB manuscript. I spent some time editing the section on chaos, complexity and emergence. The subject is top of mind right now so I’ve been tending to link to related stories on the net. But I’m hoping that my brief descriptions here help to clarify my thinking and help the presentation I’m putting in the manuscript.

I’ve also been dipping into Twitter conversations a bit more often. Since Dave Rogers says it’s the Town Square of the internet. It seems to be a more comfortable place to be over the last few months.

If I can’t describe concepts of ecology and systems here or on twitter in a few lines, I doubt I’ll do much better in the long form manuscript. This clarifying of understanding by teaching goes back to the ancient world. This is often attributed to physicist Richard Feynman but Feynman actually described learning by synthesizing the essentials of subject in a notebook rather than reading a textbook. This is closer to Zettelkasten concept of synthesis than blogging to understanding. Hence, Zettelblogging to capture both the synthesis and the teaching.

Systems Theory is central to my approach to understanding decision making, whether looking at mental activity or brain function. Systems Theory shows us how uncertainty arises even in fully deterministic of systems. When cause and effect feedback on each other and small changes result in non-linear effects, the future behavior of a system becomes harder to predict just because linear correlation and simple cause and effect lose explanatory power.

More often than not, I look at complex systems through the filter of ecology. Ecology is the term we use for the study of interacting biological organisms and their habitat in the real world. But by analogy, this mode of thinking becomes useful in thinking about how or brains interact with other brains and the environment. And of course we like to think of technologies, like Apple products and services as being an ecosystem where users, devices and information interact in a system.

Ecologies, like the organisms that live in them, are generally resilient. If they weren’t they wouldn’t last long enough to recognize as ongoing, functioning systems. But that’s not to say that ecologies don’t change over time in response to external inputs or changes in the environment.

A nice example from Ed Yong, who’s writing I treasure. An ecology of whales, krill and the ocean floor. Introduce man and the ecology collapses. The system is hurt but not gone and it may be possible to restart.

To Save the Whales, Feed the Whales – The Atlantic

Just as many large mammals are known to do on land, the whales engineer the same ecosystems upon which they depend. They don’t just eat krill; they also create the conditions that allow krill to thrive.

That’s the key to ecologies. They are constructed and maintained by their participants- all the animals in the environment have to reach a stable balance to persist over time. With change, a new stable state may be reached if the system persists. It may be diminished or barely recognizable, but it changes until it comes to rest in some newest of relationships.

Yong understands ecology and evolution, making his writing rich and deep. By the way, that’s a pointer to the article where it appeared in the Atlantic, behind a paywall. I read his writing in the Apple ecosystem, in Apple News+. As an information source, to enrich my information environment, Apple provides a great service.

As and ecology, I can’t see how these paywalls and Substack subscriptions reach a long term stable state. We used to have newstands where you could dip into a copy of the Atlantic for a small price. You got to read the New Yorker or Readers Digest in the doctor or dentist’s waiting room. Sure, once you have a readership you can move behind a paywall. But once the NYT and Washington Post have aggregated all the readers behind their paywalls they become just another monopoly like Facebook, YouTube and Google.

Not a stable information ecosystem.

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By the way, I’m glad I read the Foundation Trilogy before starting the AppleTV series. They are very different works, related stories.

The Apple series is way more coherent and focused. They’ve collapsed lots of Asimov’s threads into a real fabric, but along the way has become so much more conventional modern SciFi than Azimov’s experimental imaginings that made less sense but were wilder with huge story gaps.

The Apple show introduces some of the fantasy elements that Asimov added only in the second book and amplified in the third. Just so you know, I can enjoy stories with mind reading and mind uploading, but I find it much more likely that antigravity and faster than light travel are possible than the possibility that neuronal networks can ever be instantiated in computers or that their activity can be read out externally. But all fiction requires suspension of disbelief.

One of the advantages of adopting casual blogging is that the blank paper fear is banished. I put the date or a topic at the top and simply write what comes to mind. It should be easy to write. Publishing should be frictionless. But hopefully that casual journaling is the first part of a bigger process.

#Why blog?

In a note about the Tinderbox Meetup he participated in, Dave Rogers on Nice Marmot discusses why he blogs

I don’t do this for an audience. I do it for myself. I have no idea how many people visit here. I looked at the logs once, can’t make head or tail of them. Can’t deny that it’s a pleasure whenever I learn that someone reads what I post here, but I don’t chase it.

I’m also writing primarily for my benefit and grateful to those like Dave who have been steady readers over the years. Do we write ourselves into existence on the internet?

The narrative voice is the point of view, the way in which the reader will hear and experience the story. The first-person point of view invites the reader to see the story through the author’s perspective. The narrative voice is a reflection of the writer’s personality, a reflection of who they are. The writer displays their voice in the way they tell their story, the words they use, the aspects they highlight, the feelings they describe. Through the writer’s voice, readers can experience an event in a unique way.

Imagining an audience provides meaning to the public act of writing. Even if no one reads, there’s an implied listener. There’s a sense of creating something bigger than the grind of day to day life in art.

For years Michelle Silver, a sociologist at the University of Toronto, studied doctors as they shifted from being on call to doing secondary work to eventually retiring. And she found that, at the end, they essentially fell off a cliff. One day they were respected and passionate, with a clear purpose. Then they were just normal people.

Tinderbox is a hypertext tool

In his post, Dave makes some points about how these meetups and videos may not be doing Tinderbox any favors. I tried to watch the first one on blogging and as Dave pointed out it was filled with editing HTML and long complex coding that was not at all useful to me. Some of Michael Becker’s first YouTube videos were somewhat introductory gave me some nice ideas about setting up and using Tinderbox. For the vast majority of users looking at the new crop of personal knowledge management apps like Obsidian, Craft and Notion, I think it makes Tinderbox look too intimidating and complex.

Michael looks at Tinderbox as a programming environment, I fear, not as a hypertext tool for notes. Mark Bernstein has written about the philosophy behind the tool over the years.

Mark has always emphasized “incremental formalization”, which means starting with the notes and letting the objects dictate the organization as you go along. Obviously a set of notes referencing academic literature is going to need some way of referencing those publications, but there are many ways to accomplish that and the approach could differ for different projects. This is from The Tinderbox Way:

Tinderbox is designed to help you write things down, find them, think about them, and share them. Tinderbox is an assistant. Its meant to help, to facilitate. Its not a methodology or a code. Its a way to write things down, link them up, and share them. Its a chisel, guided by your hand and your intelligence.

The other key feature of Tinderbox is that it’s built on a hypertext foundation, supporting multiple views into the notes. Not only are there note to note links, but text to text and note to text links. You can look at a set of notes as an outline or as a map.

As we’ve all recognized over the years, Tinderbox’s greatest weakness is that flexibility. The competing tools have clear affordances that show you how it is to be used. But the truth is that it really only takes a few hours of use to start down the road of note taking and incrementally building a structure to support workflow.

Right now, I’m in the process building a Zettelblogging Tinderbox. My use is different from anything I’ve done before because of the wide variety of topics I’ve been writing about here at ODB. The other difference is that I’m putting Tinderbox in the center of a processing flow where text flows from Drafts into DEVONthink and on to Tinderbox for summarizing. I’m surprised that I’m then moving my notes out of Tinderbox into Ulysses to become text again. It’s a chain, but each program is supporting a unique activity.

It’s important to summarize and synthesize. Otherwise you fall into the well known Collector’s Fallacy

But knowledge-building doesn’t work that way. And saving content into some archive doesn’t either. I’m guilty of this myself. Having used Evernote for a decade I was used to saving everything I wanted to remember into the tool. I sorted and curated, tagged, and sometimes even highlighted content. But I fell victim to the Collectors Fallacy. Because you collected something doesn’t mean you learned it or are able to explain it.

This is where the hypertext environment of Tinderbox excels for me.

A pet peeve of mine- the suggestion that an animal or an organization or any complex system can evolve to become better adapted.

I ran across this today in an otherwise interesting discussion of life beyond the earth’s environments:

SETI: Why extraterrestrial intelligence is more likely to be artificial than biological | Space

AI may even be able to evolve, creating better and better versions of itself on a faster-than-Darwinian timescale for billions of years. Organic human-level intelligence would then be just a brief interlude in our “human history” before the machines take over. So if alien intelligence had evolved similarly, we’d be most unlikely to “catch” it in the brief sliver of time when it was still embodied in biological form.

I’m interested in this question of whether what is called artificial general intelligence is possible and if so, what form would it take. What bothered me here was equating AI evolving with creating better versions of itself. That’s not evolution; that’s merely improvement.

There’s a real argument to be made that fundamentally an algorithmic process can’t get outside of itself to ever be better than it was originally programmed to be. As argued in this paper, there may be fundamental limits on artificial general intelligence as long as we try to create algorithms limited to a particular problem space

We show that it is impossible to predefine a list of such uses. Therefore, they cannot be treated algorithmically. This means that “AI agents” and organisms differ in their ability to leverage new affordances. Only organisms can do this. This implies that true AGI is not achievable in the current algorithmic frame of AI research. It also has important consequences for the theory of evolution. We argue that organismic agency is strictly required for truly open-ended evolution through radical emergence.

Real evolution in the natural world demonstrates, I think, that there’s no fundamental limit as long as we build in variation so that novel forms of the algorithm are tried and can be selected for against a real ecology independent of the algorithm.

So remember, evolution needs both pre-existing variation and selection of the best adapted variants. You can’t evolve, you can express differences that the world will choose from.

On the other hand, we can see this going on right now.

Ed Yong is one of our best working science writers. This article so clearly lays out how evolution occurs all the time, right before our eyes. The story is that there is a gene for brittle tusks being selected for in the population because tuskless elephants have a survival advantage in an ecology with ivory poachers.

African Elephants Evolved Tusklessness Amazingly Fast

Campbell-Staton’s team has “done a convincing job showing that the Gorongosa elephants have evolved in response to poaching,” Kiyoko Gotanda, an evolutionary biologist at Brock University, told me. Usually, evolution is a slow process, but it can proceed with blinding speed.

I’ll give Dr. Gotanda some leeway here because he said the elephants “have evolved” which is a passive construction, since obviously the elephants didn’t actually do anything to evolve. Well, actually what they had was a pre-existing genetic variation that caused loss of tusks. Had that gene not been there, no selection could have occurred. It’s the part of evolution often forgotten. Variation is extremely valuable to a species because it allows for very rapid adaptation to a changing ecology.

Interesting to see the range of responses to the Mark Zuckerberg’s announcement of his aspiration to build a virtual world. This is the best of the interviews I read. As far as I can tell the only achievement that Facebook has is it’s algorithm that stole social interaction from the distributed net and concentrated it in a walled garden. Contrast that with Apple or Microsoft’s or Google’s embodiment of a vision in shipped products evolved to meet the challenges of advancing technology. It seems to me that the Facebook founder knows his time on stage will draw to a close as his users age and his only move will be to acquire the next platform (Instagram, What’s App).

You have to be in awe of what Apple has become from Apple II to Mac to iPhone to iPad to Watch. Never inventing the future mind you, just iterating to create a better, more expensive, more profitable experience. And kudo’s to Microsoft to emerging from the PC era to the cloud, continuing to dominate business software. My company’s IT infrastructure is almost entirely built on Microsoft products from email to Teams to Sharepoint.

Tech visions don’t always fail, but they do turn out to take unexpected turns and end up in places you wouldn’t expect. I loved my Palm Pilot, never got along with the Blackberry I had for a couple of years, enjoyed the Newton, but preferred the Palm Pilot. But we ended up with iPhones in the end. And that’s been the end of the chain for a long time now. A glass slab.

You can talk all you want about the vision. The lesson of Deciding Better is that you have only the Now in which to act. You can’t bring about the future, you can only do things in the present. Of course, those actions make some futures more likely and others less likely or maybe even impossible. But you can’t will the future into reality. I’ve found that it’s a common illusion among CEOs actually. They get disconnected from the real work of creating in the now and start to believe that their vision is what has brought the current reality into being.

Wow me with the first step toward this future and I’ll believe. So far all I can tell the VR rigs are good for is playing Fruit Ninja in 3-D or taking calming immersive journeys. Sometimes I wonder whether Tim Cook’s frequent enthusiasms about augmented reality isn’t trolling competitors like Zuckerberg. But no, Apple has not only shipped “Spatial Audio”, they are using it and integrating it into daily use for music and conferencing. I’ve seen QR-coded exhibits where you can get an AR overlay for the phone. My car has a heads up display that alerts me to speed limit changes. These are real steps toward a future where there is more than our mind’s semantic tags on what we see, but an extension of what we can know spatially integrated into the world as we move through it.

As some one once said, “Real artists ship”

I’m not very interested in the Nikon Z9 announced today, way too much camera. But the NIKKOR Z 24-120mm f/4 lens is the Z mount version of my carry around lens I used for the D800 and D850 when I went full frame. That was a really nice lens after I sent it to Nikon for adjustment. I use the SL2 on occasion but it’s heavy and the primes I have are big and heavy. It only comes out for events, never travel.

Apple reported earnings today. For some reason I was looking at some information on the industrial side of computing like Wind River and other real time operating systems and it struck me how close Apple stays to its original vision and remains a consumer device company that sells a software, hardware and service package to consumers. Unique really. But with these latest generation SoCs, aren’t advanced robotics, intelligent control systems with visual input and other industrial uses in reach? All are like the automous vehicle market, but the prospective Apple Car is a consumer package. Seems like these chips would be very capable of doing much more, starting in robotics.

For the first time I’m dipping into dynamic web content. I’ve never edited my web posts, but I see maybe I should be updating and expanding earlier posts. Maybe not touching old blog posts is a philosophical line like cropping photos.

I was skeptical of using baking soda to polish scratched eyeglasses

Mix a couple of tablespoons of baking soda with a small amount of water to create a thick paste, Zavaleta says. Then grab a clean microfiber cloth (i.e. not the one you just used) and gently rub the solution onto the lenses.

My wife tried it and was really pleased with the result. I was told by a Zeiss microscope salesman many years ago to use a facial tissue and condensation from the breathe. The tissues are made to be very soft and non-abrasive and the condensation is close to distilled water. My glasses remain unscratched for my years. Also, I have them on from when I get up in the morning until I’m ready to sleep at night.

I dropped my Medium subscription. I used to follow links and get stopped by their paywall. Now Medium seems mostly clickbait. I have no substack subscriptions. I don’t think hiding behind a paywall based on internet fame is a sustainable business model.