Friday Thinking is a humble curation of my foraging in the digital environment. Choices are based on my own curiosity and that suggest we are in the midst of a change in the conditions of change - a phase-transition. That tomorrow will be radically unlike yesterday.
Many thanks to those who enjoy this. ☺
In the 21st Century curiosity is what skills the cat -
for life of skillful means .
Jobs are dying - Work is just beginning.
Work that engages our whole self becomes play that works.
The emerging world-of-connected-everything - digital environment -
computational ecology -
may still require humans as the consciousness of its own existence.
To see red - is to know other colors - without the ground of others - there is no figure - differences that make a defference.
‘There are times, ‘when I catch myself believing there is something which is separate from something else.’
“I'm not failing - I'm Learning"
Quellcrist Falconer - Altered Carbon
Content
Quotes:
Articles:
Manufacturing mRNA vaccines is surprisingly straightforward
Reactive, reproducible, collaborative: computational notebooks evolve
3D holographic head-up display could improve road safety
Move over CRISPR, the retrons are coming
Weird viral DNA spills secrets to biologists
A two-qubit engine powered by entanglement and local measurements
interventions to promote mathematical literacy among gamblers generally push the message that gamblers should unconditionally trust mathematics. But recall in the opening story that the philosopher didn’t actually trust what the mathematician said; she trusted mathematics, sure, but she didn’t trust it as applied in the context of the die roll. The problem for gamblers isn’t so much a lack of trust in mathematics as much as an incorrect application and interpretation. After all, the gambler did trust mathematics, she just misinterpreted it.
The limitations of mathematical counselling make sense when we recall that the mathematics of ‘real world’ events are far from pure numbers; rather, they take the form of descriptions, strategies, predictions and expectations, all mediated by language and meaning. By making a distinction between pure and applied mathematics, between truths that are necessary and those that are contingent, and noticing how often we mix mathematical and non-mathematical terms ourselves, we might steer ourselves on the right track to correct our cognitive distortions.
No single expert or guide can help us here. We need the combined wisdom of the mathematician, the philosopher and the psychological counsellor to help combat the forces that sustain problem gambling. Indeed, some of the associated cognitive distortions tap into genuine philosophical debates, such as over the meaning of randomness, something that’s uncontrolled and proceeds without any rules. Mathematicians and philosophers struggle to agree on a rigorous and universally accepted definition, despite the centrality of the concept to probability theory.
When we put abstract, formal mathematics in empirical situations such as games of chance, we ultimately rely on language to express newly inferred relations as truths. However, these ‘truths’ are no longer necessary truths; they depend on meanings, interpretations and context. As such, they’re contingent truths. If we’re too zealous in abstracting or idealising our empirical context, or if we poorly interpret the mathematical truths in the target domain, such modelling can lead to erroneous results. When this happens, it’s not pure mathematics that’s to blame, but the whole setup.
All of this shows that any application of mathematics is a balance between relevance and convenience – a choice, a refinement, and finally a cross-checking against the real world. All this relies as much on a mathematician’s or scientist’s intuition as it does on scientific or mathematical rigour.
All probability theory is grounded in the concept of infinity, yet all our gaming experiences are finite
Mathematics for gamblers
Take a soccer simulation where an AI figured out that if it kicked the ball out of bounds, the goalie would have to throw the ball in and leave the goal undefended. Or another simulation, where an AI figured out that instead of running, it could make itself tall enough to cross a distant finish line by falling over it. Or the robot vacuum cleaner that instead of learning to not bump into things, it learned to drive backwards, where there were no sensors telling it it was bumping into things. If there are problems, inconsistencies, or loopholes in the rules, and if those properties lead to an acceptable solution as defined by the rules, then AIs will find these hacks.
We can imagine equipping an AI with all of the world’s laws and regulations, plus all the world’s financial information in real time, plus anything else we think might be relevant; and then giving it the goal of “maximum profit.” My guess is that this isn’t very far off, and that the result will be all sorts of novel hacks.
When AIs Start Hacking
Anyone who studies public health knows the importance of qualitative factors. Even seemingly precise, quantitative figures, like the infamous R0 – describing the rate of spread of a pathogen – is heavily dependent on qualitative factors that you just can’t do math on. R0 doesn’t just depend on things like, “How many virus particles must you inhale before you are likely to become infected,” it depends every bit as much on things like “do people trust public health authorities enough to report their contacts after they are diagnosed with an infection?”
But mathematical models operate on quantitative elements. To do math on a qualitative measurement, you must first quantize it, assigning a numeric value to it. This is also a qualitative exercise, because “how much does this hurt?” or “how intense does this shade of blue appear to you?” or “how much do you trust the CDC?” are not questions with precise, deterministic answers.
Quantitative disciplines – physics, math, and (especially) computer science – make a pretense of objectivity. They make very precise measurements of everything that can be measured precisely, assign deceptively precise measurements to things that can’t be measured precisely, and jettison the rest on the grounds that you can’t do mathematical operations on it.
This is the quant’s version of the drunkard’s search for car-keys under the lamp-post: we can’t add, subtract, multiply or divide qualitative elements, so we just incinerate them, sweep up the dubious quantitative residue that remains, do math on that, and simply assert that nothing important was lost in the process.
Cory Doctorow: Qualia
The word ‘authenticity’ comes from the Greek authentes for ‘master’ or ‘one acting on his own authority’ (aut = self and hentes = making or working on/crafting). Importantly, it doesn’t mean ‘self-maker’ in the reflexive sense of one who makes himself, but one who makes or acts according to his own will – making from out of the self. And in crafting of our accord, we do actually actualise ourselves. We transform inner feelings into something real.
If we’re to be authentic, we should ironically and humbly acknowledge the limitations of our individual perspective and effort, without despairing at our limitations. We should embrace the necessarily fragmentary nature of our endeavours, and we should enrich our efforts by trying to inhabit those of others, including those who came before us. In this way, we do take some steps toward the absolute.
This ironic attitude allows us, like Socrates, to truly know that we don’t know, to be comfortable with our ignorance while pushing against its boundaries, and to temper our desire for wholeness with an authentic understanding of our limitations. From this perspective, the silence of the world doesn’t sound unreasonable at all.
Authenticity is a sham
This is vital information if we are going to create conditions not only for the current pandemic - but for the inevitable next ones. A strong signal of progress - if we also develop the right business - public infrastructure models for the whole world - the local is now global - making it local everywhere.
Manufacturing mRNA vaccines is surprisingly straightforward
The Gates Foundation convinced the Oxford team to do an exclusive deal with Astrazeneca. In support of this proposition, Gates argued that without a profit motive, the pharma giants would abandon human society and risk civilizational collapse.
Despite his cuddly reputation as a philanthropist, Gates has always pursued the ideology that the world should be guarded over by monopolist-kings, dependent on their largesse (guided by their superhuman judgment) for progress.
Some of the poorest, most populous countries on Earth have petitioned the WTO for a patent waiver to allow them to manufacture generic versions of vaccines. There’s enormous, global support for this, both from people who care about humanitarian causes and from people who just don’t want to die of a mutant strain incubated half a world away.
[Gates] and his foundation are peddling the lie that patents aren’t the reason that poor countries aren’t making their own vaccines — instead, they are simply not “developed” enough to do science (again, the world’s largest existing vaccine factories are in the Global South).
“Rapid development and deployment of high‐volume vaccines for pandemic response” (DOI: 10.1002.amp2.10060) is an open access, peer-reviewed paper in the American Institute of Chemical Engineers’ Journal of Advanced Manufacturing and Processing: https://aiche.onlinelibrary.wiley.com/doi/full/10.1002/amp2.10060
- New facilities will be 99–99.9% smaller than conventional vaccine facilities
- They will be 95–99.7% cheaper than conventional vaccine facilities
- You could use a single room in a conventional vaccine factory to make more vaccine doses of mRNA vaccines than the entire output of the rest of the factory
- New vaccines can be made 1,000% faster than previous vaccines
We have to remember that it will be impossible to have a single all-powerful AI - the digital environment is enabling a complex ecology of all manner of AI - with all the diversity that any other viable ecology produces.
When AIs Start Hacking
If you don’t have enough to worry about already, consider a world where AIs are hackers.
Hacking is as old as humanity. We are creative problem solvers. We exploit loopholes, manipulate systems, and strive for more influence, power, and wealth. To date, hacking has exclusively been a human activity. Not for long.
As I lay out in a report I just published, artificial intelligence will eventually find vulnerabilities in all sorts of social, economic, and political systems, and then exploit them at unprecedented speed, scale, and scope. After hacking humanity, AI systems will then hack other AI systems, and humans will be little more than collateral damage.
Okay, maybe this is a bit of hyperbole, but it requires no far-future science fiction technology. I’m not postulating an AI “singularity,” where the AI-learning feedback loop becomes so fast that it outstrips human understanding. I’m not assuming intelligent androids. I’m not assuming evil intent. Most of these hacks don’t even require major research breakthroughs in AI. They’re already happening. As AI gets more sophisticated, though, we often won’t even know it’s happening.
AIs don’t solve problems like humans do. They look at more types of solutions than us. They’ll go down complex paths that we haven’t considered. This can be an issue because of something called the explainability problem. Modern AI systems are essentially black boxes. Data goes in one end, and an answer comes out the other. It can be impossible to understand how the system reached its conclusion, even if you’re a programmer looking at the code.
This is a very good signal of the future of scientific publishing.
Reactive, reproducible, collaborative: computational notebooks evolve
A new breed of notebooks is taking data visualization and collaborative functionality to the next level, with spreadsheet simplicity.
This year marks ten years since the launch of the IPython Notebook. The open-source tool, now known as the Jupyter Notebook, has become an exceedingly popular piece of data-science kit, with millions of notebooks deposited to the GitHub code-sharing site.
Computational notebooks combine code, results, text and images in a single document, yielding what Stephen Wolfram, creator of the Mathematica software package, has called a “computational essay”. And whether written using Jupyter, Mathematica, RStudio or any other platform, researchers can use them for iterative data exploration, communication, teaching and more.
But computational notebooks can also be confusing and foster poor coding practices. And they are difficult to share, collaborate on and reproduce. A 2019 study found that just 24% of 863,878 publicly available Jupyter notebooks on GitHub could be successfully re-executed, and only 4% produced the same results
How long will it be before we see this as a standard feature in our vehicles? Will it be before self-driving vehicles?
3D holographic head-up display could improve road safety
Researchers have developed the first LiDAR-based augmented reality head-up display for use in vehicles. Tests on a prototype version of the technology suggest that it could improve road safety by 'seeing through' objects to alert of potential hazards without distracting the driver.
The technology, developed by researchers from the University of Cambridge, the University of Oxford and University College London (UCL), is based on LiDAR (light detection and ranging), and uses LiDAR data to create ultra high-definition holographic representations of road objects which are beamed directly to the driver's eyes, instead of 2D windscreen projections used in most head-up displays.
While the technology has not yet been tested in a car, early tests, based on data collected from a busy street in central London, showed that the holographic images appear in the driver's field of view according to their actual position, creating an augmented reality. This could be particularly useful where objects such as road signs are hidden by large trees or trucks, for example, allowing the driver to 'see through' visual obstructions. The results are reported in the journal Optics Express.
Another signal in the emerging toolbox of domesticated DNA.
"RLR enabled us to do something that's impossible to do with CRISPR: we randomly chopped up a bacterial genome, turned those genetic fragments into single-stranded DNA in situ, and used them to screen millions of sequences simultaneously, … RLR is a simpler, more flexible gene editing tool that can be used for highly multiplexed experiments, which eliminates the toxicity often observed with CRISPR and improves researchers' ability to explore mutations at the genome level."
"Being able to analyze pooled, barcoded mutant libraries with RLR enables millions of experiments to be performed simultaneously, allowing us to observe the effects of mutations across the genome, as well as how those mutations might interact with each other,"
Move over CRISPR, the retrons are coming
While the CRISPR-Cas9 gene editing system has become the poster child for innovation in synthetic biology, it has some major limitations. CRISPR-Cas9 can be programmed to find and cut specific pieces of DNA, but editing the DNA to create desired mutations requires tricking the cell into using a new piece of DNA to repair the break. This bait-and-switch can be complicated to orchestrate, and can even be toxic to cells because Cas9 often cuts unintended, off-target sites as well.
Alternative gene editing techniques called recombineering instead perform this bait-and-switch by introducing an alternate piece of DNA while a cell is replicating its genome, efficiently creating genetic mutations without breaking DNA. These methods are simple enough that they can be used in many cells at once to create complex pools of mutations for researchers to study. Figuring out what the effects of those mutations are, however, requires that each mutant be isolated, sequenced, and characterized: a time-consuming and impractical task.
Researchers at the Wyss Institute for Biologically Inspired Engineering at Harvard University and Harvard Medical School (HMS) have created a new gene editing tool called Retron Library Recombineering (RLR) that makes this task easier. RLR generates up to millions of mutations simultaneously, and "barcodes" mutant cells so that the entire pool can be screened at once, enabling massive amounts of data to be easily generated and analyzed. The achievement, which has been accomplished in bacterial cells, is described in a recent paper in PNAS.
There was some fear mongering a while back about an attempt to add two more letters to the basic genetic code - to create a synthetic DNA - as is often the case reality is stranger than our imagination.
The work is seminal, says Steven Benner, a synthetic biologist and founder of the Foundation for Applied Molecular Evolution in Alachua, Florida, who compares it to US microbiologist Carl Woese’s discovery of a new branch of single-celled life. “It represents the first discovery of a ‘shadow biosphere’ since Woese identified the Archaea a half century ago.”
Weird viral DNA spills secrets to biologists
Bacteria-infecting viruses have specialized enzymes to make genes with alternative nucleobase.
‘Alien’ genomes can be found on Earth. Some viruses that infect bacteria use an alternative genetic alphabet that’s distinct from the code used by nearly all other organisms — and, now, two teams have spelt out how the system works.
More than four decades in the making, the studies show how dozens of these bacteriophages (or just ‘phages’), as they are known, write their genomes using a chemical base called 2-aminoadenine, Z for short, instead of adenine — the A in the As, Ts, Cs and Gs of genetics textbooks.
“Scientists have long dreamed of increasing the diversity of bases. Our work shows that nature has already come up with a way to do that,” write Suwen Zhao, a computational biologist at ShanghaiTech University in China, and her team in a 29 April Science paper, showing how ‘Z-DNA’ is made. Researchers in France described similar insights in a pair of papers in the same journal.
It seems like the hydrogen economy is about to take off - again. But this time there’s a bigger tide of change to surf.
Burnaby's Ballard bets the day has finally come for technology Elon Musk called 'mind-bogglingly stupid'
After 40 years on the brink, Ballard Power, backed by heavyweights like Ford, Daimler and China's Weichai, may actually get its breakthrough
As chief executive of Burnaby-based Ballard Power Systems Inc., the company that hopes to disrupt trucking, municipal transit buses, railways and shipping with its proprietary hydrogen fuel cell technology, Randy MacEwen has made countless sacrifices.
A weak signal of something farther off - but conceptually fascinating.
A two-qubit engine powered by entanglement and local measurements
Researchers at Institut Néel-CNRS, University of Saint Louis and University of Rochester recently realized a two-qubit engine fueled by entanglement and local measurements. This engine's unique design, outlined in a paper published in Physical Review Letters, could open up exciting possibilities for thermodynamics research and inform the development of new quantum technologies.
"Our paper is based on a very simple and deep effect of quantum mechanics: Measuring a quantum system disturbs the system, i.e., changes its state in a random way," Alexia Auffèves, one of the researchers who carried out the study, told Phys.org. "As an immediate consequence, the measuring device provides both energy and entropy to the quantum system, playing a role similar to a hot source fueling a thermal engine. The noticeable difference is that here, the fuel is not thermal, but quantum."
A few years ago, Auffèves and some of her colleagues at Institut Néel-CNRS introduced the proof of concept for a measurement-fueled engine based on a single qubit. This was the first of a series of proposals that revealed the energetic counterpart of measurement devices.
Flagrant - Self-Promotion
I have two pieces to share - the first is a sprouting endeavor that will very soon enter into the access from the digital environment - Re-Imagining the Local
Re-imagining the Local
Response-Able action to the challenges of the 21st Century
Three paradigms enabling response-able action to the challenges of the 21st Century — where everything that can be automated will be.
And
There will never be a shortage of Work and Activity to Do and to Value — When we are Engaged in the enterprise of a Flourishing Life, Community and Ecology.
Paradigm One — Power of a nation with its own currency — Modern Monetary Theory.
Paradigm Two — Enabling a person to flourish as a citizen — Universal Basic Assets (UBA) and Guaranteed Job rather than unemployment insurance.
Paradigm Three — Enabling community to be response-able in a changing world — Asset-Based Community Development (ABCD).
And two - A cartoon of serious thinking - but here is my 10 page version of my epistemon-tology musings. It’s a 10 page narrative account of the opening ‘Motif’.
A Eulogy to Truth – Long Live Honesty
Motif
The truth is dead - long live honesty
Entailing honest accounts and holding accounts honest
Science teaches us skepticism -
Entailing multiple lines of evidence
For reliable knowledge
Complexity teaches us relative perspectives -
Entailing multiple ways of reasoning
For relevant wisdom
Collective wisdom emerges in our institutions of conversation
Entailing good faith speaker-hearers -
with honest accounting -
Entangling complex reasonings -
For adaptive evolving
We know what we know – but we don’t even know what we don’t know
#micopoem
watching bingetv -
partial attention syndrome -
meant I had to watch episodes -
many times -
something very compelling -
kept me on repeat to understand -
now on last episode -
major archetype becomes clear -
very brilliant -
unless it’s my own apophenia -
financism -
Failing to distinguish -
risk from uncertainty -
less a failing -
more a willing blindness -
denial enable by -
magical thinking alchemy -
of probability-incantations -
All probability theory is -
grounded in concept of infinity -
yet all our gaming experiences -
are finite -
George Ellis noted -
mathematics progresses -
to degree infinity is eliminated -
So probability -
a misdirection -
obfuscating infinity?
