Benchmarking!

“Sea level” is actually different everywhere, but in Britain, it remains a function, plus or minus, of ODN: Ordnance Datum Newlyn. This is the level measured within the town’s tidal observatory, constructed on the South Pier in 1915. The observatory takes the form of a hollow tower in which several floats are suspended, connected to a recording device. An inlet pipe allows the tower’s well to fill and empty with the Atlantic tides. Between 1915 and 2015 the mean sea level at Newlyn increased by 1.83 mm/year—and by 3.8 mm/year between 1993 and 2014. Each change in sea level is reflected in an incremental adjustment to elevations across the land. 

The last official benchmark was carved on a milestone located outside a pub in Loughton, Essex, in 1993, before satellite-based systems took over the datum (today, a GPS antenna sprouts from the top of the tide tower in Newlyn). The Ordnance Survey still maintains a record of over half a million benchmarks, although many more have disappeared. Hiking clubs lead expeditions to find them, and hobbyist benchmarkers check them off their lists. When you start looking for them, you see them everywhere.

“Benchmarking” remains in use today as a term for establishing a baseline against which other data can be measured and judged: software performance, product quality, profitability, growth; quality, time, cost. But it’s worth remembering its origins not as a tool for establishing hierarchies, but for leveling; for connecting, rather than separating; and for understanding the whole earth, and everything that happens upon it, as a continuous, indivisible field, stretched across cities, forests, and mountains, and ever susceptible to the rhythm of the tides.

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I actually studied AI at university, twenty years ago: exactly the wrong time, it turned out, to be studying it. The history of AI is one of booms and busts: “AI winters,” they were called, when the field seemed to sputter out after a series of advancements, and twenty years ago it was decidedly chilly. We learned about expert systems and neural networks from aging professors, but all the sensible students were learning about classical logic and statistics as preparation for careers in digital finance. It was another decade before the field would regain its energy, and—this is a controversial take—it would have little to do with conceptual breakthroughs. Rather, the growth of the internet, with its accompanying boom in processing capacity and data storage, would allow those same ideas—primarily neural networks—to be supercharged by graphics cards, digitized text and artworks, surveillance and social media, and the wholesale transference of everyday life to the online world. The AI “revolution,” if that’s what it is, is not a technological breakthrough, but the overwhelming accumulation of power and data in the hands of a few companies: power and data which rightfully belong to, and have been stolen from, everyone. But I digress.

I’d been noodling with this idea for some time: What if we used AI for something actually useful? It feels like we’re applying this new tool to all the wrong things: beating us at the games we enjoy, supercharging predatory capitalism, extracting and burning fossil fuels, depleting the planet’s resources, conflating images with art, encouraging extremism, suppressing rights, hallucinating, and so on and so forth. Wouldn’t it be infinitely more interesting if AI helped us do useful things in new and better ways, ways which we could not have imagined alone? Intelligences which we engaged with more like colleagues and collaborators than slaves and masters.

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The anarchist anthropologist David Graeber, may he rest in peace, had a good bit on authority. He said that anarchists don’t oppose authority per se, but they study and critique it, and appraise its legitimacy. What he liked, he said, was self-subverting authority, authority which undermines its own basis. He gave the example of a teacher: A teacher knows something useful to their student, and so they have a natural authority; but if they do their job well, at the end of the process the student knows what the teacher knows, and their authority is spent. The hierarchy is flattened, and no further unequal power can accrue. The student is changed, and so is the world.

Of course it’s possible to learn things from AI, but, for me, real intelligence resides not in an ability to extract and dominate, but in the capacity to share, co-exist, and thrive together. There are many ways of being intelligent, as many as there are living beings, each one unique and valuable. The real challenge of AI is not in building ever more powerful systems—this is difficult, but inevitable—the challenge is to find what relationships between different intelligences benefit us all. The challenge is to choose the kind of world we all want to inhabit. Benchmarking—the practical, embodied work of exploration and mediation—is an attempt to find our way towards such a world.

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Meta Value - 57

Humans do "xyz" while other animals cannot or do not 'xyz".

That is a lack of epistemic humility. Most times, we don't know shit about why and how we do "xyz" and we never even tried to "xyz" versions of other animals. 

I think this drives from the pleasure of being anthropocentric which cannot be easily derived without a benchmark. Other animals help create an artificial benchmark that sapiens long for albeit it always is pure fiction.

On the surface it looks harmless and mundane but this has caused immense pain and suffering for other animals. 

The value is don't make up artificial benchmarks, instead use the most beautiful sentence in english - "I don't know."

Humans do "xyz" while we have no idea about the other animals’ version of  'xyz".

Pressure

Wow! What a movie! 

I have said this for decades and this still holds true - the best AI models in the world then, and now are weather forecasting models. 

People don't have any appreciation nor gratitude for the people who work on these weather forecasts. 

Kay Summersby: "Did you know that weathermen are traditionally a little boring?"

James Stagg: "How dare you say that! Weathermen, maybe—but how can the weather be boring? It feeds us. The weather can destroy us. It controls our daily life. I don't think that's boring.

Happy B'day Neo !

Max's little baby is today 7!

You saved my life my love - for all the unfairness I dwelt in after Max, for all the deep depression I resided in...

With your adamance, hard headed-ness, naughtiness, and unfiltered independence - you didn’t give a fly fuck about where I dwelling in those dark days and you sucked me out of it. 

Thank you! You gave me so much and I hope, you feel the same way, 

I am and will be eternally grateful for you.

Happy B'day my love!

How Is Music Possible?

How is it possible for music to alter the world like this? It’s like when you take a scene from a horror movie and add funny music and the killer suddenly looks hilarious. Isn’t it strange that that happens? Why can we put certain sounds together that make the trees feel unfamiliar? Music is tones and rhythms in various mathematical relationships to each other—it is almost pure abstraction.2 Why should that move us? It is a realm of patterns largely independent of outside reality, and yet, when Maud closes her eyes, the music leads her somewhere, to some inner landscape.

How can these landscapes arise?

[---]

Experiencing music can give us the feeling that we are confronted with “the deepest recesses of our nature,” as Schopenhauer put it. His explanation for that feeling, by the way, was very different from the accounts I’ve given so far. He didn’t merely think music evoked emotions; he thought music and emotions were both evoking something, and evoking the same thing, something more fundamental than both. Let me give his theory as an example of how people have gone about attributing music to sources outside normal reality.

[---]

Now that I think about it, I suspect the reason I’m dissatisfied with all of the explanations of why music moves us comes down to this enormous distance between how simple the building blocks are and how far reaching their consequences.

I wonder if music is perhaps best thought of as an emergent phenomenon. It is built from small, mundane actions (plucking a string, manipulating our emotional processing, synchronizing our body movements with others to create a sense of bonding, and so on). But the thing that emerges (these swooping existential experiences) can’t be understood by just looking at the building blocks—much as the behavior of a sand dune can’t be understood by considering a single grain of sand. Sand dunes move around, larger ones more slowly than smaller ones, and when they collide, they exchange sand in various ways—none of which are properties that sand grains have.

New levels of emergence like this require their own concepts and explanations. And perhaps the vague, poetic language we reach for when talking about what music does to us—saying it feels like it “lifts us up” or “confronts us with a deeper reality,” and so on—is the best we can do when talking about the ever-evolving desert landscapes that arise, inexplicably, out of the simple-looking sand grains called notes.7 Perhaps I just have to accept that.

However that may be, it is astounding that we get to live in a universe where music is possible. Absolutely astounding.

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The Loneliness Of The Modern Self

So what can be done? Not everything, but something.

The answer probably does not lie in grand solutions or sentimental language about reconnecting. It lies in recovering forms of attention that modern life has made rare. A real conversation without hurry. A friendship that does not depend on performance. A commitment to fewer but deeper bonds. The ability to sit in silence without immediately reaching for distraction. The humility to let another person remain complex, opaque, and irreducible. The willingness to stay with a book, a piece of music, a walk, a sorrow, or a difficult thought long enough for it to change us.

These are small acts, but small acts are often where the human is either lost or saved. Modern life trains us to think scale is what matters: larger networks, wider visibility, more options, more access, more speed. But a soul is not repaired at scale. It is repaired through depth. Through repetition. Through fidelity. Through the slow rebuilding of the capacity to attend.

Maybe that is where hope begins: not in the fantasy of escaping modernity, but in resisting some of its most deforming habits. In refusing to treat every silence as empty, every pause as waste, every relationship as exchange, every self as brand. In relearning the difficult art of presence.

To be present is more demanding than it sounds. It means giving attention without immediate self-reference. It means listening without preparing a performance. It means staying long enough for the other person to become real beyond your use for them. It means inhabiting your own life rather than racing past it. Presence is not passive. It is one of the highest forms of discipline.

[---]

How do we begin again? Probably not all at once. Probably not dramatically. We begin by staying.

Staying in a conversation long enough for it to become real. Staying with a friend long enough to move past pleasantries. Staying with a grief long enough to understand what it is asking of us. Staying with ourselves long enough to hear a voice beneath the noise.

The loneliness of modern man is not simply that he has fewer people around him. It is that he has lost too many of the conditions under which presence becomes possible.

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Ten Men, One Summer: The Dartmouth Workshop of 1956 and the Naming of Artificial Intelligence

The story of legends who were humble and spearheaded innovation (rather than the current "business", non technical, marvel loving morons with no sense of common sense):  

The Conjecture

The document that named artificial intelligence opens with a single bold sentence: "The study is to proceed on the basis of the conjecture that every aspect of learning or any other feature of intelligence can in principle be so precisely described that a machine can be made to simulate it." Nobody in 1955 had established this conjecture. Nobody has established it since.

The document was a grant proposal, dated 31 August 1955 and submitted to the Rockefeller Foundation two days later. It asked for $13,500, ten participants, and two months at Dartmouth College in Hanover, New Hampshire. It introduced, for the first time in print, the phrase "artificial intelligence." The summer workshop it funded was smaller, shorter, and less conclusive than seventy years of retelling have suggested. Its name, however, has outlasted everything.

The Proposal

The proposal opened with its conjecture and then listed seven research problems: automatic computers and how to program them; how to make a computer use language; neuron nets; a theory of the size of calculations; self-improvement; abstraction; and randomness and creativity. The document did not say how anyone would know whether progress on any of these had been made. It said that significant advances were likely if a carefully chosen group worked together for a summer.

Of the four signatories, Shannon was by some distance the most famous scientist on the page: he had already founded information theory, was co-editing a volume with McCarthy, and had results in cryptography and the theory of Turing machines. Minsky, a Harvard Junior Fellow in mathematics and neurology, had built a machine for simulating learning by nerve nets and completed a Princeton PhD thesis entitled "Neural Nets and the Brain Model Problem." Rochester was Manager of Information Research at IBM, jointly responsible for the design of the IBM Type 701, who had also worked on simulation of nerve nets to test theories in neurophysiology. McCarthy, the youngest, was an assistant professor of mathematics at Dartmouth who had worked on Turing machines, the speed of computers, and the use of languages by machines. The contrast between Shannon's standing and McCarthy's juniority is worth holding in mind: the youngest and least established man in the room had picked the name and written the central conjecture.

[---]

What endured was not a research programme but a label and a concept. The name "artificial intelligence" gave a new field a clear identity distinct from cybernetics, from automata theory, from complex information processing. Departments could take the name, and did. Funding lines could adopt it, and did. Within two years, McCarthy and Minsky had started the MIT Artificial Intelligence Project; McCarthy later founded the Stanford AI Laboratory in 1962 and won the Turing Award in 1971; Newell and Simon won the 1975 Turing Award for the work that had its public debut in Hanover.40 Rochester's enthusiasm for Minsky's geometry-machine idea, taken back to IBM, set Herbert Gelernter working on a geometry theorem prover, with McCarthy as a consultant, and Gelernter presented a major paper on the result in 1959.41 None of this was the result of the summer's collective work. It was the result of those weeks of conversation, disagreement, and proximity. 

 

Meta Values - 56

The more you pursue feeling better all the time, the less satisfied you become. 

Pursuing something only reinforces the fact that you lack it in the first place.

That timeless wisdom was from Alan Watts and it is called "Backward Law".

I never knew this law but somehow it was instilled as part of everyday life for Max and I.

I don't even pursue peace as peace is a place Max and I live. 

There’s No Such Thing as a Natural Disaster

Written post Katrina in 2006 - lot of truth if you can try to filter out the ideology: 

It is generally accepted among environmental geographers that there is no such thing as a natural disaster. In every phase and aspect of a disaster—causes, vulnerability, preparedness, results and response, and reconstruction—the contours of disaster and the difference between who lives and who dies is to a greater or lesser extent a social calculus. Hurricane Katrina provides the most startling confirmation of that axiom. This is not simply an academic point but a practical one, and it has everything to do with how societies prepare for and absorb natural events and how they can or should reconstruct afterward. It is difficult, so soon on the heels of such an unnecessarily deadly disaster, to be discompassionate, but it is important in the heat of the moment to put social science to work as a counterweight to official attempts to relegate Katrina to the historical dustbin of inevitable “natural” disasters.

First, causes. The denial of the naturalness of disasters is in no way a denial of natural process. Earthquakes, tsunamis, blizzards, droughts, and hurricanes are certainly events of nature that require a knowledge of geophysics, physical geography, or climatology to comprehend. Whether a natural event is a disaster or not depends ultimately, however, on its location. A large earthquake in the Hindu Kush may spawn no disaster whatsoever while the same intensity event in California could be a catastrophe. But even among climatic events, natural causes are not entirely divorced from the social. The world has recently experienced dramatic warming, which scientists increasingly attribute to airborne emissions of carbon, and around the world Katrina is widely seen as evidence of socially induced climatic change. Much as a single hurricane such as Katrina, even when followed by an almost equally intense Hurricane Rita, or even when embedded in a record 2005 season of Atlantic hurricanes, is not in itself conclusive evidence of humanly induced global warming. Yet it would be irresponsible to ignore such signals. 

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Vulnerability, in turn, is highly differentiated; some people are much more vulnerable than others. Put bluntly, in many climates rich people tend to take the higher land leaving to the poor and working-class land more vulnerable to flooding and environmental pestilence. This is a trend, not an iron clad generalization: oceanfront property marks a major exception in many places, and Bolivia’s La Paz, where the wealthy live in the cooler valley below 13,000 feet, is another. In New Orleans, however, topographic gradients doubled as class and race gradients, and as the Katrina evacuation so tragically demonstrated, the better off had cars to get out, credit cards and bank accounts for emergency hotels and supplies, their immediate families likely had resources to support their evacuation, and the wealthier also had the insurance policies for rebuilding.

 

Trees As Public Health Infrastructure

For instance, city dwellers who live in neighborhoods with more trees (and often more resources) tend to have lower dementia risk and better heart and lung health, and are less likely to die prematurely as a result. Urban forests are also associated with cooler temperatures, cleaner air and water, and greater biodiversity. Yet until recently, few studies have measured the magnitude of these benefits in “health, deaths, or dollars,” says Colorado State University environmental epidemiologist David Rojas-Rueda.

Now, as Seattle and dozens of other cities across the United States work to expand their urban canopies, Rojas-Rueda and his collaborators have quantified the health and economic gains that cities could achieve if they actually meet their lofty goals. Seattle, for instance, is shooting to reach 30 percent tree cover (from its current 28 percent) by 2037. New York City aims to jump from 23 to 30 percent by 2040. Each city’s goal is unique, based on local ecology, climate, and other factors.

Hitting such targets, the researchers found, could collectively avoid more than 67,000 premature deaths across 144 cities, along with alleviating US $539 billion in economic burden from lives lost.

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