Written in collaboration with <a href="https://www.instagram.com/eddieblake_now/" target="_blank" rel="noreferrer noopener">Eddie Blake</a>.

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Written in collaboration with <a href="https://www.instagram.com/eddieblake_now/" target="_blank" rel="noreferrer noopener">Eddie Blake</a>.

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core/column

This essay was published as part of "Dixit Algorizmi – The Garden of Knowledge" the catalog of the Pavilion of the Republic of Uzbekistan at The Venice Biennale 2022. Dixit Algorizmi - The Garden of Knowledge&nbsp;is an ongoing exhibition and research project curated by&nbsp;<a href="http://www.spacecaviar.net" target="_blank" rel="noreferrer noopener">Space Caviar</a>&nbsp;and <a href="https://www.instagram.com/sheida_ghomashchi/" target="_blank" rel="noreferrer noopener">Sheida Ghomashchi</a>, reflecting on the history of technology and its relationship with contemporary artistic production.&nbsp;&nbsp;

This essay was published as part of "Dixit Algorizmi – The Garden of Knowledge" the catalog of the Pavilion of the Republic of Uzbekistan at The Venice Biennale 2022. Dixit Algorizmi - The Garden of Knowledge&nbsp;is an ongoing exhibition and research project curated by&nbsp;<a href="http://www.spacecaviar.net" target="_blank" rel="noreferrer noopener">Space Caviar</a>&nbsp;and <a href="https://www.instagram.com/sheida_ghomashchi/" target="_blank" rel="noreferrer noopener">Sheida Ghomashchi</a>, reflecting on the history of technology and its relationship with contemporary artistic production.&nbsp;&nbsp;

The full book is for sale here: <a href="https://www.humboldtbooks.com/en/book/dixit-algorizmi">https://www.humboldtbooks.com/en/book/dixit-algorizmi</a>

The full book is for sale here: <a href="https://www.humboldtbooks.com/en/book/dixit-algorizmi">https://www.humboldtbooks.com/en/book/dixit-algorizmi</a>

<div class="wp-block-column" style="flex-basis:50%">This essay was published as part of "Dixit Algorizmi – The Garden of Knowledge" the catalog of the Pavilion of the Republic of Uzbekistan at The Venice Biennale 2022. Dixit Algorizmi - The Garden of Knowledge&nbsp;is an ongoing exhibition and research project curated by&nbsp;<a href="http://www.spacecaviar.net" target="_blank" rel="noreferrer noopener">Space Caviar</a>&nbsp;and <a href="https://www.instagram.com/sheida_ghomashchi/" target="_blank" rel="noreferrer noopener">Sheida Ghomashchi</a>, reflecting on the history of technology and its relationship with contemporary artistic production.&nbsp;&nbsp;The full book is for sale here: <a href="https://www.humboldtbooks.com/en/book/dixit-algorizmi">https://www.humboldtbooks.com/en/book/dixit-algorizmi</a></div>

core/columns

<div class="wp-block-columns alignwide"><div class="wp-block-column" style="flex-basis:50%"><figure class="wp-block-image size-large"><img src="https://writing-api.burman.work/wp-content/uploads/2022/05/279628203_166385555799664_4064652710698118641_n-1024x1024.jpeg" alt="" class="wp-image-2553"/></figure></div><div class="wp-block-column" style="flex-basis:50%">This essay was published as part of "Dixit Algorizmi – The Garden of Knowledge" the catalog of the Pavilion of the Republic of Uzbekistan at The Venice Biennale 2022. Dixit Algorizmi - The Garden of Knowledge&nbsp;is an ongoing exhibition and research project curated by&nbsp;<a href="http://www.spacecaviar.net" target="_blank" rel="noreferrer noopener">Space Caviar</a>&nbsp;and <a href="https://www.instagram.com/sheida_ghomashchi/" target="_blank" rel="noreferrer noopener">Sheida Ghomashchi</a>, reflecting on the history of technology and its relationship with contemporary artistic production.&nbsp;&nbsp;The full book is for sale here: <a href="https://www.humboldtbooks.com/en/book/dixit-algorizmi">https://www.humboldtbooks.com/en/book/dixit-algorizmi</a></div></div>

Today, the map lies scattered across billions of data points—infinite subjective views on digital screens, all updating in real- time. Far from being a unifying, stabilising phenomenon as it once was, the map is now fractured. How did we get here, and what does this mean for our worldview?

Today, the map lies scattered across billions of data points—infinite subjective views on digital screens, all updating in real- time. Far from being a unifying, stabilising phenomenon as it once was, the map is now fractured. How did we get here, and what does this mean for our worldview?

Arguably, the trajectory that has led us to Uber and Google Maps started when al-Khwārizmī compiled Kitāb Sūrat al-Ard (The Book of the Description of the Earth), a book that encapsulated the whole known world into a single edition. Distilling something as complex as the world into a single book was, and still is, a dramatic feat of imaginative abstraction. In that process, the world had been reformed — the territory transposed onto the map. In this essay, we discuss what is so important about the map, how it has evolved, and the unnerving idea that whoever makes the map, also makes us.

Arguably, the trajectory that has led us to Uber and Google Maps started when al-Khwārizmī compiled Kitāb Sūrat al-Ard (The Book of the Description of the Earth), a book that encapsulated the whole known world into a single edition. Distilling something as complex as the world into a single book was, and still is, a dramatic feat of imaginative abstraction. In that process, the world had been reformed — the territory transposed onto the map. In this essay, we discuss what is so important about the map, how it has evolved, and the unnerving idea that whoever makes the map, also makes us.

The Book and al-Khwārizmī’s wider output were highly influential for generations of map-makers. In c. 830, he was a key figure in the production of the pioneering world map commissioned by caliph al-Ma’mūn. In the 11th century cartographical collection, The Book of Curiosities,<a href="#references">1</a> several maps appear to be largely based on al-Khwārizmī’s data tables. Similarly, al-Khwārizmī’s influential Zij — or collected volume of astronomical data — would also prove influential, being republished centuries after al-Khwārizmī’s death in the Toledan Tables, a key source for medieval astronomy.<a href="#references">2</a> What made al-Khwārizmī’s map-making influential wasn’t the visual representations, or even the visible graphics at all, but the way he calculated data and articulated new mathematical tools.<a href="#references">3</a> His contribution was the unseen infrastructure, the dark matter of coding, which underpins a map’s visual representation.

The Book and al-Khwārizmī’s wider output were highly influential for generations of map-makers. In c. 830, he was a key figure in the production of the pioneering world map commissioned by caliph al-Ma’mūn. In the 11th century cartographical collection, The Book of Curiosities,<a href="#references">1</a> several maps appear to be largely based on al-Khwārizmī’s data tables. Similarly, al-Khwārizmī’s influential Zij — or collected volume of astronomical data — would also prove influential, being republished centuries after al-Khwārizmī’s death in the Toledan Tables, a key source for medieval astronomy.<a href="#references">2</a> What made al-Khwārizmī’s map-making influential wasn’t the visual representations, or even the visible graphics at all, but the way he calculated data and articulated new mathematical tools.<a href="#references">3</a> His contribution was the unseen infrastructure, the dark matter of coding, which underpins a map’s visual representation.

<figure class="wp-block-image alignwide size-full"><img src="https://writing-api.burman.work/wp-content/uploads/2022/05/The-World-map-of-the-Caliph-al-Mamun-scaled.jpg" alt="" class="wp-image-2534"/><figcaption>“The World map of the Caliph al- Ma’mūn,” 833 Kitāb Masālik al-Absār by ibn Fadlallāh al-Umarī (d. 1349), MS 2797/1 Ahmet III Collection, Topkapı Sarayı Library, Istanbul</figcaption></figure>

Al-Khwārizmī’s expansion of spherical trigonometric techniques, in turn, enlarged the measurable world as foundational tools in mapping and projection for a millennium. Perhaps the foremost practical aspiration of his time was to find accurate calculations of Qibla:<a href="#references">4</a> the direction of Mecca. But the underlying logic of this practical applica- tion from the Middle Ages also lays the groundwork for the contemporary mathematical operations which underpin data processing within Geographic Information Systems (GIS) and more broadly across Geodesy.

Al-Khwārizmī’s expansion of spherical trigonometric techniques, in turn, enlarged the measurable world as foundational tools in mapping and projection for a millennium. Perhaps the foremost practical aspiration of his time was to find accurate calculations of Qibla:<a href="#references">4</a> the direction of Mecca. But the underlying logic of this practical applica- tion from the Middle Ages also lays the groundwork for the contemporary mathematical operations which underpin data processing within Geographic Information Systems (GIS) and more broadly across Geodesy.

Fluency with algebraic calculation, knowledge of gnomonics (the design of sundials), astronomy, and the astrolabe (the design of mechanical models of the universe) is what enabled al-Khwārizmī to compile such accurate data. Taken together, we may consider his prodigious output of mathematical knowledge an embryonic foray into the production of big data — from abstract foundational trigonometric values to astronomical data and cartographic locations. Such data would ultimately become the basis of how the world is ordered. In al-Khwārizmī’s work, we can see an early expression of the now commonplace powerful rela- tionship between reality, abstraction, and data.

Fluency with algebraic calculation, knowledge of gnomonics (the design of sundials), astronomy, and the astrolabe (the design of mechanical models of the universe) is what enabled al-Khwārizmī to compile such accurate data. Taken together, we may consider his prodigious output of mathematical knowledge an embryonic foray into the production of big data — from abstract foundational trigonometric values to astronomical data and cartographic locations. Such data would ultimately become the basis of how the world is ordered. In al-Khwārizmī’s work, we can see an early expression of the now commonplace powerful rela- tionship between reality, abstraction, and data.

While superficially neutral surveys of ground truth, maps are of course anything but ideologically passive. Architects and urban planners instinctively separate the idea of the map from the most fundamental tool in their work, the plan, but it may be more instructive to consider them as connected cousins. Understanding the differences between the map and the plan is not immediately obvious. In fact, they can be superficially indistinguishable. Both represent less than what is actually there, by distilling information and setting up a hierarchy of what is important or not. There is a difference of intent also: plans arepropositional, maps are descriptive. The map is a space in which we share the location of discovered objects. The plan reveals the order of things that have been or will be arranged.

While superficially neutral surveys of ground truth, maps are of course anything but ideologically passive. Architects and urban planners instinctively separate the idea of the map from the most fundamental tool in their work, the plan, but it may be more instructive to consider them as connected cousins. Understanding the differences between the map and the plan is not immediately obvious. In fact, they can be superficially indistinguishable. Both represent less than what is actually there, by distilling information and setting up a hierarchy of what is important or not. There is a difference of intent also: plans arepropositional, maps are descriptive. The map is a space in which we share the location of discovered objects. The plan reveals the order of things that have been or will be arranged.

Historically, map-makers refined the boundaries between what was known and what wasn’t. What existed outside — terra incognita — constituted a call to discovery and imagination. As far-flung cities entered geography, they became elements of military strategies and trade networks. All places were once uncharted space. The map makes room for the plan.

Historically, map-makers refined the boundaries between what was known and what wasn’t. What existed outside — terra incognita — constituted a call to discovery and imagination. As far-flung cities entered geography, they became elements of military strategies and trade networks. All places were once uncharted space. The map makes room for the plan.

A map is a series of symbolic gestures, a series of tricks and abstractions; scale, symbols, keys, orientation, all work to quickly communicate something unfathomably complex. These tricks work through a kind of map infrastructure, made up of projections, grids, and tabulated data. Yet, in the age of screens, we have another conceptual leap to make: resolution. It is the measure of an image, which quantifies how much information exists in a space. It is an estranged cousin of scale. When we can zoom and scroll, suddenly resolution becomes the key quality that allows us to see through the layers of representation and glimpse the data beneath. The higher the resolution, the closer to reality we get. But even at the highest resolution, the map doesn’t become the territory.

A map is a series of symbolic gestures, a series of tricks and abstractions; scale, symbols, keys, orientation, all work to quickly communicate something unfathomably complex. These tricks work through a kind of map infrastructure, made up of projections, grids, and tabulated data. Yet, in the age of screens, we have another conceptual leap to make: resolution. It is the measure of an image, which quantifies how much information exists in a space. It is an estranged cousin of scale. When we can zoom and scroll, suddenly resolution becomes the key quality that allows us to see through the layers of representation and glimpse the data beneath. The higher the resolution, the closer to reality we get. But even at the highest resolution, the map doesn’t become the territory.

Comparing ‘the map’ and ‘the territory’ is a philosophical issue as old as mapping itself. It is possible to forget that the elementary difference between the two is that ‘maps’ exist by virtue of a trick — by mathematical projection — abstracting the near-spherical earth into a two-dimensional geometry. This process is an example of the human capacity to abstract, simplify, and approximate. So, when we ask “who makes the map” we are also asking what kind of abstraction is taking place. Grids, coordinate systems, and projections do not physically exist out there in hard reality. They occur in the conceptual space of possi- bilities in which geographic knowledge exists.

Comparing ‘the map’ and ‘the territory’ is a philosophical issue as old as mapping itself. It is possible to forget that the elementary difference between the two is that ‘maps’ exist by virtue of a trick — by mathematical projection — abstracting the near-spherical earth into a two-dimensional geometry. This process is an example of the human capacity to abstract, simplify, and approximate. So, when we ask “who makes the map” we are also asking what kind of abstraction is taking place. Grids, coordinate systems, and projections do not physically exist out there in hard reality. They occur in the conceptual space of possi- bilities in which geographic knowledge exists.

<figure class="wp-block-image size-full"><a href="https://www.metmuseum.org/art/collection/search/457726" target="_blank" rel="noopener"><img src="https://writing-api.burman.work/wp-content/uploads/2022/05/main-image.jpeg" alt="" class="wp-image-2529"/></a><figcaption>Incomplete tile panel (ca. 1430), attributed to Damascus, Syria. Source: The Met</figcaption></figure>

In Islamic medieval maps, the earth is most commonly shown as a circle, sometimes an oval, only occasionally a rectangle.<a href="#references">5</a> The circle usually showed the poles reversed with the South at the top and represented a simplified projection of the single hemisphere that was believed to be inhabited. In this graphic construction, we can see what the map-makers’ contemporaries believed the world to be like, and perhaps what they wished the world to be like.

In Islamic medieval maps, the earth is most commonly shown as a circle, sometimes an oval, only occasionally a rectangle.<a href="#references">5</a> The circle usually showed the poles reversed with the South at the top and represented a simplified projection of the single hemisphere that was believed to be inhabited. In this graphic construction, we can see what the map-makers’ contemporaries believed the world to be like, and perhaps what they wished the world to be like.

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In The Book of the Description of the Earth, al-Khwārizmī expands directly from Ptolemy’s contributions to cartography and the original invention of the science of geography. The Geography of Ptolemy (and, in turn, al-Khwārizmī) locates objects and places in relation to the whole, across the unfolded surface of the planet, rather than with each other. Ptolemy also proposed several map projections, the most complete attempt to systematise the coordinates through which places might be located.<a href="#references">6</a>

In The Book of the Description of the Earth, al-Khwārizmī expands directly from Ptolemy’s contributions to cartography and the original invention of the science of geography. The Geography of Ptolemy (and, in turn, al-Khwārizmī) locates objects and places in relation to the whole, across the unfolded surface of the planet, rather than with each other. Ptolemy also proposed several map projections, the most complete attempt to systematise the coordinates through which places might be located.<a href="#references">6</a>

Geography, in its classical form, was the study of where things are relative to the greater planetary whole, rather than each other. For al-Khwārizmī, his map data could represent something akin to an objective grounded truth about the world, which could be continually refined and made more accurate. Any map, however, encodes a world view — co-locating the viewer and the observed — guiding the reader through a territory and, therefore, inscribing it. In turn, the map reshapes the represented territory.

Geography, in its classical form, was the study of where things are relative to the greater planetary whole, rather than each other. For al-Khwārizmī, his map data could represent something akin to an objective grounded truth about the world, which could be continually refined and made more accurate. Any map, however, encodes a world view — co-locating the viewer and the observed — guiding the reader through a territory and, therefore, inscribing it. In turn, the map reshapes the represented territory.

A feature of our contemporary world so comprehensively mapped is that there is no outside to the geographic boundary of knowledge. Instead, the focus of analysis is on charting all things and their interactions, all the time. The binary between mapped and unknown gives way to refresh rates and image analysis artefacts. When did we last scan how reliable is the algorithm? The 16-inch pixels of the GeoEye-1 satellites give way to the 1cm-per-pixel resolutions of real-time drone feeds and hungry laser-focused eyes of autonomous vehicles.

A feature of our contemporary world so comprehensively mapped is that there is no outside to the geographic boundary of knowledge. Instead, the focus of analysis is on charting all things and their interactions, all the time. The binary between mapped and unknown gives way to refresh rates and image analysis artefacts. When did we last scan how reliable is the algorithm? The 16-inch pixels of the GeoEye-1 satellites give way to the 1cm-per-pixel resolutions of real-time drone feeds and hungry laser-focused eyes of autonomous vehicles.

<figure class="wp-block-image size-full"><img src="https://writing-api.burman.work/wp-content/uploads/2022/05/Screenshot-2022-05-04-at-13.06.59.png" alt="" class="wp-image-2532"/><figcaption>Grid cell firing patterns; bird’s eye view. See Tor Stensola and Edvard I. Moser, “Grid Cells and Spatial Maps in Entorhinal Cortex and Hippocampus,” 2016</figcaption></figure>

<div class="wp-block-column" style="flex-basis:50%"><figure class="wp-block-image size-full"><img src="https://writing-api.burman.work/wp-content/uploads/2022/05/Screenshot-2022-05-04-at-13.06.59.png" alt="" class="wp-image-2532"/><figcaption>Grid cell firing patterns; bird’s eye view. See Tor Stensola and Edvard I. Moser, “Grid Cells and Spatial Maps in Entorhinal Cortex and Hippocampus,” 2016</figcaption></figure></div>

<figure class="wp-block-image size-full"><img src="https://writing-api.burman.work/wp-content/uploads/2022/05/Screenshot-2022-05-04-at-13.07.22.png" alt="" class="wp-image-2531"/><figcaption> A unified theory for the origin of grid cells through the lens of pattern formation, Ben Sorscher, Gabriel C. Mel, Surya Ganguli,Samuel A. Ocko. 2019, Advances in Neural Information Pro- cessing Systems 32 (NeurIPS 2019). Results of multi-grid pattern forming dynamics with nonnegativity constraint show regular hexagonal grids across multiple spatial scales</figcaption></figure>

<div class="wp-block-column" style="flex-basis:50%"><figure class="wp-block-image size-full"><img src="https://writing-api.burman.work/wp-content/uploads/2022/05/Screenshot-2022-05-04-at-13.07.22.png" alt="" class="wp-image-2531"/><figcaption> A unified theory for the origin of grid cells through the lens of pattern formation, Ben Sorscher, Gabriel C. Mel, Surya Ganguli,Samuel A. Ocko. 2019, Advances in Neural Information Pro- cessing Systems 32 (NeurIPS 2019). Results of multi-grid pattern forming dynamics with nonnegativity constraint show regular hexagonal grids across multiple spatial scales</figcaption></figure></div>

<div class="wp-block-columns alignwide"><div class="wp-block-column" style="flex-basis:50%"><figure class="wp-block-image size-full"><img src="https://writing-api.burman.work/wp-content/uploads/2022/05/Screenshot-2022-05-04-at-13.06.59.png" alt="" class="wp-image-2532"/><figcaption>Grid cell firing patterns; bird’s eye view. See Tor Stensola and Edvard I. Moser, “Grid Cells and Spatial Maps in Entorhinal Cortex and Hippocampus,” 2016</figcaption></figure></div><div class="wp-block-column" style="flex-basis:50%"><figure class="wp-block-image size-full"><img src="https://writing-api.burman.work/wp-content/uploads/2022/05/Screenshot-2022-05-04-at-13.07.22.png" alt="" class="wp-image-2531"/><figcaption> A unified theory for the origin of grid cells through the lens of pattern formation, Ben Sorscher, Gabriel C. Mel, Surya Ganguli,Samuel A. Ocko. 2019, Advances in Neural Information Pro- cessing Systems 32 (NeurIPS 2019). Results of multi-grid pattern forming dynamics with nonnegativity constraint show regular hexagonal grids across multiple spatial scales</figcaption></figure></div></div>

Contemporary neurobiology can shed light on this subject. How we conceive of space, increasingly appears to inform how memory and knowledge are structured in our brains. The rife spatial metaphors throughout language seem to stem from the map-like structures of memory.

Contemporary neurobiology can shed light on this subject. How we conceive of space, increasingly appears to inform how memory and knowledge are structured in our brains. The rife spatial metaphors throughout language seem to stem from the map-like structures of memory.

We can see this demonstrated in the physical neural mech- anisms at play in the most basic functions of perception such as neurons known as grid cells and place cells. These neurons, roughly speaking, allow us to orientate ourselves, and help us locate things respectively.<a href="#references">7</a> A core difference between these two neural architectures is that place cells encode specific objects and landmarks in relation to each other, while grid cells operate as a hexagonal coordinate system. Here, in the most basic unit of our cognition, is the basis for the map and the plan.

We can see this demonstrated in the physical neural mech- anisms at play in the most basic functions of perception such as neurons known as grid cells and place cells. These neurons, roughly speaking, allow us to orientate ourselves, and help us locate things respectively.<a href="#references">7</a> A core difference between these two neural architectures is that place cells encode specific objects and landmarks in relation to each other, while grid cells operate as a hexagonal coordinate system. Here, in the most basic unit of our cognition, is the basis for the map and the plan.

<figure class="wp-block-image size-full"><a href="https://h3geo.org"><img src="https://writing-api.burman.work/wp-content/uploads/2022/05/Screenshot-2022-05-04-at-13.06.52.png" alt="" class="wp-image-2533"/></a><figcaption>H3: Uber’s Hexagonal Hierarchical Spatial Index. Source: https://h3geo.org</figcaption></figure>

One might assume that al-Khwārizmī was familiar with the politics that enabled his scholarly pursuits. His work was underwritten by the patronage of the caliph and the House of Wisdom. The work was at the core of a top-down cultural and political programme to absorb and develop the knowledge of the Hellenistic world initiated by the caliphs, the so-called ‘translation movement.’ The maps not only encode a worldview, but project an idea of worldly power. No matter how abstract the field one works in, it is inevitably tethered back to the social reality of a political context. Today the equivalent of al-Khwārizmī’s work is being carried out by the software engineers and data-wranglers of planetary-scale platforms such as Uber.

One might assume that al-Khwārizmī was familiar with the politics that enabled his scholarly pursuits. His work was underwritten by the patronage of the caliph and the House of Wisdom. The work was at the core of a top-down cultural and political programme to absorb and develop the knowledge of the Hellenistic world initiated by the caliphs, the so-called ‘translation movement.’ The maps not only encode a worldview, but project an idea of worldly power. No matter how abstract the field one works in, it is inevitably tethered back to the social reality of a political context. Today the equivalent of al-Khwārizmī’s work is being carried out by the software engineers and data-wranglers of planetary-scale platforms such as Uber.

Alongside its core businesses, Uber has played a key role in the engineering of rapidly scalable data infrastructures. In the past few years, Uber has been broken and reformed by its own popularity. As user numbers exploded, the vast number of trips and locations flowing through the core technology meant that the infrastructure had to be rebuilt. The Uber app originally spawning from a single monolithic codebase was ‘rearchitected’ into a distributed system of robust ‘micro-services.’

Alongside its core businesses, Uber has played a key role in the engineering of rapidly scalable data infrastructures. In the past few years, Uber has been broken and reformed by its own popularity. As user numbers exploded, the vast number of trips and locations flowing through the core technology meant that the infrastructure had to be rebuilt. The Uber app originally spawning from a single monolithic codebase was ‘rearchitected’ into a distributed system of robust ‘micro-services.’

This was a daunting task given the scale of its operations, but one that has attracted many of the world’s most capable developers. One output has been H3,<a href="#references">8</a> a new approach to global mapping utilising nested hexagons (and pentagons) to form a universal grid system that scales for the entire earth without the exaggerated extremes of other cartographic projections.

This was a daunting task given the scale of its operations, but one that has attracted many of the world’s most capable developers. One output has been H3,<a href="#references">8</a> a new approach to global mapping utilising nested hexagons (and pentagons) to form a universal grid system that scales for the entire earth without the exaggerated extremes of other cartographic projections.

H3 is an example of a “discrete global grid system.”<a href="#references">9</a> Such grids are generated by “recursive tessellation” so that each scale or resolution of the grid is formed of nested smaller versions of the same pattern, allowing for theoretically infinite scaling while using grid elements of different sizes within the same mapping. So, for instance, a large empty region can occupy far less of the memory over-heads compared to a dense city. Hexagons (rather than squares) allow for a much faster computational addressability by storing every location with a single 64-bit integer, as opposed to longer and more computationally costly latitude and longitude. These hexagons also help compensate for a problem within urban data visualisation at the scale of street networks. The problem lies in using a square grid to distribute data coordinates when overlaid with cities built according to particularly strong grids. This problem gets worse if the grids nearly align.

H3 is an example of a “discrete global grid system.”<a href="#references">9</a> Such grids are generated by “recursive tessellation” so that each scale or resolution of the grid is formed of nested smaller versions of the same pattern, allowing for theoretically infinite scaling while using grid elements of different sizes within the same mapping. So, for instance, a large empty region can occupy far less of the memory over-heads compared to a dense city. Hexagons (rather than squares) allow for a much faster computational addressability by storing every location with a single 64-bit integer, as opposed to longer and more computationally costly latitude and longitude. These hexagons also help compensate for a problem within urban data visualisation at the scale of street networks. The problem lies in using a square grid to distribute data coordinates when overlaid with cities built according to particularly strong grids. This problem gets worse if the grids nearly align.

H3 anticipates a world where data production continues to explode, driven by an exponential growth in sensors and cameras required for automated vehicles. Crack open the boot of Uber’s last generation of experimental autonomous cars and you will find a colossal rig of CPUs, GPUs, and storage processing data points so numerous that wireless networks cannot currently provide the bandwidth to fully transmit them. This is the engine of the next cartography, underscored by machine intelligence.

H3 anticipates a world where data production continues to explode, driven by an exponential growth in sensors and cameras required for automated vehicles. Crack open the boot of Uber’s last generation of experimental autonomous cars and you will find a colossal rig of CPUs, GPUs, and storage processing data points so numerous that wireless networks cannot currently provide the bandwidth to fully transmit them. This is the engine of the next cartography, underscored by machine intelligence.

<figure class="wp-block-image size-full"><img src="https://writing-api.burman.work/wp-content/uploads/2022/05/Darb-i_Imam_shrine_spandrel.jpg" alt="" class="wp-image-2527"/><figcaption>Girih tile subdivision found in the decagonal girih pattern on a spandrel from the Darb-e Imam shrine in Isfahan. Source: <a href="https://commons.wikimedia.org/wiki/File:Darb-i_Imam_shrine_spandrel.JPG">Wiki Commons</a></figcaption></figure>

Uber’s mapping system&nbsp;—&nbsp;and even perhaps the images of our neural grid cells&nbsp;—&nbsp;are curiously reminiscent of the geometric patterns found within Islamic architecture. The earliest examples of this hexagon-based pattern first appeared towards the end of al-Khwārizmī’s life in 836 at the Great Mosque of Kairouan in Tunisia. It has been argued that the emergence of such patterns was influenced by the work of al-Khwārizmī and his contemporaries to reinterpret and expand upon the mathematics of Euclidean geometry,<a href="#references">10</a>&nbsp;especially within the context of Islamic cosmology. As such we might see maps (and the way they are constructed) as artefacts that allow us to glimpse some of the most fundamental workings of our minds. Understood in this way, maps are part of a cyclical cultural production, where they are both the product and the manufacturer of minds.

Uber’s mapping system&nbsp;—&nbsp;and even perhaps the images of our neural grid cells&nbsp;—&nbsp;are curiously reminiscent of the geometric patterns found within Islamic architecture. The earliest examples of this hexagon-based pattern first appeared towards the end of al-Khwārizmī’s life in 836 at the Great Mosque of Kairouan in Tunisia. It has been argued that the emergence of such patterns was influenced by the work of al-Khwārizmī and his contemporaries to reinterpret and expand upon the mathematics of Euclidean geometry,<a href="#references">10</a>&nbsp;especially within the context of Islamic cosmology. As such we might see maps (and the way they are constructed) as artefacts that allow us to glimpse some of the most fundamental workings of our minds. Understood in this way, maps are part of a cyclical cultural production, where they are both the product and the manufacturer of minds.

<figure class="wp-block-image size-full"><img src="https://writing-api.burman.work/wp-content/uploads/2022/05/main-image-2.jpeg" alt="" class="wp-image-2528"/><figcaption>Hexagonal pattern bottle, 9th–10th century, attributed to Iran. Source: <a href="https://www.metmuseum.org/art/collection/search/451716" target="_blank" rel="noreferrer noopener">The Met</a></figcaption></figure>

Our worldview can appear so stable and consistent with the facts as we perceive them, that it sometimes appears to be as unimpeachable as revealed truth. But by scratching the surface, we find that the underpinning of any worldview is a construct. Through grids, co-ordinate systems, projections, or tabulated data, we make maps that order, distil, and re-present the world, in turn, altering our perceptions of it. We live in an era when the construction and configuration of such knowledge are undergoing a revolution as dramatic as the original contributions of al-Khwārizmī. We are already feeling the tremors of this reconfiguration. We should pay attention to the construction of this knowledge, because whoever makes the maps, ultimately makes us.

Our worldview can appear so stable and consistent with the facts as we perceive them, that it sometimes appears to be as unimpeachable as revealed truth. But by scratching the surface, we find that the underpinning of any worldview is a construct. Through grids, co-ordinate systems, projections, or tabulated data, we make maps that order, distil, and re-present the world, in turn, altering our perceptions of it. We live in an era when the construction and configuration of such knowledge are undergoing a revolution as dramatic as the original contributions of al-Khwārizmī. We are already feeling the tremors of this reconfiguration. We should pay attention to the construction of this knowledge, because whoever makes the maps, ultimately makes us.

core/list

<ol><li>Yossef Rapoport, Emilie Savage- Smith,&nbsp;An Eleventh-Century Egyptian Guide to the Universe, The Book of Curiosities, Brill, 2014</li><li>Gerald J. Toomer, “Al-Khwarizmi” in Charles Coulston Gillispie (ed.),&nbsp;Dictionary of Scientific Biography, vol. 7, Gale Cengage, 1981</li><li>Ahmad ibn Yahya ibn Fadlallāh&nbsp;Encyclopedia of the History of Arabic&nbsp;al-Umarī, “The Mamunic World Map.”&nbsp;Science, vol. 1, Routledge, 1996. </li><li>Edward S. Kennedy, “Mathematical Geography,” in Roshdi Rashed (ed.),</li><li>Cyrus Alai, “Mapping the Mediterranean: By the Cartographers of Medieval Islamic Societies” in&nbsp;Journal of the International Map Collectors’</li><li>O.A.W. Dilke, “The Culmination of Greek Cartography in Ptolemy,” in J.B. Harley, David Woodward (eds.), The History of Cartography Volume 1:&nbsp;Press, 1987.&nbsp;Cartography in Prehistoric, Ancient, and Medieval Europe and the Mediterranean, The University of Chicago </li><li>Jordana Cepelewicz, “The Brain Maps Out Ideas and Memories Like Spaces” in&nbsp;Quanta Magazine, January 14, 2019.</li><li>Hexagonal Hierarchical Geospatial Indexing System 2018, <a href="http://h3geo.org" target="_blank" rel="noreferrer noopener">h3geo.org</a></li><li>OGC DGGS Standards Working Group <a href="http://www.ogc.org/projects/groups/dggsswg" target="_blank" rel="noreferrer noopener">www.ogc.org/projects/groups/dggsswg</a>.</li><li>Yahya Abdullahi, Mohamed pp. 243–251. Rashid Bin Embi, “Evolution of Islamic Geometric Patterns” in&nbsp;Frontiers of Architectural Research, 2013, vol. 2</li></ol>

0004 – It’s On Like Comic Con

0002 – The Content House

0003 – Who Makes The Map, Makes Us

Over the summer, a new state-of-the-art AI image generator, <a href="https://stability.ai/blog/stable-diffusion-public-release">Stable Diffusion</a> was released. Unlike its competitors which remain largely paywalled, it was made freely downloadable, smashing open a piñata of hype, panic and potential. Influential researcher (and former Director of AI at Tesla) Andrej Karpathy described it as ‘<a href="https://twitter.com/karpathy/status/1561818955966058500">a day of historic proportion for human creativity</a>'.

Over the summer, a new state-of-the-art AI image generator, <a href="https://stability.ai/blog/stable-diffusion-public-release">Stable Diffusion</a> was released. Unlike its competitors which remain largely paywalled, it was made freely downloadable, smashing open a piñata of hype, panic and potential. Influential researcher (and former Director of AI at Tesla) Andrej Karpathy described it as ‘<a href="https://twitter.com/karpathy/status/1561818955966058500">a day of historic proportion for human creativity</a>'.

With <a href="https://thesequence.substack.com/p/generative-ai-fundraising-momentum" target="_blank" rel="noreferrer noopener">investment dollars pouring in</a>, including a $101m for Stability.AI, the company behind Stable Diffusion, the field of "Generative AI" has quickly become this seasons venture capital unicorn ranch and nothing will ever be the same again, again.

With <a href="https://thesequence.substack.com/p/generative-ai-fundraising-momentum" target="_blank" rel="noreferrer noopener">investment dollars pouring in</a>, including a $101m for Stability.AI, the company behind Stable Diffusion, the field of "Generative AI" has quickly become this seasons venture capital unicorn ranch and nothing will ever be the same again, again.

I've been experimenting with Stable Diffusion since its release – see the numbered images in this post – and while contending with such intense buzz requires caution - also TLDR;  I don’t think I’ve ever used a piece of code or software that has left such an intense impression so quickly.

I've been experimenting with Stable Diffusion since its release – see the numbered images in this post – and while contending with such intense buzz requires caution - also TLDR; I don’t think I’ve ever used a piece of code or software that has left such an intense impression so quickly.

Stable Diffusion doesn't appear to be hugely more capable than its competitors MidJourney or Dall-E although the outputs it generates are generally more fascinating, especially in the terrain beyond style-transfer. Its primary advantage is that it's downloadable and free to operate on your own PC, providing space to both fine-tune it's process and to some extent reverse engineer its logic. As someone who spends a significant amount of time making and thinking about images - inputting my own images and drawings into Stable Diffusion has thrown up some knotty questions.

Stable Diffusion doesn't appear to be hugely more capable than its competitors MidJourney or Dall-E although the outputs it generates are generally more fascinating, especially in the terrain beyond style-transfer. Its primary advantage is that it's downloadable and free to operate on your own PC, providing space to both fine-tune it's process and to some extent reverse engineer its logic. As someone who spends a significant amount of time making and thinking about images - inputting my own images and drawings into Stable Diffusion has thrown up some knotty questions.

Before getting into these, the quickest shortcut through the hype might be just to try it for yourself and experience both its weirdness and limitations. There are many <a href="https://medium.com/geekculture/run-stable-diffusion-in-your-local-computer-heres-a-step-by-step-guide-af128397d424" target="_blank" rel="noreferrer noopener">guides</a>, <a href="https://www.howtogeek.com/830179/how-to-run-stable-diffusion-on-your-pc-to-generate-ai-images/" target="_blank" rel="noreferrer noopener">tutorials</a> and easy to use interfaces such as <a href="https://github.com/AUTOMATIC1111/stable-diffusion-webui">webui</a>, which is perhaps the most active and <a href="https://github.com/cmdr2/stable-diffusion-ui" target="_blank" rel="noreferrer noopener">stable-diffusion-ui</a>, which is possibly marginally easier to install. It can be used directly online at <a href="https://huggingface.co/spaces/stabilityai/stable-diffusion" target="_blank" rel="noreferrer noopener">huggingface</a> or dozens of other hosted version that have sprung up, although tinkering with a local installation provides the most flexibility.

Before getting into these, the quickest shortcut through the hype might be just to try it for yourself and experience both its weirdness and limitations. There are many <a href="https://medium.com/geekculture/run-stable-diffusion-in-your-local-computer-heres-a-step-by-step-guide-af128397d424" target="_blank" rel="noreferrer noopener">guides</a>, <a href="https://www.howtogeek.com/830179/how-to-run-stable-diffusion-on-your-pc-to-generate-ai-images/" target="_blank" rel="noreferrer noopener">tutorials</a> and easy to use interfaces such as <a href="https://github.com/AUTOMATIC1111/stable-diffusion-webui">webui</a>, which is perhaps the most active and <a href="https://github.com/cmdr2/stable-diffusion-ui" target="_blank" rel="noreferrer noopener">stable-diffusion-ui</a>, which is possibly marginally easier to install. It can be used directly online at <a href="https://huggingface.co/spaces/stabilityai/stable-diffusion" target="_blank" rel="noreferrer noopener">huggingface</a> or dozens of other hosted version that have sprung up, although tinkering with a local installation provides the most flexibility.

Sidestepping the tangled definitions of intelligence, we can at least recognise that such models are capable of extraordinary feats of translation, allowing us to skirt across vast dimensions of latent space and metaphorical image analysis that 150,000 hours of top grade GPU training time affords. We may not yet have sufficient metaphors to describe these interactions, landing somewhere between co-creation and augmented visual research made possible by ingesting 5.8 billion images. As a tool of self-evaluation it's remarkably useful to be able to supply it images and essentially ask 'what is this?' and then 'what it would be like as something slightly, or significantly, or entirely different?'. It's a process that feels conversational, and stranger still, one where the other party is adamantly attempting to convince you that images are not what you thought they were.

Sidestepping the tangled definitions of intelligence, we can at least recognise that such models are capable of extraordinary feats of translation, allowing us to skirt across vast dimensions of latent space and metaphorical image analysis that 150,000 hours of top grade GPU training time affords. We may not yet have sufficient metaphors to describe these interactions, landing somewhere between co-creation and augmented visual research made possible by ingesting 5.8 billion images. As a tool of self-evaluation it's remarkably useful to be able to supply it images and essentially ask 'what is this?' and then 'what it would be like as something slightly, or significantly, or entirely different?'. It's a process that feels conversational, and stranger still, one where the other party is adamantly attempting to convince you that images are not what you thought they were.

The term-of-art to describe the process of fine-tuning the inputs is known as ‘<a href="https://github.com/sw-yx/prompt-eng/blob/main/README.md">Prompt Engineering</a>’, although we may quickly need a more expansive term, that is less suggestive of a short, written starting points and more considerate of different potential input methods. How we feed such models is now encompassing all forms digital media - see emerging techniques for speech2video or text-to-3D aka <a href="https://dreamfusion3d.github.io">Dreamfusion</a>. Naturally some are already <a href="https://medium.com/mlearning-ai/using-an-ai-writer-to-generate-the-text-prompt-for-an-ai-image-generator-b331a6b94cdb" target="_blank" rel="noreferrer noopener">using one AI</a> to work out what to ask another.

The term-of-art to describe the process of fine-tuning the inputs is known as ‘<a href="https://github.com/sw-yx/prompt-eng/blob/main/README.md">Prompt Engineering</a>’, although we may quickly need a more expansive term, that is less suggestive of a short, written starting points and more considerate of different potential input methods. How we feed such models is now encompassing all forms digital media - see emerging techniques for speech2video or text-to-3D aka <a href="https://dreamfusion3d.github.io">Dreamfusion</a>. Naturally some are already <a href="https://medium.com/mlearning-ai/using-an-ai-writer-to-generate-the-text-prompt-for-an-ai-image-generator-b331a6b94cdb" target="_blank" rel="noreferrer noopener">using one AI</a> to work out what to ask another.

In a talk around a decade ago, I remember the artist <a href="https://markleckey.com">Mark Leckey</a> comparing image search engines to alchemy, since they could, if used effectively, conjure images from our imagination into being. In the era of “Big Data”, search could be considered be a productive, creative act.

In a talk around a decade ago, I remember the artist <a href="https://markleckey.com">Mark Leckey</a> comparing image search engines to alchemy, since they could, if used effectively, conjure images from our imagination into being. In the era of “Big Data”, search could be considered be a productive, creative act.

It was also an acknowledgement that, in a world where images are no longer scarce or hidden, how we work with them and what they mean might need to be fundamentally reconsidered.  As with many technologies, there is a window between our first interactions initial it and it’s maturity.  This same process feels like it’s happening with AI image generation, albeit slightly faster. I remember using Google Image Search not long after it was originally launched, it was both revelatory and yet also strangely limited. Before long it 'got good', and what once felt slightly unreliable, quickly cemented itself as an essential component of how we think about images.

It was also an acknowledgement that, in a world where images are no longer scarce or hidden, how we work with them and what they mean might need to be fundamentally reconsidered. As with many technologies, there is a window between our first interactions initial it and it’s maturity. This same process feels like it’s happening with AI image generation, albeit slightly faster. I remember using Google Image Search not long after it was originally launched, it was both revelatory and yet also strangely limited. Before long it 'got good', and what once felt slightly unreliable, quickly cemented itself as an essential component of how we think about images.

Emad Mostaque, CEO of&nbsp;<a href="http://stability.ai/" target="_blank" rel="noreferrer noopener">Stability.ai</a>&nbsp;describes using his model as&nbsp;‘<a href="https://www.youtube.com/watch?v=Snn4Pq5DBIo">generative search</a>’ – perhaps he was also in attendance at Leckeys lecture. He also predicts bombastically that<a href="https://twitter.com/EMostaque/status/1581669854720888832"> "image will be solved within a year</a>". Siri - set a reminder, 17th October, 2023. Hype train aside - it does seem likely that the underlying capacity of such technologies is going to keep growing in the near future. From the perspective of what they can already do, things are only going to get weirder.

Emad Mostaque, CEO of&nbsp;<a href="http://stability.ai/" target="_blank" rel="noreferrer noopener">Stability.ai</a>&nbsp;describes using his model as&nbsp;‘<a href="https://www.youtube.com/watch?v=Snn4Pq5DBIo">generative search</a>’ – perhaps he was also in attendance at Leckeys lecture. He also predicts bombastically that<a href="https://twitter.com/EMostaque/status/1581669854720888832"> "image will be solved within a year</a>". Siri - set a reminder, 17th October, 2023. Hype train aside - it does seem likely that the underlying capacity of such technologies is going to keep growing in the near future. From the perspective of what they can already do, things are only going to get weirder.

The crescendo of excitement surrounding Stable Diffusion is partly thanks to its public release. While the main competitor <a href="https://www.midjourney.com/home/" target="_blank" rel="noreferrer noopener">Midjourney</a> currently has 3 million members on its discord, that's primarily because chatting with a bot is the primary way to use use it. By decoupling the model from the service offering, Stability.AI has been propelled skyward by a community eager to to build things on top of the technology. This community is growing wildly fast and releasing a stream of visual tools and genre-bending proof-of-concepts, with new <a href="https://github.com/cobanov/awesome-diffusion">resources</a> available almost daily.

The crescendo of excitement surrounding Stable Diffusion is partly thanks to its public release. While the main competitor <a href="https://www.midjourney.com/home/" target="_blank" rel="noreferrer noopener">Midjourney</a> currently has 3 million members on its discord, that's primarily because chatting with a bot is the primary way to use use it. By decoupling the model from the service offering, Stability.AI has been propelled skyward by a community eager to to build things on top of the technology. This community is growing wildly fast and releasing a stream of visual tools and genre-bending proof-of-concepts, with new <a href="https://github.com/cobanov/awesome-diffusion">resources</a> available almost daily.

<figure class="wp-block-image size-large"><img src="https://writing-api.burman.work/wp-content/uploads/2022/10/image-1024x729.png" alt="" class="wp-image-3315"/><figcaption class="wp-element-caption">Graph comparing 'stars' on GitHub of the Stable Diffusion repo vs several other popular open source libraries (it's the vertical blue line on the right) via <a href="https://twitter.com/EMostaque">@EMostaque</a></figcaption></figure>

Nowhere is this more evidence that the rapid-fire demoscene of interfacial experiments, such as the <a href="https://www.youtube.com/watch?v=hkOF3_MIDOs">VR &amp; 360 Demos</a> by <a href="https://twitter.com/scottiefoxttv">ScottieFox</a>, and live AR demos by <a href="https://twitter.com/stspanho/status/1581707753747537920">Stijn </a><a href="https://twitter.com/stspanho/status/1581707753747537920" target="_blank" rel="noreferrer noopener">Spanhove</a> and <a href="https://twitter.com/sergeyglkn/status/1580167837770870784">Sergie Galkin</a>. Daniel Eckler has also compiled <a href="https://twitter.com/daniel_eckler/status/1572210382944538624" target="_blank" rel="noreferrer noopener">a fantastic thread</a>. For a general state of play, a good place to start is reddit: <a href="https://www.reddit.com/r/StableDiffusion/">r/StableDiffusion</a> and <a href="https://www.reddit.com/r/sdforall/">r/sdforall</a> or the <a href="https://discord.gg/stablediffusion">discord</a>. This outpouring of activity is the result to Stability.Ai's gamble to embrace an an alternative business model, helpfully summarised by swyx's "<a href="https://lspace.swyx.io/p/open-source-ai">How Open Source is eating A</a>I".

Nowhere is this more evidence that the rapid-fire demoscene of interfacial experiments, such as the <a href="https://www.youtube.com/watch?v=hkOF3_MIDOs">VR &amp; 360 Demos</a> by <a href="https://twitter.com/scottiefoxttv">ScottieFox</a>, and live AR demos by <a href="https://twitter.com/stspanho/status/1581707753747537920">Stijn </a><a href="https://twitter.com/stspanho/status/1581707753747537920" target="_blank" rel="noreferrer noopener">Spanhove</a> and <a href="https://twitter.com/sergeyglkn/status/1580167837770870784">Sergie Galkin</a>. Daniel Eckler has also compiled <a href="https://twitter.com/daniel_eckler/status/1572210382944538624" target="_blank" rel="noreferrer noopener">a fantastic thread</a>. For a general state of play, a good place to start is reddit: <a href="https://www.reddit.com/r/StableDiffusion/">r/StableDiffusion</a> and <a href="https://www.reddit.com/r/sdforall/">r/sdforall</a> or the <a href="https://discord.gg/stablediffusion">discord</a>. This outpouring of activity is the result to Stability.Ai's gamble to embrace an an alternative business model, helpfully summarised by swyx's "<a href="https://lspace.swyx.io/p/open-source-ai">How Open Source is eating A</a>I".

It's tempting humanise these tools, thinking of the model as somehow intuitive since its outputs can sometimes feel so unexpected, complex or perhaps even baffling. For now at least the very opposite is true, part of what makes it so interesting is that the latent space from which it pulls images is fully explorable - we can export an image for every step of the way or restart the process where we left off.

It's tempting humanise these tools, thinking of the model as somehow intuitive since its outputs can sometimes feel so unexpected, complex or perhaps even baffling. For now at least the very opposite is true, part of what makes it so interesting is that the latent space from which it pulls images is fully explorable - we can export an image for every step of the way or restart the process where we left off.

To such models, every image resembles a Monet painting or '<a href="https://mashable.com/article/werid-dall-e-images" target="_blank" rel="noreferrer noopener">A bottle of ranch testifying in court</a>', to some extent - it's just that most of the time it's 0.000%. To this end we can consider essentially all images, generated or otherwise as a bundle of definitions within Stable Diffusions <a href="https://jalammar.github.io/illustrated-stable-diffusion/" target="_blank" rel="noreferrer noopener">hyper-dimensional latent space</a>. To generate an image is to chart a logical (or absurd) route through the model, sampling the states of confusion and intrigue along the way, jiggling images from 0.041% of this to 0.98% of that.

To such models, every image resembles a Monet painting or '<a href="https://mashable.com/article/werid-dall-e-images" target="_blank" rel="noreferrer noopener">A bottle of ranch testifying in court</a>', to some extent - it's just that most of the time it's 0.000%. To this end we can consider essentially all images, generated or otherwise as a bundle of definitions within Stable Diffusions <a href="https://jalammar.github.io/illustrated-stable-diffusion/" target="_blank" rel="noreferrer noopener">hyper-dimensional latent space</a>. To generate an image is to chart a logical (or absurd) route through the model, sampling the states of confusion and intrigue along the way, jiggling images from 0.041% of this to 0.98% of that.

<div class="wp-block-column" style="flex-basis:50%"><figure class="wp-block-image size-large"><img src="https://writing-api.burman.work/wp-content/uploads/2022/10/diffusion-example-1024x757.png" alt="" class="wp-image-3217"/><figcaption class="wp-element-caption">&nbsp;An example of training a diffusion model for modeling a 2D swiss roll data. (Image source:&nbsp;<a href="https://arxiv.org/abs/1503.03585" target="_blank" rel="noreferrer noopener">Sohl-Dickstein et al., 2015</a>). - via What are Diffusion Models? by Lilian Weng </figcaption></figure></div>

<div class="wp-block-column" style="flex-basis:50%">Curiously the underlying technical <a href="https://lilianweng.github.io/posts/2021-07-11-diffusion-models/" target="_blank" rel="noreferrer noopener">architectures of diffusion models</a>, i.e Stable Diffusion, have their origins in thermodynamics. Authors on one of the early papers on the topic summarise it as: <a href="https://arxiv.org/abs/1503.03585">"The essential idea, inspired by non-equilibrium statistical physics, is to systematically and slowly destroy structure in a data distribution through an iterative forward diffusion process."</a> It turns out to be deliriously effective to train a neural network by adding and removing noise from an image in tiny iterations. We might even think of Stable Diffusion as essentially hyper-specialised noise reduction repeated dozens of times over. Generally the individual gradual steps along this path are nearly imperceptible to the human eye - in aggregate however the model can travel on what appears to be a wild ride of imagination.That doesn't mean we can directly parse it's reasoning. For instance the outputs can dramatically change form when it's underling parameters, such as 'de-noising' are only marginally adjusted, from say 0.875 to 0.9 as if crossing a threshold beyond which the model can no longer contain itself.</div>

<div class="wp-block-columns alignwide"><div class="wp-block-column" style="flex-basis:50%"><figure class="wp-block-image size-large"><img src="https://writing-api.burman.work/wp-content/uploads/2022/10/diffusion-example-1024x757.png" alt="" class="wp-image-3217"/><figcaption class="wp-element-caption">&nbsp;An example of training a diffusion model for modeling a 2D swiss roll data. (Image source:&nbsp;<a href="https://arxiv.org/abs/1503.03585" target="_blank" rel="noreferrer noopener">Sohl-Dickstein et al., 2015</a>). - via What are Diffusion Models? by Lilian Weng </figcaption></figure></div><div class="wp-block-column" style="flex-basis:50%">Curiously the underlying technical <a href="https://lilianweng.github.io/posts/2021-07-11-diffusion-models/" target="_blank" rel="noreferrer noopener">architectures of diffusion models</a>, i.e Stable Diffusion, have their origins in thermodynamics. Authors on one of the early papers on the topic summarise it as: <a href="https://arxiv.org/abs/1503.03585">"The essential idea, inspired by non-equilibrium statistical physics, is to systematically and slowly destroy structure in a data distribution through an iterative forward diffusion process."</a> It turns out to be deliriously effective to train a neural network by adding and removing noise from an image in tiny iterations. We might even think of Stable Diffusion as essentially hyper-specialised noise reduction repeated dozens of times over. Generally the individual gradual steps along this path are nearly imperceptible to the human eye - in aggregate however the model can travel on what appears to be a wild ride of imagination.That doesn't mean we can directly parse it's reasoning. For instance the outputs can dramatically change form when it's underling parameters, such as 'de-noising' are only marginally adjusted, from say 0.875 to 0.9 as if crossing a threshold beyond which the model can no longer contain itself.</div></div>

Stable Diffusion works because it is trained on 5.8 billion images but it's also appears fundamentally scarred by the process. It is common for images it generates to feature a hallucinated stock image watermark or 'garbled Getty images' banner. In her essay <a href="https://www.e-flux.com/journal/32/68260/the-spam-of-the-earth-withdrawal-from-representation/">'The Spam of the Earth: Withdrawal from Representation'</a> Hito Steyl reminds us that we have inadvertently flooded actual deep space with spam, "Image spam is our message to the future.". Now we’re filling our artificial brains with spam and stock image offcuts as well.

Stable Diffusion works because it is trained on 5.8 billion images but it's also appears fundamentally scarred by the process. It is common for images it generates to feature a hallucinated stock image watermark or 'garbled Getty images' banner. In her essay <a href="https://www.e-flux.com/journal/32/68260/the-spam-of-the-earth-withdrawal-from-representation/">'The Spam of the Earth: Withdrawal from Representation'</a> Hito Steyl reminds us that we have inadvertently flooded actual deep space with spam, "Image spam is our message to the future.". Now we’re filling our artificial brains with spam and stock image offcuts as well.

<figure class="wp-block-image size-full"><img src="https://writing-api.burman.work/wp-content/uploads/2022/10/spam-collage.png" alt="" class="wp-image-3226"/><figcaption class="wp-element-caption">Examples of watermarks and logos in images generated by Stable Diffusion (v1.5).</figcaption></figure>

However these issues may be trivial to bigger concerns now that a model with such power is out-in-the-wild. Stability.ai claim that the images are digitally watermarked, there are safeguards against NSFW content and mandate some fairly hefty licence restrictions. However judging by some of the community outputs this is almost impossible to regulate and potentially laying the groundwork for even more complex challenges.

However these issues may be trivial to bigger concerns now that a model with such power is out-in-the-wild. Stability.ai claim that the images are digitally watermarked, there are safeguards against NSFW content and mandate some fairly hefty licence restrictions. However judging by some of the community outputs this is almost impossible to regulate and potentially laying the groundwork for even more complex challenges.

Benjamin Bratton &amp; Blaise Aguera y Arcas, in their recent essay "<a href="https://www.noemamag.com/the-model-is-the-message" target="_blank" rel="noreferrer noopener">The Model Is The Message: Why We Need New Language For Artificial Intelligence</a> " partially in response to Google Engineer Blake Lemoines claim that the LaMDA chatbot might be '<a href="https://www.nytimes.com/2022/06/12/technology/google-chatbot-ai-blake-lemoine.html">sentient</a>', define "Seven Problems With Synthetic Language At Platform Scale". Two of these seven seem of immediate relevance to the release of Stable Diffusion - The Machine Majority Language Problem - what happens when the majority of language is spoken machine made? Then as a chaser – The Ouroboros Language Problem - what happens when the models are then trained on a corpus that was machine made?

Benjamin Bratton &amp; Blaise Aguera y Arcas, in their recent essay "<a href="https://www.noemamag.com/the-model-is-the-message" target="_blank" rel="noreferrer noopener">The Model Is The Message: Why We Need New Language For Artificial Intelligence</a> " partially in response to Google Engineer Blake Lemoines claim that the LaMDA chatbot might be '<a href="https://www.nytimes.com/2022/06/12/technology/google-chatbot-ai-blake-lemoine.html">sentient</a>', define "Seven Problems With Synthetic Language At Platform Scale". Two of these seven seem of immediate relevance to the release of Stable Diffusion - The Machine Majority Language Problem - what happens when the majority of language is spoken machine made? Then as a chaser – The Ouroboros Language Problem - what happens when the models are then trained on a corpus that was machine made?

<a href="https://www.stockphotosecrets.com/news/getty-images-shutterstock-ai-submission.html">Getty and Shutterstock have already banned AI generated images</a> given the sudden ease of being able to make them and the training pool for the next generation models is probably now already polluted. As Bratton and Aguera y Arcas observe, given the forthcoming onslaught of AI content, more radical approaches may be necessary, such as tagging content which is explicitly 'human made'.

<a href="https://www.stockphotosecrets.com/news/getty-images-shutterstock-ai-submission.html">Getty and Shutterstock have already banned AI generated images</a> given the sudden ease of being able to make them and the training pool for the next generation models is probably now already polluted. As Bratton and Aguera y Arcas observe, given the forthcoming onslaught of AI content, more radical approaches may be necessary, such as tagging content which is explicitly 'human made'.

Although their focus is on language processing models, the underlying logic is not only directly transferable to image generation, but really all machine learning approaches to media – as they write "the sequence modeling at the heart of natural language processing is key to enabling generalist AI models that can flexibly do arbitrary tasks, even ones that are not themselves linguistic, from image synthesis to drug discovery to robotics".

Although their focus is on language processing models, the underlying logic is not only directly transferable to image generation, but really all machine learning approaches to media – as they write "the sequence modeling at the heart of natural language processing is key to enabling generalist AI models that can flexibly do arbitrary tasks, even ones that are not themselves linguistic, from image synthesis to drug discovery to robotics".

While of course Stable Diffusion is largely manipulated with text-based prompts, the deeper consideration here is that linguistic capacity is the likely foundation for computational systems that can learn or build models of the world with a comparable speed, flexibility or inventiveness that even small children might display when picking up grammar, syntax and vocabulary. When it comes to machine learning, metaphor isn't a metaphor.

While of course Stable Diffusion is largely manipulated with text-based prompts, the deeper consideration here is that linguistic capacity is the likely foundation for computational systems that can learn or build models of the world with a comparable speed, flexibility or inventiveness that even small children might display when picking up grammar, syntax and vocabulary. When it comes to machine learning, metaphor isn't a metaphor.

So the commercial viability of libraries of stock images, game textures (and in time footage, copy-right free music) is perhaps shaky, but more fundamentally, but so to is the very nature of the 'stock' image. It's easy to forget such archives represent an industrialisation of visual communication, though the continuous production of generic images, vector graphics, symbols, logos and templates. What's changing is that the 'stock' is no longer a store but likely to become a process - the fruits of which will be strange. Adaptive illustrations that A/B test themselves, hyper-personalisation, deep instability.

So the commercial viability of libraries of stock images, game textures (and in time footage, copy-right free music) is perhaps shaky, but more fundamentally, but so to is the very nature of the 'stock' image. It's easy to forget such archives represent an industrialisation of visual communication, though the continuous production of generic images, vector graphics, symbols, logos and templates. What's changing is that the 'stock' is no longer a store but likely to become a process - the fruits of which will be strange. Adaptive illustrations that A/B test themselves, hyper-personalisation, deep instability.

It is only within the last few years that architectural visualisation and product photography has really got anywhere close to a level of 'true' photo-realism which might reasonably confuse experienced professionals, mainly because achieving the right level of complexity and textural variation that we are subconsciously rely on is extremely tedious or expensive. At the very least we can imagine that a commercial rendering pipelines are going to start including AI if only to sprinkle some of this magic realism dust at various stages of the pipeline.

It is only within the last few years that architectural visualisation and product photography has really got anywhere close to a level of 'true' photo-realism which might reasonably confuse experienced professionals, mainly because achieving the right level of complexity and textural variation that we are subconsciously rely on is extremely tedious or expensive. At the very least we can imagine that a commercial rendering pipelines are going to start including AI if only to sprinkle some of this magic realism dust at various stages of the pipeline.

<figure class="wp-block-image size-full"><img src="https://writing-api.burman.work/wp-content/uploads/2022/10/sd-0001.jpg" alt="" class="wp-image-3172"/><figcaption class="wp-element-caption"><a href="https://www.instagram.com/p/Cjlfg43Ib9x/" target="_blank" rel="noreferrer noopener">“#0001&nbsp;(geons, polished stones, building blocks, sheets of marble, film)”, 2022</a></figcaption></figure>

Stable Diffusion appears capable of generating a particular flavour of unreality. Given the right blend of inputs it will generate detail, form and lighting that reassure the human eye and appears to ‘know’ how to make something appear 3D or correctly textured while simultaneously making fundamental logical errors that we don't immediately acknowledge. While machine vision may be able to police machine image production, human labelling may soon be a thing of the past.

Stable Diffusion appears capable of generating a particular flavour of unreality. Given the right blend of inputs it will generate detail, form and lighting that reassure the human eye and appears to ‘know’ how to make something appear 3D or correctly textured while simultaneously making fundamental logical errors that we don't immediately acknowledge. While machine vision may be able to police machine image production, human labelling may soon be a thing of the past.

What this means for digital professional is a more complicated question. It's true that creative people who depend on a highly cultivated visual language may take a hit from unscrupulous actors if potential legal protections are fiddly to design or slow to be realised, but these may in time, also be easily addressable concerns to legislate for. To hold focus on the legal or economic side may gloss over the fundamental expansion and necessary reconstitution of what it means to be 'an artist' in the first place.

What this means for digital professional is a more complicated question. It's true that creative people who depend on a highly cultivated visual language may take a hit from unscrupulous actors if potential legal protections are fiddly to design or slow to be realised, but these may in time, also be easily addressable concerns to legislate for. To hold focus on the legal or economic side may gloss over the fundamental expansion and necessary reconstitution of what it means to be 'an artist' in the first place.

At a basic level, the premise that AI can independently make coherent art is essentially a boring category error, illustrating the somewhat reductive nature of conversations in mainstream and tech discourse, often based on the overestimation of the importance of 'style', as if visual art has remained static since Van Gogh chopped off his ear. While it may sound slightly obnoxious - it may also be literally true - that AI models and their creators might find a great advantage by somehow integrating lessons from art history and visual theory instead of presuming it can continue to be brute-forced a billion images 512px x 512px at a time.

At a basic level, the premise that AI can independently make coherent art is essentially a boring category error, illustrating the somewhat reductive nature of conversations in mainstream and tech discourse, often based on the overestimation of the importance of 'style', as if visual art has remained static since Van Gogh chopped off his ear. While it may sound slightly obnoxious - it may also be literally true - that AI models and their creators might find a great advantage by somehow integrating lessons from art history and visual theory instead of presuming it can continue to be brute-forced a billion images 512px x 512px at a time.

<h3>Stabilisation (And Its Discontents)</h3>

This isn't to make a value judgement about the different ways that people might use Stable Diffusion, quite the opposite, art is perhaps the primary process through which we as humans will build a cultural understanding of the computational structures that AI is revealing, and the wider the gamut of outputs, the better. As we shift from demo to tool it's likely that enhanced interfaces will provide a suite of richer interactions that may explicitly challenge us on this front, rather than defaulting to one-liner prompts, squashed into a HTML text input.

This isn't to make a value judgement about the different ways that people might use Stable Diffusion, quite the opposite, art is perhaps the primary process through which we as humans will build a cultural understanding of the computational structures that AI is revealing, and the wider the gamut of outputs, the better. As we shift from demo to tool it's likely that enhanced interfaces will provide a suite of richer interactions that may explicitly challenge us on this front, rather than defaulting to one-liner prompts, squashed into a HTML text input.

There is of course a whole separate debate to be had as to what it might mean for such a model to make art for itself or other machines, and even if we could realistically recognise it doing so. In the mean time it's a technology that will likely reveal more about ourselves, how we perceive the world and our emotional relationship to images, perhaps in time taking the the form of industrial-grade, cheaply available art therapy.

There is of course a whole separate debate to be had as to what it might mean for such a model to make art for itself or other machines, and even if we could realistically recognise it doing so. In the mean time it's a technology that will likely reveal more about ourselves, how we perceive the world and our emotional relationship to images, perhaps in time taking the the form of industrial-grade, cheaply available art therapy.

<div class="wp-block-column" style="flex-basis:50%">That the go-to nomenclature for such technologies is 'dream' i.e DeepDream, Dream Studio, Dream Fusion etc, may not be as trivial as it might first appears if in time such software performs a perceptual function similar to actual dreaming, albeit a little more on-demand.As with dreaming though, the process of AI image generation is generally speaking far more fascinating than any specific output. The most common audience responses usually concern method - 'how was that done?' and 'can I do it too?'.Very few AI images hold our attention in a meaningful way except perhaps those with a particular satirical resonance (see <a href="https://www.reddit.com/r/StableDiffusion/comments/x3u3r0/jeflon_zuckergates/" target="_blank" rel="noreferrer noopener">Jeflon Zuckergates</a>) which capitalise on Stable Diffusions dazzling capacity to seamlessly blend between numerous semantic concepts. </div>

<div class="wp-block-column" style="flex-basis:50%"><figure class="wp-block-image size-full"><img src="https://writing-api.burman.work/wp-content/uploads/2022/10/hdyw1o181el91.png" alt="" class="wp-image-3325"/><figcaption class="wp-element-caption"><a href="https://www.reddit.com/r/StableDiffusion/comments/x3u3r0/jeflon_zuckergates/" target="_blank" rel="noreferrer noopener">Jeflon Zuckergates - via reddit</a></figcaption></figure></div>

<div class="wp-block-columns alignwide"><div class="wp-block-column" style="flex-basis:50%">That the go-to nomenclature for such technologies is 'dream' i.e DeepDream, Dream Studio, Dream Fusion etc, may not be as trivial as it might first appears if in time such software performs a perceptual function similar to actual dreaming, albeit a little more on-demand.As with dreaming though, the process of AI image generation is generally speaking far more fascinating than any specific output. The most common audience responses usually concern method - 'how was that done?' and 'can I do it too?'.Very few AI images hold our attention in a meaningful way except perhaps those with a particular satirical resonance (see <a href="https://www.reddit.com/r/StableDiffusion/comments/x3u3r0/jeflon_zuckergates/" target="_blank" rel="noreferrer noopener">Jeflon Zuckergates</a>) which capitalise on Stable Diffusions dazzling capacity to seamlessly blend between numerous semantic concepts. </div><div class="wp-block-column" style="flex-basis:50%"><figure class="wp-block-image size-full"><img src="https://writing-api.burman.work/wp-content/uploads/2022/10/hdyw1o181el91.png" alt="" class="wp-image-3325"/><figcaption class="wp-element-caption"><a href="https://www.reddit.com/r/StableDiffusion/comments/x3u3r0/jeflon_zuckergates/" target="_blank" rel="noreferrer noopener">Jeflon Zuckergates - via reddit</a></figcaption></figure></div></div>

Reading through the pages of community generated add-ons already reveals the pathology of its current userbase to some extent - a blend of fantasy castles, cyberpunk streets, celebrity portraits, and of course endless, endless waifus. Beyond meme soup of X in the style of Y, lies a whole alphabet of image-based psychoanalysis.

Reading through the pages of community generated add-ons already reveals the pathology of its current userbase to some extent - a blend of fantasy castles, cyberpunk streets, celebrity portraits, and of course endless, endless waifus. Beyond meme soup of X in the style of Y, lies a whole alphabet of image-based psychoanalysis.

Indeed using Stable Diffusion has gradually unpicked and reassembled my own visual inclinations, distilling a mix of 70's conceptual sculpture, waste materials, geology and architectural formalism. For all the discussion about what it will mean for artists to have their work encoded into such models, it's also more than a little humbling to have an AI suggest that your images resemble an artist you thought you weren't obviously ripping off.

Indeed using Stable Diffusion has gradually unpicked and reassembled my own visual inclinations, distilling a mix of 70's conceptual sculpture, waste materials, geology and architectural formalism. For all the discussion about what it will mean for artists to have their work encoded into such models, it's also more than a little humbling to have an AI suggest that your images resemble an artist you thought you weren't obviously ripping off.

<div class="wp-block-column" style="flex-basis:50%"><figure class="wp-block-image size-full"><img src="https://writing-api.burman.work/wp-content/uploads/2022/10/0005img.png" alt="" class="wp-image-3174"/><figcaption class="wp-element-caption">“<a href="https://www.instagram.com/explore/tags/0005/">#0005</a>&nbsp;(prompt: ‘geological scrap paper, plaster, sculpture’)”, 2022</figcaption></figure></div>

<div class="wp-block-column" style="flex-basis:50%"><figure class="wp-block-image size-full"><img src="https://writing-api.burman.work/wp-content/uploads/2022/10/insty_08.png" alt="" class="wp-image-3178"/><figcaption class="wp-element-caption">#0008 &nbsp;(prompt: ‘blocks, concrete, brick’)”, 2022</figcaption></figure></div>

<div class="wp-block-columns alignfull"><div class="wp-block-column" style="flex-basis:50%"><figure class="wp-block-image size-full"><img src="https://writing-api.burman.work/wp-content/uploads/2022/10/0005img.png" alt="" class="wp-image-3174"/><figcaption class="wp-element-caption">“<a href="https://www.instagram.com/explore/tags/0005/">#0005</a>&nbsp;(prompt: ‘geological scrap paper, plaster, sculpture’)”, 2022</figcaption></figure></div><div class="wp-block-column" style="flex-basis:50%"><figure class="wp-block-image size-full"><img src="https://writing-api.burman.work/wp-content/uploads/2022/10/insty_08.png" alt="" class="wp-image-3178"/><figcaption class="wp-element-caption">#0008 &nbsp;(prompt: ‘blocks, concrete, brick’)”, 2022</figcaption></figure></div></div>

While it's astonishing that models like Stable Diffusion are capable of such outputs, they are still hyper-specialised only within a single domain, the question lingers about what happens as they start to become even slightly more general or perhaps even why they aren't already.

While it's astonishing that models like Stable Diffusion are capable of such outputs, they are still hyper-specialised only within a single domain, the question lingers about what happens as they start to become even slightly more general or perhaps even why they aren't already.

This concern is at the centre of Stanislas Dehaenes highly approachable '<a href="https://www.penguin.co.uk/authors/22843/stanislas-dehaene" target="_blank" rel="noreferrer noopener">How We Learn: The New Science of Education and the Brain'</a>, in which he compares the limit of current machine learning to the multi-layered, multi-sensory and social nature of human learning and it's surprising adaptability and robustness.

This concern is at the centre of Stanislas Dehaenes highly approachable '<a href="https://www.penguin.co.uk/authors/22843/stanislas-dehaene" target="_blank" rel="noreferrer noopener">How We Learn: The New Science of Education and the Brain'</a>, in which he compares the limit of current machine learning to the multi-layered, multi-sensory and social nature of human learning and it's surprising adaptability and robustness.

More recently the multi-author paper&nbsp;<a href="https://arxiv.org/abs/2210.08340">Toward Next-Generation Artificial Intelligence: Catalyzing the NeuroAI Revolution</a>&nbsp;is in essence a challenge to the wider AI research community to lean more fully into the study of Neuroscience and so-called ‘NeuroAI’, and to explore biological models that might radically improve the environmental interactions, flexibility and energy efficiency of AI. Certainly many in the field are betting on neuro-biologically inspired research to further reveal how to better design software intelligences while possibly helping us understand our own brains in the process.

More recently the multi-author paper&nbsp;<a href="https://arxiv.org/abs/2210.08340">Toward Next-Generation Artificial Intelligence: Catalyzing the NeuroAI Revolution</a>&nbsp;is in essence a challenge to the wider AI research community to lean more fully into the study of Neuroscience and so-called ‘NeuroAI’, and to explore biological models that might radically improve the environmental interactions, flexibility and energy efficiency of AI. Certainly many in the field are betting on neuro-biologically inspired research to further reveal how to better design software intelligences while possibly helping us understand our own brains in the process.

Among the authors is Jeff Hawkins, co-founder of Numenta (and formely co-founder of Palm Computing, originators of the PalmPilot) and author of the recent&nbsp;<a href="https://www.hachette.co.uk/titles/jeff-hawkins/a-thousand-brains/9781541675810/">A Thousand Brains: A New Theory of Intelligence</a>. The book is&nbsp;a cogent articulation of why AI needs neuroscience, based on two decades of research into the neocortex and it’s seemingly all-purpose role in high-level cognitive tasks - such as language. Emerging from this work are new theories of the organisation of the neocortex based on cortical&nbsp;columns and 'frames of reference', that might yet be one of the building blocks of neuro-inspired computational models.

Among the authors is Jeff Hawkins, co-founder of Numenta (and formely co-founder of Palm Computing, originators of the PalmPilot) and author of the recent&nbsp;<a href="https://www.hachette.co.uk/titles/jeff-hawkins/a-thousand-brains/9781541675810/">A Thousand Brains: A New Theory of Intelligence</a>. The book is&nbsp;a cogent articulation of why AI needs neuroscience, based on two decades of research into the neocortex and it’s seemingly all-purpose role in high-level cognitive tasks - such as language. Emerging from this work are new theories of the organisation of the neocortex based on cortical&nbsp;columns and 'frames of reference', that might yet be one of the building blocks of neuro-inspired computational models.

A key observation is that intelligence in biological systems is at least one or two orders of magnitude more efficient that current software approaches - implying there is still massive headroom in realising ever more powerful AI systems. It’s somewhat surprising perhaps that the artificial intelligence community maintains any distance from neuroscientific enquiry when so many of the active topics as, attention, episodic memory and of course neural networks themselves, are direct biological in origin.

A key observation is that intelligence in biological systems is at least one or two orders of magnitude more efficient that current software approaches - implying there is still massive headroom in realising ever more powerful AI systems. It’s somewhat surprising perhaps that the artificial intelligence community maintains any distance from neuroscientific enquiry when so many of the active topics as, attention, episodic memory and of course neural networks themselves, are direct biological in origin.

Of particular value are ‘sparse' networks, or ones with a minimal amount of connections is already appearing to have significant performance in real world applications, with a claimed improvement of 100x improvement in the "<a href="https://numenta.com/assets/pdf/research-publications/papers/Sparsity-Enables-100x-Performance-Acceleration-Deep-Learning-Networks.pdf" target="_blank" rel="noreferrer noopener">Performance Acceleration in Deep Learning Networks</a>”. As they write in their whitepaper: “How is the brain so intelligent with such amazing efficiency? One reason is that most of the neocortex is sparse. It stores and processes information in the context of extremely sparse neural activity and sparse connectivity.”

Of particular value are ‘sparse' networks, or ones with a minimal amount of connections is already appearing to have significant performance in real world applications, with a claimed improvement of 100x improvement in the "<a href="https://numenta.com/assets/pdf/research-publications/papers/Sparsity-Enables-100x-Performance-Acceleration-Deep-Learning-Networks.pdf" target="_blank" rel="noreferrer noopener">Performance Acceleration in Deep Learning Networks</a>”. As they write in their whitepaper: “How is the brain so intelligent with such amazing efficiency? One reason is that most of the neocortex is sparse. It stores and processes information in the context of extremely sparse neural activity and sparse connectivity.”

<figure class="wp-block-image size-full"><img src="https://writing-api.burman.work/wp-content/uploads/2022/11/0006-1024.png" alt="" class="wp-image-3328"/><figcaption class="wp-element-caption">‘<a href="https://www.instagram.com/explore/tags/0006/">#0006</a>&nbsp;(prompt: “industrial materials, studio photoshoot”)’, 2022</figcaption></figure>

Although this is only a single example, it demonstrates there is still plenty of room for step-change improvements in artificial intelligence. It's not just that models may become computationally more dazzling, but more nimble, easier to train, run and embed.

Although this is only a single example, it demonstrates there is still plenty of room for step-change improvements in artificial intelligence. It's not just that models may become computationally more dazzling, but more nimble, easier to train, run and embed.

Altogether it feels like we’re at an inflection point. On one hand Stable Diffusion demonstrates that open-sourcing AI models can ignite creativity around them - especially as media technologies - far more rapidly than the initial attempts to commercialise them as AI-as-a-service or a via APIs. Simultaneously, the underlying architectures are still a space of wild invention and likely to become ever more ‘untameable’. Now we’ve established Doom can indeed run on your <a href="https://www.pcmag.com/news/yes-doom-is-playable-on-a-pregnancy-test" target="_blank" rel="noreferrer noopener">pregnancy test</a> or <a href="https://www.youtube.com/watch?v=KFDlVgBMomQ" target="_blank" rel="noreferrer noopener">potato-powered TI-84 calculator</a>, or even <a href="https://www.youtube.com/watch?v=PW5ELKTivbE&amp;feature=emb_title" target="_blank" rel="noreferrer noopener">ATM</a>, perhaps the next question may be will they run Stable Diffusion and what happens when they do?

Altogether it feels like we’re at an inflection point. On one hand Stable Diffusion demonstrates that open-sourcing AI models can ignite creativity around them - especially as media technologies - far more rapidly than the initial attempts to commercialise them as AI-as-a-service or a via APIs. Simultaneously, the underlying architectures are still a space of wild invention and likely to become ever more ‘untameable’. Now we’ve established Doom can indeed run on your <a href="https://www.pcmag.com/news/yes-doom-is-playable-on-a-pregnancy-test" target="_blank" rel="noreferrer noopener">pregnancy test</a> or <a href="https://www.youtube.com/watch?v=KFDlVgBMomQ" target="_blank" rel="noreferrer noopener">potato-powered TI-84 calculator</a>, or even <a href="https://www.youtube.com/watch?v=PW5ELKTivbE&amp;feature=emb_title" target="_blank" rel="noreferrer noopener">ATM</a>, perhaps the next question may be will they run Stable Diffusion and what happens when they do?

0005 – Model Behaviour

In his 2012 <a href="http://archive.boston.com/ae/movies/articles/2012/04/29/the_avengers_collects_all_your_favorite_marvel_characters_in_one_handy_wannabe_blockbustersuper_groupthe_avengers_assembles_all_your_favorite_marvel_characters_in_one_handy_wannabe_blockbuster/">review</a> of the movie The Avengers, film critic of The Boston Globe, Tom Russo noted:

In his 2012 <a href="http://archive.boston.com/ae/movies/articles/2012/04/29/the_avengers_collects_all_your_favorite_marvel_characters_in_one_handy_wannabe_blockbustersuper_groupthe_avengers_assembles_all_your_favorite_marvel_characters_in_one_handy_wannabe_blockbuster/">review</a> of the movie The Avengers, film critic of The Boston Globe, Tom Russo noted:

core/quote

<blockquote class="wp-block-quote">The word “universe” is standard parlance in the comic book industry. [...] You don’t hear “universe” much in the film industry. Here in the real world — or Hollywood, at any rate — the prospect of mingling franchise characters is dauntingly complicated. &nbsp;Sure, we get a novelty such as “Alien vs. Predator” here and there, but rarely. Different studios hold rights to characters. Actors’ contracts can be tricky to coordinate — and so can their egos, one imagines.<cite>– <a href="http://archive.boston.com/ae/movies/articles/2012/04/29/the_avengers_collects_all_your_favorite_marvel_characters_in_one_handy_wannabe_blockbustersuper_groupthe_avengers_assembles_all_your_favorite_marvel_characters_in_one_handy_wannabe_blockbuster/">Super Group - 'The Avengers' assembles all your favorite Marvel characters in one handy wannabe blockbuster </a> </cite></blockquote>

The quote is a useful reminder that the era of the Big Comics crossover franchise, at least in cinema is barely a decade old.

The quote is a useful reminder that the era of the Big Comics crossover franchise, at least in cinema is barely a decade old.

Marvel's ambitious pace has been matched by staggering financial returns. Including the movies they used to strategically (re)introduce audiences to individual characters before The Avengers first assembled, the Marvel Cinematic Universe (MCU) is now a catalogue of 28 films, with a further 11 in development, all in just 15 years. A single franchise that has amassed billions of global fans and as of 2021 represents <a href="https://screenrant.com/marvel-movie-mcu-box-office-2021-details/" target="_blank" rel="noreferrer noopener">30% of all US box office revenue</a> and generated <a href="https://www.the-numbers.com/movies/franchises" target="_blank" rel="noreferrer noopener">$26.5B in global revenue since 2008</a>.

Marvel's ambitious pace has been matched by staggering financial returns. Including the movies they used to strategically (re)introduce audiences to individual characters before The Avengers first assembled, the Marvel Cinematic Universe (MCU) is now a catalogue of 28 films, with a further 11 in development, all in just 15 years. A single franchise that has amassed billions of global fans and as of 2021 represents <a href="https://screenrant.com/marvel-movie-mcu-box-office-2021-details/" target="_blank" rel="noreferrer noopener">30% of all US box office revenue</a> and generated <a href="https://www.the-numbers.com/movies/franchises" target="_blank" rel="noreferrer noopener">$26.5B in global revenue since 2008</a>.

<figure class="wp-block-image alignwide size-full"><img src="https://writing-api.burman.work/wp-content/uploads/2022/06/comicon-1-scaled.jpg" alt="" class="wp-image-2597"/><figcaption>The long and winding path in the first entrance hall.</figcaption></figure>

The methods, platforms and regularity with which we consume, or become consumed by, has also been changing at a dizzy pace during this time. Marvel, along with Harry Potter, DC, Star Wars, Lord of The Rings (to name just a few) are the juggernauts of IP,  speculative fictional universes that are inducing a new era of immersive fandom that is continuously reprocessed across every concievable contemporary media from film, books, comics, computer games, mobile apps, theme parks, trading cards, cosplay and seemingly unlimited avenues for merchandise or online social presence and communities.

The methods, platforms and regularity with which we consume, or become consumed by, has also been changing at a dizzy pace during this time. Marvel, along with Harry Potter, DC, Star Wars, Lord of The Rings (to name just a few) are the juggernauts of IP, speculative fictional universes that are inducing a new era of immersive fandom that is continuously reprocessed across every concievable contemporary media from film, books, comics, computer games, mobile apps, theme parks, trading cards, cosplay and seemingly unlimited avenues for merchandise or online social presence and communities.

The condition of fandom is by no means new, although the connective tissue of the digital age is allowing the entertainment and media companies controlling these franchise to offer the contemporary fan something altogether more boundless and integrated. Captivating oceans of glossy, social activated and deliciously addictive content. If "politics is downstream of culture", then fandom may very well be the melting glacier atop the mountain.

The condition of fandom is by no means new, although the connective tissue of the digital age is allowing the entertainment and media companies controlling these franchise to offer the contemporary fan something altogether more boundless and integrated. Captivating oceans of glossy, social activated and deliciously addictive content. If "politics is downstream of culture", then fandom may very well be the melting glacier atop the mountain.

What might be novel though is the scale and rich complexity that underpins the proposition of these 'universes', the result of decades of output by hundreds of authors and artists. Marvel films for instance can draw from a staggering diversity of story arcs and characters, given there are approximately approximately 27,000 comics in the series, so many in fact it is considered by some to be the largest continuous human narrative and it's speculated that only a handful of people, notably author Douglas Wolk and Marvel archivist Peter Sanderson and have read them all. The 4,868 pages that make up the Harry Potter books (including spin-offs) seems slight by comparison.

What might be novel though is the scale and rich complexity that underpins the proposition of these 'universes', the result of decades of output by hundreds of authors and artists. Marvel films for instance can draw from a staggering diversity of story arcs and characters, given there are approximately approximately 27,000 comics in the series, so many in fact it is considered by some to be the largest continuous human narrative and it's speculated that only a handful of people, notably author Douglas Wolk and Marvel archivist Peter Sanderson and have read them all. The 4,868 pages that make up the Harry Potter books (including spin-offs) seems slight by comparison.

This vastness enables a type of story-telling that can sustain countless spin-offs, callbacks, knowing references - interwoven narrative threads that might take a dozen movies to resolve, only to reappear in a video game demanding 100 hours of gameplay. A screenplay writer friend of mine once theorised that one of the major innovations of the crossover comic book film is that there is so little requirement for exposition that the movies can essentially begin with full tilt action, when in a more polite era of Hollywood the audience might expect to get at least 10 or 20 minutes to settle in.

This vastness enables a type of story-telling that can sustain countless spin-offs, callbacks, knowing references - interwoven narrative threads that might take a dozen movies to resolve, only to reappear in a video game demanding 100 hours of gameplay. A screenplay writer friend of mine once theorised that one of the major innovations of the crossover comic book film is that there is so little requirement for exposition that the movies can essentially begin with full tilt action, when in a more polite era of Hollywood the audience might expect to get at least 10 or 20 minutes to settle in.

Personally speaking however, I feel like I missed the bus altogether, despite being deeply curios my knowledge of comic books is very patchy, which is why I took the chance to go to Comic Con, or more fully Movie Comic Media (MCM) London Comic Con 2022 at The Excel Centre. The trip was anything but premeditated however - I had been travelling on London's new Elizabeth Line when the carriage was suddenly overwhelmed with Cosplay - when the (Marvel) universe gives you a sign, you better act on it.

Personally speaking however, I feel like I missed the bus altogether, despite being deeply curios my knowledge of comic books is very patchy, which is why I took the chance to go to Comic Con, or more fully Movie Comic Media (MCM) London Comic Con 2022 at The Excel Centre. The trip was anything but premeditated however - I had been travelling on London's new Elizabeth Line when the carriage was suddenly overwhelmed with Cosplay - when the (Marvel) universe gives you a sign, you better act on it.

The cradle of Comic Book conventions is Comic Con San Diego, first held in 1976, steadily growing to 13,000 visitors by 1990, before exploding in popularity and reaching 130,000 by 2010.  Whether Comic Con or Comicon or Comic-Con is a legal trademark has been a major legal battle. I incorrectly assumed it was all part of the same happy family, but Comic Con London is distinctly not commercially related to San Diego.

The cradle of Comic Book conventions is Comic Con San Diego, first held in 1976, steadily growing to 13,000 visitors by 1990, before exploding in popularity and reaching 130,000 by 2010. Whether Comic Con or Comicon or Comic-Con is a legal trademark has been a major legal battle. I incorrectly assumed it was all part of the same happy family, but Comic Con London is distinctly not commercially related to San Diego.

For all the observations that follow, and some of the overt cynicism I have for certain aspects of the industries involved -  almost everyone attending seemed to be having a contagiously fantastic time. Although precise numbers are hard to locate, The London Comic Con is one of, if not the largest convention held in the UK, frequently receiving upwards 130,000 visitors, rivalling Glastonbury in sheer numbers albeit requiring distinctly less investment of both time, money and exposure to the elements.

For all the observations that follow, and some of the overt cynicism I have for certain aspects of the industries involved - almost everyone attending seemed to be having a contagiously fantastic time. Although precise numbers are hard to locate, The London Comic Con is one of, if not the largest convention held in the UK, frequently receiving upwards 130,000 visitors, rivalling Glastonbury in sheer numbers albeit requiring distinctly less investment of both time, money and exposure to the elements.

While the fictional universes of comic books is the glue, the real show is of course the Cosplay. It's trite observation, but Cosplay obviously gives affords an experience out of the everyday, a cheat code to a different way of socialising. The atmosphere at Comic Con is far more electric than I anticipated, a tangible slightly nervous atmosphere of hyperactivity, neon energy drinks and imported Japanese sweets. The buzz also seems almost entirely be generated by attendees interacting with each other, a plasma of awkward but joyful high-fives, photo opportunities and sparks of recognition.

While the fictional universes of comic books is the glue, the real show is of course the Cosplay. It's trite observation, but Cosplay obviously gives affords an experience out of the everyday, a cheat code to a different way of socialising. The atmosphere at Comic Con is far more electric than I anticipated, a tangible slightly nervous atmosphere of hyperactivity, neon energy drinks and imported Japanese sweets. The buzz also seems almost entirely be generated by attendees interacting with each other, a plasma of awkward but joyful high-fives, photo opportunities and sparks of recognition.

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