Dmitri Cherniak is a Canadian artist based in New York. An engineer by education and trade, Cherniak sees the act of automation as a creative process. From the outside, art is regarded as highbrow and intellectual. Automation, however, is often perceived as rote and boring by those who are non-technical. Cherniak tries to bridge this gap by using software to automate the generation of unique art pieces that aim to elicit the same emotions and reactions that viewers feel when viewing art that has been “generated” by hand.
Jeff Davis: Hi Dmitri, it’s great to speak with you and learn more about your creative practice. How did you first get into making art?
Dmitri Cherniak: I have always been interested in making art, and as a kid was a prolific doodler and illustrator. In fact, I still get messages from my Dad telling me that my latest pieces remind him of pictures I drew when I was young. Despite that interest, my aptitude and curiosity for STEM classes eventually pulled me away from pursuing any kind of serious formal arts education, which is something I regret to this day.
JD: So what caused you to revisit the concept of artmaking with your technical background?
DC: In 2010 for a university course in AI, our yearlong project was to create a player for a variant of the game “Go.” At the time the game was dominated by human players, but now masters of Go are completely trampled by Alpha Go. I made a player called “Taylor Swift” and after she defeated her opponent, I wanted them to see a picture of her blowing them a kiss. Because all of the tournament game play was text based and written to logs, I built a system to generate Taylor Swift ASCII art so that whenever anyone would go over their logs to see how they got beaten so badly they would also see her blowing them a kiss in the console. In addition, I made a stylized cover image for the term paper that used a grayscale color palette that made me realize how much depth I could achieve in ASCII art portraiture. Five years later, in 2015, I posted the image online and it really resonated with my friends, around 10 people messaged me asking to buy it within the hour. At that point I knew I was on to something.
JD: That’s really interesting. What was your transition then into NFTs / crypto art?
DC: I’ve been fortunate enough to have been exposed to cryptocurrency and blockchains for a while. At my first solo show in San Francisco, the curator I worked with thought it would be cheeky if we allowed collectors to purchase art with Bitcoin. It turns out one of the founders of Coinbase stopped by and purchased one of my prints using BTC. Looking back, it might have been the best art business decision ever made considering the exchange rate of BTC at the time. The first NFT I ever minted was in 2019 for Jake Brukhman on OpenSea. He really pushed me to consider minting an NFT alongside the physical print that hangs in his apartment today.
JD: How do you think your creative practice has changed since then?
DC: At first, I was happy to just make one-off unique prints from an algorithm with unstructured code that wasn’t backed up, but over time I’ve focused on using good engineering discipline and hygiene to make aspects of the art more easily customizable, make my code more reusable, and reproduce any work I’ve generated previously. Not only does this make it easier to make new work, but it also helps me develop a “style” in generative art. Since we don’t get the benefit of having a distinct brush stroke in generative art, the code and configuration we decide to reuse helps us define our own distinct styles.
JD: Any recent accomplishments you’d like to share?
DC: This was a strange year as almost all events and commissions got cancelled, but some highlights include my artwork being shown on the big screens in Shibuya (The Times Square of Tokyo), being included in the Official “Virtual” New Year’s Eve Art Gallery in Times Square, and a collaboration between myself and renowned GAN artist Helena Sarin being made into an art book called Gen 2 GAN. We used my generative art algorithms to create a dataset for a machine learning pipeline tended to and curated by Sarin which yielded amazing results.
JD: OK, so let’s talk Art Blocks. What was the inspiration for Ringers?
DC: One of the things that really excites me about Art Blocks is that it feels like a breakthrough for my creative practice. Instead of focusing on selling a single output that I want to share, I can share the whole algorithm and collectors can appreciate a distinct set of the outputs.
The inspiration for Ringers came from taking a looped string and wrapping/weaving it around a set of circular pegs sampled from a two dimensional grid in a way that there are no intersections. Visually when you see it it’s rather intuitive and you might be able to draw a few instances by hand, which is something I often do. From a code and numerical perspective, it’s much more complicated to get right. You need to sample positions from the grid, sort them in a way such that the lines don’t intersect (I do this by doing an angular sort around the centroid of the sampled pegs), calculate the set of lines that are tangent between each peg/circle based on position and radius, then you need to calculate the arc curves around each peg taking note of which way around the peg the path would need to follow and compensating for that. It involves a bit of geometry, a bit of problem solving, and a number of steps that individually don’t feel intuitive compared to the visual system at all.
JD: What should collectors look for in your Art Blocks project as the series is revealed?
DC: I think they should be aware that it’s a form that I have been working with over a number of years and what they are seeing on Art Blocks is a culmination of insights into the form. If they want to know what to expect from the algorithm’s output, I recommend looking at my social media and observing the development of new features over time.
JD: Anything else people should know to better understand your art?
DC: I like to say that automation is my artistic medium. I think it’s important to understand that though I build and design the system in which the art is created, the actual output is not something I have much of an explicit say in. I often joke that the computer is in fact the artist. I will always downplay the role of the artist in my work and I’ve noticed it pisses off a lot of other artists who make algorithmic work. At the end of the day, I take in inputs, fiddle around with parameters, and then leave you with a system that produces output.
JD: Great stuff Dmitri! What’s the best way for people to follow your work?
DC: I post frequently on Twitter and Instagram.
Dmitri Cherniak is a Canadian artist based in New York. An engineer by education and trade, Cherniak sees the act of automation as a creative process. From the outside, art is regarded as highbrow and intellectual. Automation, however, is often perceived as rote and boring by those who are non-technical. Cherniak tries to bridge this gap by using software to automate the generation of unique art pieces that aim to elicit the same emotions and reactions that viewers feel when viewing art that has been “generated” by hand.
Jeff Davis: Hi Dmitri, it’s great to speak with you and learn more about your creative practice. How did you first get into making art?
Dmitri Cherniak: I have always been interested in making art, and as a kid was a prolific doodler and illustrator. In fact, I still get messages from my Dad telling me that my latest pieces remind him of pictures I drew when I was young. Despite that interest, my aptitude and curiosity for STEM classes eventually pulled me away from pursuing any kind of serious formal arts education, which is something I regret to this day.
JD: So what caused you to revisit the concept of artmaking with your technical background?
DC: In 2010 for a university course in AI, our yearlong project was to create a player for a variant of the game “Go.” At the time the game was dominated by human players, but now masters of Go are completely trampled by Alpha Go. I made a player called “Taylor Swift” and after she defeated her opponent, I wanted them to see a picture of her blowing them a kiss. Because all of the tournament game play was text based and written to logs, I built a system to generate Taylor Swift ASCII art so that whenever anyone would go over their logs to see how they got beaten so badly they would also see her blowing them a kiss in the console. In addition, I made a stylized cover image for the term paper that used a grayscale color palette that made me realize how much depth I could achieve in ASCII art portraiture. Five years later, in 2015, I posted the image online and it really resonated with my friends, around 10 people messaged me asking to buy it within the hour. At that point I knew I was on to something.
JD: That’s really interesting. What was your transition then into NFTs / crypto art?
DC: I’ve been fortunate enough to have been exposed to cryptocurrency and blockchains for a while. At my first solo show in San Francisco, the curator I worked with thought it would be cheeky if we allowed collectors to purchase art with Bitcoin. It turns out one of the founders of Coinbase stopped by and purchased one of my prints using BTC. Looking back, it might have been the best art business decision ever made considering the exchange rate of BTC at the time. The first NFT I ever minted was in 2019 for Jake Brukhman on OpenSea. He really pushed me to consider minting an NFT alongside the physical print that hangs in his apartment today.
JD: How do you think your creative practice has changed since then?
DC: At first, I was happy to just make one-off unique prints from an algorithm with unstructured code that wasn’t backed up, but over time I’ve focused on using good engineering discipline and hygiene to make aspects of the art more easily customizable, make my code more reusable, and reproduce any work I’ve generated previously. Not only does this make it easier to make new work, but it also helps me develop a “style” in generative art. Since we don’t get the benefit of having a distinct brush stroke in generative art, the code and configuration we decide to reuse helps us define our own distinct styles.
JD: Any recent accomplishments you’d like to share?
DC: This was a strange year as almost all events and commissions got cancelled, but some highlights include my artwork being shown on the big screens in Shibuya (The Times Square of Tokyo), being included in the Official “Virtual” New Year’s Eve Art Gallery in Times Square, and a collaboration between myself and renowned GAN artist Helena Sarin being made into an art book called Gen 2 GAN. We used my generative art algorithms to create a dataset for a machine learning pipeline tended to and curated by Sarin which yielded amazing results.
JD: OK, so let’s talk Art Blocks. What was the inspiration for Ringers?
DC: One of the things that really excites me about Art Blocks is that it feels like a breakthrough for my creative practice. Instead of focusing on selling a single output that I want to share, I can share the whole algorithm and collectors can appreciate a distinct set of the outputs.
The inspiration for Ringers came from taking a looped string and wrapping/weaving it around a set of circular pegs sampled from a two dimensional grid in a way that there are no intersections. Visually when you see it it’s rather intuitive and you might be able to draw a few instances by hand, which is something I often do. From a code and numerical perspective, it’s much more complicated to get right. You need to sample positions from the grid, sort them in a way such that the lines don’t intersect (I do this by doing an angular sort around the centroid of the sampled pegs), calculate the set of lines that are tangent between each peg/circle based on position and radius, then you need to calculate the arc curves around each peg taking note of which way around the peg the path would need to follow and compensating for that. It involves a bit of geometry, a bit of problem solving, and a number of steps that individually don’t feel intuitive compared to the visual system at all.
JD: What should collectors look for in your Art Blocks project as the series is revealed?
DC: I think they should be aware that it’s a form that I have been working with over a number of years and what they are seeing on Art Blocks is a culmination of insights into the form. If they want to know what to expect from the algorithm’s output, I recommend looking at my social media and observing the development of new features over time.
JD: Anything else people should know to better understand your art?
DC: I like to say that automation is my artistic medium. I think it’s important to understand that though I build and design the system in which the art is created, the actual output is not something I have much of an explicit say in. I often joke that the computer is in fact the artist. I will always downplay the role of the artist in my work and I’ve noticed it pisses off a lot of other artists who make algorithmic work. At the end of the day, I take in inputs, fiddle around with parameters, and then leave you with a system that produces output.
JD: Great stuff Dmitri! What’s the best way for people to follow your work?
DC: I post frequently on Twitter and Instagram.
Dmitri Cherniak is a Canadian artist based in New York. An engineer by education and trade, Cherniak sees the act of automation as a creative process. From the outside, art is regarded as highbrow and intellectual. Automation, however, is often perceived as rote and boring by those who are non-technical. Cherniak tries to bridge this gap by using software to automate the generation of unique art pieces that aim to elicit the same emotions and reactions that viewers feel when viewing art that has been “generated” by hand.
Jeff Davis: Hi Dmitri, it’s great to speak with you and learn more about your creative practice. How did you first get into making art?
Dmitri Cherniak: I have always been interested in making art, and as a kid was a prolific doodler and illustrator. In fact, I still get messages from my Dad telling me that my latest pieces remind him of pictures I drew when I was young. Despite that interest, my aptitude and curiosity for STEM classes eventually pulled me away from pursuing any kind of serious formal arts education, which is something I regret to this day.
JD: So what caused you to revisit the concept of artmaking with your technical background?
DC: In 2010 for a university course in AI, our yearlong project was to create a player for a variant of the game “Go.” At the time the game was dominated by human players, but now masters of Go are completely trampled by Alpha Go. I made a player called “Taylor Swift” and after she defeated her opponent, I wanted them to see a picture of her blowing them a kiss. Because all of the tournament game play was text based and written to logs, I built a system to generate Taylor Swift ASCII art so that whenever anyone would go over their logs to see how they got beaten so badly they would also see her blowing them a kiss in the console. In addition, I made a stylized cover image for the term paper that used a grayscale color palette that made me realize how much depth I could achieve in ASCII art portraiture. Five years later, in 2015, I posted the image online and it really resonated with my friends, around 10 people messaged me asking to buy it within the hour. At that point I knew I was on to something.
JD: That’s really interesting. What was your transition then into NFTs / crypto art?
DC: I’ve been fortunate enough to have been exposed to cryptocurrency and blockchains for a while. At my first solo show in San Francisco, the curator I worked with thought it would be cheeky if we allowed collectors to purchase art with Bitcoin. It turns out one of the founders of Coinbase stopped by and purchased one of my prints using BTC. Looking back, it might have been the best art business decision ever made considering the exchange rate of BTC at the time. The first NFT I ever minted was in 2019 for Jake Brukhman on OpenSea. He really pushed me to consider minting an NFT alongside the physical print that hangs in his apartment today.
JD: How do you think your creative practice has changed since then?
DC: At first, I was happy to just make one-off unique prints from an algorithm with unstructured code that wasn’t backed up, but over time I’ve focused on using good engineering discipline and hygiene to make aspects of the art more easily customizable, make my code more reusable, and reproduce any work I’ve generated previously. Not only does this make it easier to make new work, but it also helps me develop a “style” in generative art. Since we don’t get the benefit of having a distinct brush stroke in generative art, the code and configuration we decide to reuse helps us define our own distinct styles.
JD: Any recent accomplishments you’d like to share?
DC: This was a strange year as almost all events and commissions got cancelled, but some highlights include my artwork being shown on the big screens in Shibuya (The Times Square of Tokyo), being included in the Official “Virtual” New Year’s Eve Art Gallery in Times Square, and a collaboration between myself and renowned GAN artist Helena Sarin being made into an art book called Gen 2 GAN. We used my generative art algorithms to create a dataset for a machine learning pipeline tended to and curated by Sarin which yielded amazing results.
JD: OK, so let’s talk Art Blocks. What was the inspiration for Ringers?
DC: One of the things that really excites me about Art Blocks is that it feels like a breakthrough for my creative practice. Instead of focusing on selling a single output that I want to share, I can share the whole algorithm and collectors can appreciate a distinct set of the outputs.
The inspiration for Ringers came from taking a looped string and wrapping/weaving it around a set of circular pegs sampled from a two dimensional grid in a way that there are no intersections. Visually when you see it it’s rather intuitive and you might be able to draw a few instances by hand, which is something I often do. From a code and numerical perspective, it’s much more complicated to get right. You need to sample positions from the grid, sort them in a way such that the lines don’t intersect (I do this by doing an angular sort around the centroid of the sampled pegs), calculate the set of lines that are tangent between each peg/circle based on position and radius, then you need to calculate the arc curves around each peg taking note of which way around the peg the path would need to follow and compensating for that. It involves a bit of geometry, a bit of problem solving, and a number of steps that individually don’t feel intuitive compared to the visual system at all.
JD: What should collectors look for in your Art Blocks project as the series is revealed?
DC: I think they should be aware that it’s a form that I have been working with over a number of years and what they are seeing on Art Blocks is a culmination of insights into the form. If they want to know what to expect from the algorithm’s output, I recommend looking at my social media and observing the development of new features over time.
JD: Anything else people should know to better understand your art?
DC: I like to say that automation is my artistic medium. I think it’s important to understand that though I build and design the system in which the art is created, the actual output is not something I have much of an explicit say in. I often joke that the computer is in fact the artist. I will always downplay the role of the artist in my work and I’ve noticed it pisses off a lot of other artists who make algorithmic work. At the end of the day, I take in inputs, fiddle around with parameters, and then leave you with a system that produces output.
JD: Great stuff Dmitri! What’s the best way for people to follow your work?
DC: I post frequently on Twitter and Instagram.
Dmitri Cherniak is a Canadian artist based in New York. An engineer by education and trade, Cherniak sees the act of automation as a creative process. From the outside, art is regarded as highbrow and intellectual. Automation, however, is often perceived as rote and boring by those who are non-technical. Cherniak tries to bridge this gap by using software to automate the generation of unique art pieces that aim to elicit the same emotions and reactions that viewers feel when viewing art that has been “generated” by hand.
Jeff Davis: Hi Dmitri, it’s great to speak with you and learn more about your creative practice. How did you first get into making art?
Dmitri Cherniak: I have always been interested in making art, and as a kid was a prolific doodler and illustrator. In fact, I still get messages from my Dad telling me that my latest pieces remind him of pictures I drew when I was young. Despite that interest, my aptitude and curiosity for STEM classes eventually pulled me away from pursuing any kind of serious formal arts education, which is something I regret to this day.
JD: So what caused you to revisit the concept of artmaking with your technical background?
DC: In 2010 for a university course in AI, our yearlong project was to create a player for a variant of the game “Go.” At the time the game was dominated by human players, but now masters of Go are completely trampled by Alpha Go. I made a player called “Taylor Swift” and after she defeated her opponent, I wanted them to see a picture of her blowing them a kiss. Because all of the tournament game play was text based and written to logs, I built a system to generate Taylor Swift ASCII art so that whenever anyone would go over their logs to see how they got beaten so badly they would also see her blowing them a kiss in the console. In addition, I made a stylized cover image for the term paper that used a grayscale color palette that made me realize how much depth I could achieve in ASCII art portraiture. Five years later, in 2015, I posted the image online and it really resonated with my friends, around 10 people messaged me asking to buy it within the hour. At that point I knew I was on to something.
JD: That’s really interesting. What was your transition then into NFTs / crypto art?
DC: I’ve been fortunate enough to have been exposed to cryptocurrency and blockchains for a while. At my first solo show in San Francisco, the curator I worked with thought it would be cheeky if we allowed collectors to purchase art with Bitcoin. It turns out one of the founders of Coinbase stopped by and purchased one of my prints using BTC. Looking back, it might have been the best art business decision ever made considering the exchange rate of BTC at the time. The first NFT I ever minted was in 2019 for Jake Brukhman on OpenSea. He really pushed me to consider minting an NFT alongside the physical print that hangs in his apartment today.
JD: How do you think your creative practice has changed since then?
DC: At first, I was happy to just make one-off unique prints from an algorithm with unstructured code that wasn’t backed up, but over time I’ve focused on using good engineering discipline and hygiene to make aspects of the art more easily customizable, make my code more reusable, and reproduce any work I’ve generated previously. Not only does this make it easier to make new work, but it also helps me develop a “style” in generative art. Since we don’t get the benefit of having a distinct brush stroke in generative art, the code and configuration we decide to reuse helps us define our own distinct styles.
JD: Any recent accomplishments you’d like to share?
DC: This was a strange year as almost all events and commissions got cancelled, but some highlights include my artwork being shown on the big screens in Shibuya (The Times Square of Tokyo), being included in the Official “Virtual” New Year’s Eve Art Gallery in Times Square, and a collaboration between myself and renowned GAN artist Helena Sarin being made into an art book called Gen 2 GAN. We used my generative art algorithms to create a dataset for a machine learning pipeline tended to and curated by Sarin which yielded amazing results.
JD: OK, so let’s talk Art Blocks. What was the inspiration for Ringers?
DC: One of the things that really excites me about Art Blocks is that it feels like a breakthrough for my creative practice. Instead of focusing on selling a single output that I want to share, I can share the whole algorithm and collectors can appreciate a distinct set of the outputs.
The inspiration for Ringers came from taking a looped string and wrapping/weaving it around a set of circular pegs sampled from a two dimensional grid in a way that there are no intersections. Visually when you see it it’s rather intuitive and you might be able to draw a few instances by hand, which is something I often do. From a code and numerical perspective, it’s much more complicated to get right. You need to sample positions from the grid, sort them in a way such that the lines don’t intersect (I do this by doing an angular sort around the centroid of the sampled pegs), calculate the set of lines that are tangent between each peg/circle based on position and radius, then you need to calculate the arc curves around each peg taking note of which way around the peg the path would need to follow and compensating for that. It involves a bit of geometry, a bit of problem solving, and a number of steps that individually don’t feel intuitive compared to the visual system at all.
JD: What should collectors look for in your Art Blocks project as the series is revealed?
DC: I think they should be aware that it’s a form that I have been working with over a number of years and what they are seeing on Art Blocks is a culmination of insights into the form. If they want to know what to expect from the algorithm’s output, I recommend looking at my social media and observing the development of new features over time.
JD: Anything else people should know to better understand your art?
DC: I like to say that automation is my artistic medium. I think it’s important to understand that though I build and design the system in which the art is created, the actual output is not something I have much of an explicit say in. I often joke that the computer is in fact the artist. I will always downplay the role of the artist in my work and I’ve noticed it pisses off a lot of other artists who make algorithmic work. At the end of the day, I take in inputs, fiddle around with parameters, and then leave you with a system that produces output.
JD: Great stuff Dmitri! What’s the best way for people to follow your work?
DC: I post frequently on Twitter and Instagram.
Dmitri Cherniak is a Canadian artist based in New York. An engineer by education and trade, Cherniak sees the act of automation as a creative process. From the outside, art is regarded as highbrow and intellectual. Automation, however, is often perceived as rote and boring by those who are non-technical. Cherniak tries to bridge this gap by using software to automate the generation of unique art pieces that aim to elicit the same emotions and reactions that viewers feel when viewing art that has been “generated” by hand.
Jeff Davis: Hi Dmitri, it’s great to speak with you and learn more about your creative practice. How did you first get into making art?
Dmitri Cherniak: I have always been interested in making art, and as a kid was a prolific doodler and illustrator. In fact, I still get messages from my Dad telling me that my latest pieces remind him of pictures I drew when I was young. Despite that interest, my aptitude and curiosity for STEM classes eventually pulled me away from pursuing any kind of serious formal arts education, which is something I regret to this day.
JD: So what caused you to revisit the concept of artmaking with your technical background?
DC: In 2010 for a university course in AI, our yearlong project was to create a player for a variant of the game “Go.” At the time the game was dominated by human players, but now masters of Go are completely trampled by Alpha Go. I made a player called “Taylor Swift” and after she defeated her opponent, I wanted them to see a picture of her blowing them a kiss. Because all of the tournament game play was text based and written to logs, I built a system to generate Taylor Swift ASCII art so that whenever anyone would go over their logs to see how they got beaten so badly they would also see her blowing them a kiss in the console. In addition, I made a stylized cover image for the term paper that used a grayscale color palette that made me realize how much depth I could achieve in ASCII art portraiture. Five years later, in 2015, I posted the image online and it really resonated with my friends, around 10 people messaged me asking to buy it within the hour. At that point I knew I was on to something.
JD: That’s really interesting. What was your transition then into NFTs / crypto art?
DC: I’ve been fortunate enough to have been exposed to cryptocurrency and blockchains for a while. At my first solo show in San Francisco, the curator I worked with thought it would be cheeky if we allowed collectors to purchase art with Bitcoin. It turns out one of the founders of Coinbase stopped by and purchased one of my prints using BTC. Looking back, it might have been the best art business decision ever made considering the exchange rate of BTC at the time. The first NFT I ever minted was in 2019 for Jake Brukhman on OpenSea. He really pushed me to consider minting an NFT alongside the physical print that hangs in his apartment today.
JD: How do you think your creative practice has changed since then?
DC: At first, I was happy to just make one-off unique prints from an algorithm with unstructured code that wasn’t backed up, but over time I’ve focused on using good engineering discipline and hygiene to make aspects of the art more easily customizable, make my code more reusable, and reproduce any work I’ve generated previously. Not only does this make it easier to make new work, but it also helps me develop a “style” in generative art. Since we don’t get the benefit of having a distinct brush stroke in generative art, the code and configuration we decide to reuse helps us define our own distinct styles.
JD: Any recent accomplishments you’d like to share?
DC: This was a strange year as almost all events and commissions got cancelled, but some highlights include my artwork being shown on the big screens in Shibuya (The Times Square of Tokyo), being included in the Official “Virtual” New Year’s Eve Art Gallery in Times Square, and a collaboration between myself and renowned GAN artist Helena Sarin being made into an art book called Gen 2 GAN. We used my generative art algorithms to create a dataset for a machine learning pipeline tended to and curated by Sarin which yielded amazing results.
JD: OK, so let’s talk Art Blocks. What was the inspiration for Ringers?
DC: One of the things that really excites me about Art Blocks is that it feels like a breakthrough for my creative practice. Instead of focusing on selling a single output that I want to share, I can share the whole algorithm and collectors can appreciate a distinct set of the outputs.
The inspiration for Ringers came from taking a looped string and wrapping/weaving it around a set of circular pegs sampled from a two dimensional grid in a way that there are no intersections. Visually when you see it it’s rather intuitive and you might be able to draw a few instances by hand, which is something I often do. From a code and numerical perspective, it’s much more complicated to get right. You need to sample positions from the grid, sort them in a way such that the lines don’t intersect (I do this by doing an angular sort around the centroid of the sampled pegs), calculate the set of lines that are tangent between each peg/circle based on position and radius, then you need to calculate the arc curves around each peg taking note of which way around the peg the path would need to follow and compensating for that. It involves a bit of geometry, a bit of problem solving, and a number of steps that individually don’t feel intuitive compared to the visual system at all.
JD: What should collectors look for in your Art Blocks project as the series is revealed?
DC: I think they should be aware that it’s a form that I have been working with over a number of years and what they are seeing on Art Blocks is a culmination of insights into the form. If they want to know what to expect from the algorithm’s output, I recommend looking at my social media and observing the development of new features over time.
JD: Anything else people should know to better understand your art?
DC: I like to say that automation is my artistic medium. I think it’s important to understand that though I build and design the system in which the art is created, the actual output is not something I have much of an explicit say in. I often joke that the computer is in fact the artist. I will always downplay the role of the artist in my work and I’ve noticed it pisses off a lot of other artists who make algorithmic work. At the end of the day, I take in inputs, fiddle around with parameters, and then leave you with a system that produces output.
JD: Great stuff Dmitri! What’s the best way for people to follow your work?
DC: I post frequently on Twitter and Instagram.
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