Difference between revisions of "Seeing Machines research doc."
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In the series ‘Is Photography Over?’ published a few years ago by Trevor Paglen, I became aware of the concept behind ‘Seeing machines’. In first instance, he sketches out that the traditional photography theory and practice seems to be at a standstill. I agree because experience shown that at the academy no questions are asked about what photography has become. Despite the extreme change in the photographic landscape. However, we need a broader debate on this subject. And interestingly, as I think back, to ask questions such as ‘can the definition of photography expand’ of ‘what has photography become’. Paglen did approaches these question and free my mind. From his question based text I was confident enough to submit myself with the question if machine perception can expand the field of photography. | In the series ‘Is Photography Over?’ published a few years ago by Trevor Paglen, I became aware of the concept behind ‘Seeing machines’. In first instance, he sketches out that the traditional photography theory and practice seems to be at a standstill. I agree because experience shown that at the academy no questions are asked about what photography has become. Despite the extreme change in the photographic landscape. However, we need a broader debate on this subject. And interestingly, as I think back, to ask questions such as ‘can the definition of photography expand’ of ‘what has photography become’. Paglen did approaches these question and free my mind. From his question based text I was confident enough to submit myself with the question if machine perception can expand the field of photography. | ||
| − | + | ''“Seeing machines is an expansive definition of photography. It is intended to encompass the myriad ways that not only humans use technology to “see” the world, but the ways machines see the world for other machines.” Paglen'' | |
To me, it was exiting enough to start a practical research into this technique. I started with a simple question, how do computers read images? I stumbled on different techniques that all led to machine learning. [HOG/CNN] | To me, it was exiting enough to start a practical research into this technique. I started with a simple question, how do computers read images? I stumbled on different techniques that all led to machine learning. [HOG/CNN] | ||
What drew me the most was an image from Stanford’s CS 231 N a course taught by Andrei Karpathy and Justin Johnson [x]. It shows us an image of the process, inside a neural network, entire abstract to the human eye. Although I couldn’t understand what was happening in this process I wanted to explore this field and had to master the technical part, no matter what. This year I had my first experience with AI and experience in practice did show answers. | What drew me the most was an image from Stanford’s CS 231 N a course taught by Andrei Karpathy and Justin Johnson [x]. It shows us an image of the process, inside a neural network, entire abstract to the human eye. Although I couldn’t understand what was happening in this process I wanted to explore this field and had to master the technical part, no matter what. This year I had my first experience with AI and experience in practice did show answers. | ||
Revision as of 11:55, 29 May 2018
Seeing machines
Not only humans perceive the world. In the digital age, machines see the world for other machines. By producing images, Artificial Intelligence (AI) is able to orientate itself in the world. Just like humans, that created the image to guide us through the universe.
Approaching ‘seeing machines’ will introduce us to a new field of algorithms that trust on photographic technologies. They reveal images purposed solely for machine-to-machine communication and which are not optimized to seen by human. I attempt to see from their perspective, curious for the opportunities in which photography could transform. By adopting their vision I want to explore in what way machine perception can expand the field of photography, open our view of external reality and our outlook of life. Can they be a legitimate voice in the discourse of photography?
introduction
From a young age I was triggered by the image, with photography in particular. How it was a mediator between the world and myself. It was an entrance to make the world imaginable, without immediate access to this world. Opening up to a new view and increasing awareness of our environment. The world constantly changes, therewith the image.
Nowadays my urgency still lies with the image. But the deluge of images, the saturation, has prompted me to ask if its still make sense to photograph in his existing framework. Anyone can produce pictures without knowing about the complex processes. Everybody has cameras and image-processing software at there fingertips. Knowledge of craftsmanship is no longer necessary; no practise of training in equipment is required and so on. Billion of images are added daily, whereby it almost becomes a disposable product. The consequence is that I don’t see the value of making more photographs. Photography, as we all traditionally know, has undergone a transition. The further I came to realize that, the more I wanted to dissociate myself from its tradition. Because today in the age of smart phones, satellite images, CCTV, machine image algorithms or drone media, image practices become all-pervasive. The definition of photography expands. From which I concluded that this is about ‘Seeing machines’. Without question, the photographic landscape and image-making devices will enlarge and it will play a fundamental role in many basic elements of our lives. The development makes me very curious and that is why I do not abandon mine practice. I haven’t seen anything yet.
Relevance of the Topic
The contemporary revolution in photography offers opportunities that exceed the wildest expectations. The medium is embedded in our everyday life on many different levels: from automated license plate recognition systems, CCTV, Google Earth, smart phone, machine image algorithms, drones media to the advent of infinite image storage. It contains many different kind of technologies, imaging devices and practices. The medium has always closely linked with the possibilities of technological advancements. The evolving relationship has created new ways to represent our physical world. Thereby it has ultimately transformed society and affects the photographic landscape. Photography, as it was once understood, has going beyond his existing framework. The current time asks to consider a new perspective. How do I relate to photography when I think in terms of imaging systems instead of photos? […/self proven of life-shaping medium/ sculpting the world] The definition extends to help us see what photography has become.
Insight from Experimentation
‘Seeing machines’ – the working title of my artistic-based research. I came across this concept a few years ago in an interview with artist Ola Lanko. She translated it as constant recordings from example satellites or CCTV. A production process that is decoupled from human intervention. Although I could not exactly understand what it would contain, I founded it intuitively way more exciting than the traditional understanding of photography. In addition it is a better translation of the 21st century photographic landscape because it contains that many different kind of technologies, imaging devices and practices. So, to reinvent the medium for myself I started exploring within this domain. The expectation was to find life again in photography.
I consistently embarked with what ‘seeing machines’ defined for me and it became a rich topic of exploration. I approached it in different ways until I found something that I was not aware of, something that made me very curious. In the series ‘Is Photography Over?’ published a few years ago by Trevor Paglen, I became aware of the concept behind ‘Seeing machines’. In first instance, he sketches out that the traditional photography theory and practice seems to be at a standstill. I agree because experience shown that at the academy no questions are asked about what photography has become. Despite the extreme change in the photographic landscape. However, we need a broader debate on this subject. And interestingly, as I think back, to ask questions such as ‘can the definition of photography expand’ of ‘what has photography become’. Paglen did approaches these question and free my mind. From his question based text I was confident enough to submit myself with the question if machine perception can expand the field of photography.
“Seeing machines is an expansive definition of photography. It is intended to encompass the myriad ways that not only humans use technology to “see” the world, but the ways machines see the world for other machines.” Paglen
To me, it was exiting enough to start a practical research into this technique. I started with a simple question, how do computers read images? I stumbled on different techniques that all led to machine learning. [HOG/CNN] What drew me the most was an image from Stanford’s CS 231 N a course taught by Andrei Karpathy and Justin Johnson [x]. It shows us an image of the process, inside a neural network, entire abstract to the human eye. Although I couldn’t understand what was happening in this process I wanted to explore this field and had to master the technical part, no matter what. This year I had my first experience with AI and experience in practice did show answers.
