GPU

Image from the post A complete anatomy of a graphics card: Case study of the NVIDIA A100, https://blog.paperspace.com/a-complete-anatomy-of-a-graphics-card-case-study-of-the-nvidia-a100/

The king of Denmark, Jensen Huang (CEO and founder of Nvidia), and Nadia Carlsten (CEO of the Danish Center for AI Innovation) pose for a photo holding an oversized cable in front of a bright screen full of sparkles. It is the inauguration of Denmark's "sovereign" AI supercomputer, aka Gefjon, named after the Nordic goddess of ploughing.

https://blogs.nvidia.com/blog/denmark-sovereign-ai-supercomputer/

"Gefion is going to be a factory of intelligence. This is a new industry that never existed before. It sits on top of the IT industry. We’re inventing something fundamentally new" (https://blogs.nvidia.com/blog/denmark-sovereign-ai-supercomputer/)

Gefion is powered by 1,528 H100's, a GPU developed by Nvidia. This object, the Graphics Processing Unit, is a key element that, arguably, paves the way for Denmark's sovereignty and heavy ploughing in the AI world. Beyond all the sparkles, this photo shows the importance of the GPU object not only as a technical matter, but also a political and powerful element of today's landscape.

Since the boom of Large Language Models, Nvidia's graphic cards and GPUs have become somewhat familiar and mainstream. The GPU powerhouse, however, has a long history that predates their central position in generative AI, including the stable diffusion ecosystem: casual and professional gaming, cryptocurrencies mining, and just the right processing for n-dimensional matrices that translate pixels and words into latent space and viceversa.

What is a GPU?

A graphics processing unit (GPU) is an electronic circuit focused on processing images in computer graphics. Originally designed for early videogames, like arcades, this specialised hardware performs calculations for generating graphics in 2D and later for 3D. While most computational systems have a Central Processing Unit (CPU), the generation of images, for example, 3D polygons, requires a different set of mathematical calculations. GPUs gather instructions for video processing, light, 3D objects, textures, etc. The range of GPUs is vast, from small and cheap processors integrated into phones and smaller devices, to state of the art graphic cards piled in data centres to calculate massive language models.

What is the network that sustains this object?

Like many other circuits, GPUs require a very advance production process, that starts with mineral mining for both common and rare minerals (gold, hafnium, tantalum, palladium, copper, boron, cobalt, tungsten, etc)

• silicon, materials, mining
• translation to latent space (calculations)
• datacenters, individual users, networks (horde)
• power consumption (electricity) & pollution

How does it evolve through time?

• gaming
• crypto
• neural networks computation
• llm's
• large scale industrial AI

Do Graphics Processing Units Have Politics? SEE ADD

How does it create value? Or decrease / affect value?

• buzz, horde, cryptocurrencies
• covid19 scarcity
• production value (e.g. civitAI)
• national AI sovereignty
• military?

emphasis on autonomy / cultural dependency on autonomy (e.g. the gpu we use) / layer of material inftrastructure connected to cultural layers

What is its place/role in techno cultural strategies? How does it relate to autonomous infrastructure?