The GPU Mining Reboot and Its Implications for AI Compute

The recent whispers of a comeback for GPU mining, dressed up in the guise of artificial intelligence, raise more than a few eyebrows. Entities like NVIDIA and Together AI are allegedly linked to this resurgence. They promise to blend Proof of Work (PoW) with AI tasks to create something novel. But is this truly innovation or merely a smokescreen for bloated GPU prices?

The Players and Their Moves

At the center of this story is Together AI. Hosting Large Language Model (LLM) inference on their GPUs, Together AI claims its operations are subsidized by profits from their $PRL (Pearl) network. Yet miners within the Pearl network aren't performing latest AI tasks. They're engaged in PoW veiled as AI utility, which critics argue is neither efficient nor genuinely beneficial.

NVIDIA's rumored involvement hints at larger implications for the GPU market. When a tech giant like NVIDIA is linked to such efforts, it raises questions about the true motives behind this supposed innovation. Are we witnessing a strategic push to inflate demand and, consequently, prices?

The Cost of Useless Compute

Artificial intelligence, when misapplied, can create more problems than it solves. The irony here's palpable. While there's a rush to define AI as a tool for optimization and progress, this approach feels more like a gimmick. The 'useful' tag attached to this kind of PoW is suspect at best, and downright misleading at worst. Enterprise AI is boring. That's why it works. The focus should be on genuine advances, not rehashing old methods in new packaging.

So, what's the end game? Is the tech world facing a future where GPUs, essential for both AI and gaming industries, become prohibitively expensive due to such speculative ventures? This isn't just about a niche market. It affects developers, researchers, and businesses relying on affordable computing power.

What's at Stake?

The broader implications are clear. If the market succumbs to artificial inflation, it may stifle innovation where it truly matters. Nobody is modelizing lettuce for speculation. They're doing it for traceability. Similarly, AI's potential should be harnessed to solve real-world problems, not resurrect outdated mining practices.

In this evolving story, the tech community must scrutinize the true utility and purpose of these efforts. As the lines blur between genuine technological advancement and financial maneuvering, one must ask: Are we progressing, or just spinning our wheels?