Blasting AI into the past_ Modders get Llama AI working on an old Windows 98 PC

Remember when you were young, your responsibilities were far fewer, and you were still at least a little hopeful about the future potential of tech? Anyway! In our present moment, nothing appears to be safe from the sticky fingers of so-called AI—and that includes nostalgic hardware of yesteryear.

Exo Labs, an outfit with the mission statement of democratising access to AI, such as large language models, has : a modified version of running on a Windows 98 Pentium II machine (via ). Though , it's no less head-turning—even for me, a frequent AI-naysayer.

To be fair, when it comes to , Exo Labs and I seem to be of a similarly wary mind. So, setting aside my own AI-scepticism for the moment, this is undoubtedly an impressive project chiefly because it doesn't rely on to run.

The journey to Llama running on ancient-though-local hardware enjoys some twists and turns; after securing the second hand machine, Exo Labs had to contend with finding pg168 ทางเข้า compatible PS/2 peripherals, and then figure out how they'd even transfer the necessary files onto the decades-old machine. Did you know FTP over an ethernet cable was backwards compatible to this degree? I certainly didn't!

Don't be fooled though—I'm making it sound way easier than it was. Even before FTP finagling was figured out, Exo Labs had to find a way to compile modern code for a pre-Pentium Pro machine. Longer story short-ish, the team went with Borland C++ 5.02, a "26-year-old [integrated development environment] and compiler that ran directly on Windows 98." However, compatibility issues persisted with the programming language C++, so the team had to use the older incarnation of C and deal with declaring variables at ทางเข้า w88 ใหม่ ล่าสุด the start of every function. Oof.

Then, there's the hardware at the heart of this project. For those needing a refresher, the Pentium II machine sports an itty bitty 128 MB of RAM, while a full size Llama 2 LLM boasts 70 billion parameters. Managing all of these hefty constraints, the results are even more interesting.

Unsurprisingly, Exo Labs had to craft a comparatively svelte version of Llama for this project, now available to tool around with yourself via . As a result of everything aforementioned, the retrofitted LLM features 1 billion parameters and spits out 0.0093 Tokens per second—hardly blistering, but the headline take here really is that it works at all.