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GAIA – Open-source framework for building AI agents that run on local hardware
- galaxyLogic 6mo agoNot so clear from their page but from https://www.tipranks.com/news/amd-stock-slips-despite-a-major-update-to-generative-ai-app-gaia https://www.tipranks.com/news/amd-stock-slips-despite-a-majo... I read: " In addition to that, the update allows these agents to be turned into desktop apps for multiple operating systems. " This seems like a new way to create app: Create an (AI) app that creates apps.
- latchkey 6mo agoThe stock is peaking highs again and people are quoting articles saying "stock slips"...
- Mars008 6mo agoIn case you are interested: Requirement Minimum Processor AMD Ryzen AI 300-series
- lysp 6mo agoIt reads as optional for NPU support. But seems to have that as minimum on another page.
- Mars008 6mo agoAny lock in makes it significantly less attractive. AMD is not in dominant position to insist. More portable would make it more attractive. Like MS did, sort of works everywhere but better on Windows.
- xrd 6mo agoI wanted to believe but anyone who has spent any time trying to run models locally knows this is not going to be solved by two lines of python running on rocm as the example shows.
- wilkystyle 6mo agoCurious to hear more. My experience is limited to llama.cpp on Apple silicon so far, but have been eyeing AMD ecosystem from afar.
- nevi-me 6mo agoPerhaps not a good example, I tried running local models a few times, to much disappointment (actually made me skeptical of LLMs in general for a while). My last experiment in January was trying to run a Qwen model locally (RTX 4080; 128GB RAM; 9950X3D). I must have been doing it extremely wrong because the models that I tried either hallucinated severely or got stuck in a loop. The funniest one was stuck in a "but wait, ..." loop. I fortunately had started experimenting with Claude, so I opted to pay Anthropic more money for tokens (work already covers the bill, this was for personal use). That whole experience + a noisy GPU, put me off the idea of running/building local agents.
- buryat 6mo agoI have a Mac Studio with 512GB Ram and ran models of different sizes to test out how local agents are and I agree that local models aren't there yet but that depends on whether you need a lot of knowledge or not to answer your question, and I think it should be possible to either distill or train a smaller model that works on a subset of knowledge tailored toward local execution. My main interest is in reducing the latency and it feels that the local agents that work at high speeds should be an answer to this but it's not something that someone is trying to solve yet. Feels like if I could get a smaller model that could run at incredible speed locally that could unlock some interesting autoresearching.
- verdverm 6mo agoI've been running Gemma4, my initial experiments put it around gemini-3-flash levels (vibe evals)
- robwwilliams 6mo ago
- warwickmcintosh 6mo agoROCm has improved but the reality is you're still fighting the driver stack more than the models. If you're actually doing local inference on AMD you're spending your time on CUDA compatibility layers, not the AI part. Two lines of python is marketing, the gap between demo and working AMD setup is still real.
- ddtaylor 6mo agoOllama works very well in Linux on my AMD hardware. I have a 6800 XT which isn't even originally supported by the ROCm stack in some ways and it "just works" for a ton of very nice models, especially if I seek out quantized versions of the model.
- sabedevops 6mo agoROCm is finally getting better due to a few well meaning engineers. But let’s be honest, AMD has been an extremely bad citizen to non-corporate users. For my iGPU I have to fake GFX900 and build things from source or staging packages to get that working. Support for GFX90c is finally in the pipeline… The improvements feel like a bodyguard finally letting you through the door just because NVIDIA is eating their lunch and they don’t want their club to be empty. They strongarm their customers to using “Enterprise” GPUs to be able to play with ROCm, and are only broadening their offerings for market share purposes. Really shouldn’t reward this behavior.
- androiddrew 6mo agoYup, meanwhile Jensen is on the Lexfriedman podcast stating the reason why CUDA is successful is because all thier devices run it. The on ramp is at the individual user. I have and RDNA4 card and they certainly are prioritizing CDNA over a CDNA + RDNA strategy or a unification strategy.
- Shitty-kitty 6mo agoThe problem is the split CDNA/RDNA architecture. A problem they are adressing with their upcoming unified UDMA.
- suprjami 6mo agoDebian build their ROCm with support for all possible devices. If you are tired of compiling from source just use a Debian Stable container, install their libraries in your container build, and pass /dev/kfd and /dev/dri to the container. No ROCm or out-of-tree drivers required on the container host, just regular upstream Linux kernel amdgpu and those two devices to the container. It's also probably worth trying Vulkan inference. It is now faster than ROCm - both tg and pp over 16k ctx - on Strix Halo so maybe you'll see the benefits too.
- volume_tech 6mo ago[dead]
- coppsilgold 6mo agoNvidia went through a lot of effort to make CUDA operational on their entire lineup, and they did it before deep learning even took off. You do this thing not because you expect consumers with 5 year old hardware to provide meaningful utilization but as a demo ("let me grab my old gaming machine and do some supercomputing real quick") and a signal that you intend to stay the course. AMD management hasn't realized this even after various Nvidia people said that this was exactly why they did it, at some point the absence of that signal is a signal that the AMD compute ecosystem is an unreliable investment, no?
- androiddrew 6mo agoYou got it right I think. I’m sitting with two “AI Ready Radeon AI Pro 9700 workstation cards, which are RDNA4 not CDNA. My experience is that my cards are not a priority. Individual engineers at AMD may care, the company doesn’t. I have been trying since February to get ahold of anyone responsible for shipping tuned Tensile gfx1201 kernels in rocm-libs, which is used by Ollama.its been three weeks since I raised enough hell on the discord to get a response, but they still can’t find “who” is responsible for Tensile tuning, and “if” they are even going to do it for the gfx12* cards. Don’t get me started with vLLM and AITER.
- ra 6mo agoI agree, and think AMD and Nvidia philosophy diverged way before Cuda. I can't count how many times over the last 30 years I've had AMD drivers crash the OS (Linux and Windows). Nvidia have been mostly rock solid. The thing is, the die isn't much use without a stable driver (and AI stack).
- Azantys 6mo agoYeah I own an AMD Instinct MI50 and i need to patch all of my applications to work, like PyTorch, bitsandbytes, blender etc, while Nvidia cards from the same generation are still mostly supported. But the better value and hardware are worth it
- 0xbadcafebee 6mo agoI would love to use your tool locally, AMD, if you'd support the AMD graphics card you sold me.
- mininglamp 6mo ago[dead]
- ElenaDaibunny 6mo ago[dead]
- madbo1 6mo ago[flagged]
- suprjami 6mo ago> created 20 days ago > multiple factual errors > advertising re-explanation Found the bot shill account.
- MrHermes 6mo ago[dead]