11–20 of 33 posts
This feels like an AI agent doing it's own thing. The screenshot of this working is garble text ( https://github.com/sophiaeagent-beep/n64llm-legend-of-Elya/b... ), and I'm skeptical of reasonable generation with a small hard-coded training corpus. And the linked devlog on youtube is quite bizzare too.
This feels like an AI agent doing it's own thing. The screenshot of this working is garble text ( https://github.com/sophiaeagent-beep/n64llm-legend-of-Elya/b... ), and I'm skeptical of reasonable generation with a small hard-coded training corpus. And the linked devlog on youtube is quite bizzare too.
The sgai_rsp_matmul_q4() stub is planned for RSP microcode:
DMA Q4 weight tiles into DMEM (4KB at a time)
VMULF/VMADH vector multiply-accumulate for 8-lane dot products
Estimated 4-8× speedup over scalar VR4300 inference
rsp is the gift that keeps on giving; such a forwards-looking architecture (shame about the rambus latency tho)
The readme says: > This isn't just a tech demo — it's a tool for N64 homebrew developers. Running an LLM natively on N64 hardware enables game mechanics that were impossible in the cartridge era: > AI analyzes play style and adjusts on the fly > NPCs that remember previous conversations and reference past events > In-game level editors where you describe what you want to build ...anyone who has ever used very small l…
You mean to tell me the included screenshot hasn't convinced you? https://github.com/sophiaeagent-beep/n64llm-legend-of-Elya/b...
It feels very much like it’s cobbled together from the libdragon examples directory. Or, they use hardware acceleration for the 2D sprites, but then write fixed-width text to the frambuffer with software rendering.
This feels like an AI agent doing it's own thing. The screenshot of this working is garble text ( https://github.com/sophiaeagent-beep/n64llm-legend-of-Elya/b... ), and I'm skeptical of reasonable generation with a small hard-coded training corpus. And the linked devlog on youtube is quite bizzare too.
It totally is. The fact that this post has gotten this many upvotes is appalling.
This feels like an AI agent doing it's own thing. The screenshot of this working is garble text ( https://github.com/sophiaeagent-beep/n64llm-legend-of-Elya/b... ), and I'm skeptical of reasonable generation with a small hard-coded training corpus. And the linked devlog on youtube is quite bizzare too.
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The sgai_rsp_matmul_q4() stub is planned for RSP microcode: DMA Q4 weight tiles into DMEM (4KB at a time) VMULF/VMADH vector multiply-accumulate for 8-lane dot products Estimated 4-8× speedup over scalar VR4300 inference ---- rsp is the gift that keeps on giving; such a forwards-looking architecture (shame about the rambus latency tho)
The sgai_rsp_matmul_q4() stub is planned for RSP microcode: DMA Q4 weight tiles into DMEM (4KB at a time) VMULF/VMADH vector multiply-accumulate for 8-lane dot products Estimated 4-8× speedup over scalar VR4300 inference ---- rsp is the gift that keeps on giving; such a forwards-looking architecture (shame about the rambus latency tho)
We are going to use the gpu 128simd soon but it only has 4kb ram addressable so matmul offload in small chunks!