h100envy (@h100envy)
@h100envy
you're literally copium, i'm your opium
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Google engineer explained how to fine-tune a tiny LLM from 46% to 90% accuracy on your phone in 21 minutes - better than $1500 on-device AI bootcamps.
pick Gemma 270M -> generate synthetic task data -> fine-tune with LoRA -> quantize to int4 -> deploy to Pixel and hit 2000 tokens per second.
That loop is how a 270M model beats a 70B one on your task, running fully offline in your pocket.
Gemma 270M + synthetic data + LoRA + int4 quantization + on-device runtime - that's the stack.
Watch and save it, then fine-tune your own tiny agent tonight.
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Ex-Berkeley PhD who leads SGLang at xAI explained how they serve Grok on 100K GPUs in 23 minutes - better than $2000 inference-at-scale courses.
split prefill and decode -> shard experts across GPUs -> route tokens per expert -> overlap comm and compute -> serve at DeepSeek-API-killing prices.
That loop is why xAI runs Grok on SGLang and third parties beat DeepSeek's own API by 5x on cost.
SGLang + prefill-decode disaggregation + expert parallelism + AMD MI300 - that's the stack.
Watch and save it, then read the article below.
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Jensen Huang builds the chips every AI on earth runs on.
Lex asked him what every programmer is afraid to ask: will AI replace you?
His answer was sharper than yes or no. Coding doesn't die. It explodes.
Cheap software means the world wants ten times more of it, and whoever directs the machine takes the demand.
The man selling every shovel says the gold rush barely started.
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