anshuman
@athleticKoder
ml @zomato; prev: ai consultant @google
คุณอาจชื่นชอบ
LoRA sounds simple: 1. Add low-rank matrices 2. Train with less memory 3. Get same results Reality: - Learning rate needs 10x adjustment - Layer selection changes everything - Batch size tolerance is different
Nano Banana Pro Understands somethings very well
dear Substack, I'm once again appealing for a stripe alternative in India yours truly.
okay so @1littlecoder recommended me @Patreon. has anyone tried it? what are your reviews. pros/cons? i am honestly fed up of non-existent support of substack. as my audience is growing i am looking to build a community. a good portion of my audience is willing to pay for stuff…
dear Substack, I'm once again appealing for a stripe alternative in India yours truly.
Techniques to Master for Faster + Cheaper LLM Inference 1. Quantization (INT8/INT4/FP8) 2. KV-Cache Optimization (quantization, compression, eviction) 3. Flash Attention 4. Speculative Decoding 5. Continuous Batching 6. Paged Attention / vLLM-style memory management 7. Tensor…
Google is soo back.
Introducing Gemini 3 Pro, the world's most intelligent model that can help you being anything to life. It is state of the art across most benchmarks, but really comes to life across our products (AI Studio, the Gemini API, Gemini App, etc) 🤯
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