6). Consistency LLMs – uses efficient parallel decoders that reduce inference latency by decoding n-token sequence per inference step; inspired by he human's ability to form complete sentences before articulating word by word…
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3). DeepSeek-V2 – a strong MoE 236B parameter model, of which 21B are activated for each token; supports a context length of 128K tokens and uses Multi-head Latent Attention (MLA) for efficient inference by compressing the Key-Value (KV) cache into a latent vector…
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Model Scaling Outpaces Hardware in AI Competition
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Whatever that scales faster wins the wars. I would say models do scale faster than HW – but of course both trends actually supplement each other.
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