Eugene Cheah

5 statements across 2 episodes · 3 bullish · 1 bearish · 1 people on the record · first statement Aug 31, 2023 by Eugene Cheah · said 9 times in 4 episodes since 2024 · across every show →

On the record as a speaker too: Eugene Cheah's record, appearances and statements → this page counts the times other people say the name.

Mentions by year

brought up most by Sarah Chieng (5), Jesse Hu (1), Alessio Fanelli (1)

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Everything said about Eugene Cheah, oldest first

Aug 31, 2023 positive
Opinion
Cheah: A Human Personality and Memories Can Fit on Two SSDs
“No offense to myself, I don't think my personality and my memories is more than this. We could, even if I can exit, I could store this in two SSDs. Two hard drives.”
Eugene Cheah Aug 31, 2023 ▶ 1:54:37 RWKV: Reinventing RNNs for the Transformer Era
Dec 24, 2024 neutral
Assertion Not checkable as stated
Cheah: Most enterprise AI workloads use 70B models under 32k context
“Majority of enterprise workload today is just on Senti B at under 32 K context line.”
Eugene Cheah Dec 24, 2024 ▶ 27:23 2024 in Post-Transformer Architectures: State Space Models, RWKV [Latent Space LIVE! @ NeurIPS 2024]
Dec 24, 2024 positive
Insight
Cheah: Non-positional attention architectures remain stable beyond trained context
“One key advantage of this alternate attention mechanic that is not based on token position is that the model don't suddenly become crazy when you go past the eight K training context or a million context. It is actually still stable. It's still, it's able to r…”
Eugene Cheah Dec 24, 2024 ▶ 41:28 2024 in Post-Transformer Architectures: State Space Models, RWKV [Latent Space LIVE! @ NeurIPS 2024]
Dec 24, 2024 negative
Disclosure
Cheah: RWKV organization has less compute than a single Google researcher
“So our entire organization has less compute than a single researcher in Google.”
Eugene Cheah Dec 24, 2024 ▶ 24:32 2024 in Post-Transformer Architectures: State Space Models, RWKV [Latent Space LIVE! @ NeurIPS 2024]
Dec 24, 2024 positive
Insight
Cheah: Hybrid SSM-transformer models outperform pure baselines of both
“None of us understand why a hybrid with a state-based model, the RWA state space, and transformer performs better than the baseline of both. It's like when you train one, you expect, and then you replace, you expect the same results. That's our pitch. That's o…”
Eugene Cheah Dec 24, 2024 ▶ 28:15 2024 in Post-Transformer Architectures: State Space Models, RWKV [Latent Space LIVE! @ NeurIPS 2024]
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