以下部分引用 AI 总结,现阶段 AI 仍然有幻觉。请以内容的原文为准。
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jsuarez
6 atoms · 跨 2 天 · 首见 2026-06-21 · 最近 2026-06-22
三色: 🟦 fact 6 · 🟥 take 0 · stance ▲2/▼0/◆2
来源: X 6
时态: fresh:6
标签: 好数字:2 · 好观点:2 · 好信源:1 · 好思考:1
事实 (fact) (6)
- 2026-06-21 · experiment turnaround speed claim
That gives us a quick experiment turnaround.
tags: 好思考 · → daily
value: qty=quick experiment turnaround
- 2026-06-22 · can train on new game faster than LLM fine-tune
We can train it on the 11th game in less time than it takes to fine tune an LLM on the 11th
tags: 好观点 · → daily
- 2026-06-21 · deep learning research tenure
I've been in deep learning research for over a decade.
tags: 好信源 · → daily
value: qty=over a decade
- 2026-06-21 · training speed claim: 50k param model
We use a 50k param model because we can crank 10M samples per second on it (20 once optimized).
tags: 好数字 · → daily
value: qty=10M samples per second
- 2026-06-21 · general method solves entire problem class
The method I am working on is fully general in that it solves an entire class of problems that we cannot otherwise solve with existing methods.
tags: 好观点 · → daily
- 2026-06-21 · training comparison with alternatives
Maybe we 'only' train many client problems at 5M steps/second, but the most common alternatives train 5k steps/second. I routinely see people working in the 100s of steps/second. So in order to solve the same problem that we solve on 1 GPU, you need a 1000 GPU setup, and you don't have infra for that.
tags: 好数字 · → daily
value: qty=1000x speedup
时间轴 (近 20)
- 2026-06-22 ·
fact · can train on new game faster than LLM fine-tune · → daily
- 2026-06-21 ·
fact · deep learning research tenure · → daily
- 2026-06-21 ·
fact · training speed claim: 50k param model · → daily
- 2026-06-21 ·
fact · experiment turnaround speed claim · → daily
- 2026-06-21 ·
fact · general method solves entire problem class · → daily
- 2026-06-21 ·
fact · training comparison with alternatives · → daily
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