# 前OpenAI创始人Naomi Bashkansky正在构建思想转文本技术，指出实现关键在于大幅增加计算量而非精巧算法

- 来源：Chubby
- 发布时间：2026-08-06 17:18
- AIWatch 分数：51
- AIWatch 标记：未精选
- AIWatch 链接：https://aiwatch.icu/events/evt_01kzb6hxqaqndmaf1x6vnm741d
- 原文链接：https://x.com/kimmonismus/status/2085294442529874357

## 精选理由

低价值或偏离 AI-Dev

## AI 摘要

前OpenAI创始人Naomi Bashkansky正在构建思想转文本技术，指出实现关键在于大幅增加计算量而非精巧算法。

## 正文

How to achieve Thought-to-text? Simple: More compute:

"To train models that can predict text given brain signals, we must apply the same lesson learned by those predicting text given speech audio, or text given preceding text: the bitter lesson.

The lesson roughly states that you should throw more useful compute at your model, and your model will become better than any ingenious algorithm you could've hand-crafted. That means we must scale up our data collection by orders of magnitude beyond what has ever been done in academia."

Things will get very weird.