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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01 AI
7 atoms · 跨 2 天 · 首见 2026-06-24 · 最近 2026-06-25
三色: 🟦 fact 6 · 🟥 take 1 · stance ▲4/▼0/◆1
来源: X 7
时态: fresh:7
标签: 好数字:5 · 好思考:1 · 好观点:1
🟨 AI 综合 · junior analyst 概览
展开 AI 综合 (灰色 · 非市场结论 · 点击数字溯源到原 atom)
model: deepseek-chat · 2026-06-30 · 默认折叠
01 AI 2026 年合约书金额达 15 亿人民币，是 2025 年合同量的 3 倍
¹¹。客户覆盖中亚、中东及东南亚的政府与企业
¹。Palantir 类比赋予 01 AI 更好的叙事
¹，但并非每个类比都能在中国企业销售周期中存活
¹。这形成核心分歧点：对标策略的适用性
¹¹。近 7 天新增 8 个 atoms，企业市场与合同金额成为新话题
¹¹。
💢 核心分歧 (1 轴)
1. Palantir类比在中国企业市场的适用性
*topic: 类比叙事/市场定位/企业市场 · 1 bull vs 1 bear*
🟢 bullish 侧:
🔴 bearish 侧:
📏 估计带 (1)
*语料内对同一量的估计区间 (≥2 个估计才成带). 不判断谁对, 只陈列.*
- 营收 2026: $1.5B · 2 个估计 · 最新 2026-06-24 $1.5B (
X·cred3)
📊 程序化变化 (近 7 天)
- 新增 8 atoms
- 本周新 topic: 企业市场/合同金额/客户地域/对标策略/市场定位
🟦 客观事实 (facts) (5)
🟥 多头 takes (bullish) (1)
🟥 空头 takes (bearish) (1)
🟥 中性 takes (neutral) (1)
⏱ 时间轴 (近 20)
- 🟥 2026-06-25 ·
narrative · 类比Palantir · → daily
- 🟦 2026-06-24 ·
fact · 合同总额 · → daily
- 🟦 2026-06-24 ·
fact · 订单量同比 · → daily
- 🟦 2026-06-24 ·
fact · 2026 签约合同额 · → daily
- 🟦 2026-06-24 ·
fact · 2026 签约合同额同比 2025 增量 · → daily
- 🟦 2026-06-24 ·
fact · 客户构成 · → daily
- 🟦 2026-06-24 ·
fact · 2026 合同金额 · → daily
*以下是 Chinese AI labs 板块的信号 (01 AI 是成员), 非直接针对 01 AI — 供板块上下文参考*
展开板块信号
- 🟥▲ 2026-06-13 [twitter] · 价格竞争力
There’s also really competitive offering from chinese labs out, quality is usually a year behind latest gen but for 10%
- 🟦▲ 2026-06-07 [twitter] · gap 10 years ago
Chinese labs were 10 years behind (per The Economist), now they are 6 months
- 🟥▼ 2026-06-10 [twitter] · 面临美国网络攻击风险
They want to rugpull Chinese labs – no, the entire Chinese IT, if not the whole infrastructure of the society – near the
- 🟥▲ 2026-06-07 [twitter] · gap to frontier closed models
the difference is at max 6 months
- 🟥▲ 2026-06-07 [twitter] · fundamental capability gap
There is no fundamental human resource capability gap. It is compute and $$$ and datasets.
- 🟥▼ 2026-06-04 [twitter] · 停止发布开放权重模型的影响
If they stop, the frontier falls further and further behind to those who want to use local/fine-tuned models
- 🟥▲ 2026-05-31 [twitter] · resource advantages relative to US labs
cheaper energy, more abundant AI researchers and the ability to distill and learn from leading US models, but less capab
- 🟥▼ 2026-07-01 [twitter] · would not economically survive Anthropic competition
Chinese AI labs would not economically survive the juggernaut of Anthropic - unless China took drastic steps
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