The release includes DeepSeek-V4-Pro (1.6T total / 49B active) and DeepSeek-V4-Flash (284B total / 13B active), both trained natively at 1M context length.
DeepSeek V4的模型规模之大令人震惊,这表明了在长上下文处理方面取得的显著进步。
The release includes DeepSeek-V4-Pro (1.6T total / 49B active) and DeepSeek-V4-Flash (284B total / 13B active), both trained natively at 1M context length.
DeepSeek V4的模型规模之大令人震惊,这表明了在长上下文处理方面取得的显著进步。
Closed harnesses behind proprietary APIs force yielding control of agent memory to third parties.
令人惊讶的是:专有API背后的封闭式代理工具迫使用户将代理记忆的控制权让渡给第三方。这意味着用户在使用AI代理时可能不知不觉地失去了对自己数据和个人信息的控制权,这可能引发严重的隐私和安全问题。
Within a few months, they have more than a dozen production enterprise deployments & are processing over a billion events per hour.
令人惊讶的是:Artemis安全公司在短短几个月内就处理了每小时超过10亿个安全事件,这种数据处理规模反映了现代企业面临的网络安全威胁的惊人频率和复杂性。
Maine advances first statewide moratorium blocking data centers requiring over 20 megawatts
令人惊讶的是:缅因州将成为美国第一个全范围禁止大型数据中心建设的州,这一政策针对的是超过20兆瓦的数据中心设施,这在科技发展迅速的今天显得格外独特和出人意料。
the most interesting detail here is how SkillClaw clusters cross-user trajectories into referenced skills and then uses the evolver to translate those patterns into concrete updates.
令人惊讶的是:SkillClaw能够将跨用户轨迹聚类为参考技能,然后使用进化器将这些模式转化为具体更新。这种处理异构用户经验的方法非常巧妙,它不仅解决了不同用户间信号差异的问题,还能从看似无关的用户行为中提取有价值的模式,实现真正的集体智慧。
We test for a trend over time by fitting a weighted linear model to the log-odds of usage. Under this specification, Claude is the only AI service in the survey to show a statistically significant upward trend over this period
令人惊讶的是:研究团队使用了对数几率加权线性模型来分析趋势,发现Claude是唯一一个在统计上显示出显著增长趋势的AI服务。这种复杂的统计分析方法揭示了表面上微小变化背后的真实趋势。
The ChatGPT for Excel add-in operates separately from your ChatGPT chat history. Conversations and data in Excel aren't shared with your ChatGPT chats, and activity doesn't sync between experiences at this time.
令人惊讶的是:Excel中的ChatGPT功能与普通聊天历史是完全隔离的,两个系统之间没有数据同步。这意味着用户可以在Excel中使用AI处理敏感数据,而不用担心这些信息会出现在他们的常规聊天记录中,提供了额外的隐私保护层。
By default, data shared with ChatGPT isn't used to improve our models for ChatGPT Business, ChatGPT Enterprise, ChatGPT Edu, and ChatGPT for Teachers.
令人惊讶的是:企业级用户的Excel数据默认不会被用于训练AI模型,这与普通用户的数据处理方式有显著区别。这种差异反映了OpenAI对商业客户隐私的特别保护,可能是为了增强企业采用AI工具的信心。
we collaborated with over 1,000 physicians to curate training data that enables more factual and comprehensive responses.
令人惊讶的是:为了提升Muse Spark在健康领域的推理能力,Meta竟然与超过1000名医生合作来筛选训练数据。这种规模的专家参与在AI模型开发中极为罕见,显示了Meta对医疗健康领域准确性的高度重视,也反映了AI模型专业化训练的新趋势。
Support teams are high volume and high turnover, and thus need to train new reps in a fast and standardized way. To do so, they have clearly articulated standard operating procedures (SOPs) that guide the work of each rep. These SOPs create clear rules and guidelines that AI agents can model themselves off of.
AI 在客服领域成功的秘密竟然是:这个行业为了管理人类员工的高流失率,被迫建立了极其清晰的 SOP 文档——而这恰好是训练 AI Agent 的完美素材。这是一个意外的历史巧合:企业因为人类问题(高离职率)被迫文档化了所有流程,然后 AI 来了,直接把这些文档变成了自己的「培训手册」。低价值工作被最彻底地文档化,反而最容易被 AI 替代。
MiniMax may have been able to get 100 billion tokens of data from interactions with Claude.
100 亿 token 的 Claude 交互数据——这个估算令人瞠目。这意味着 MiniMax 的用户在不知情的情况下,可能成了为 Claude 蒸馏数据的「采集器」。从 Anthropic 的角度看,这是商业数据被盗用;从竞争视角看,这说明 API 开放策略本身就是一把双刃剑——越开放,越容易被「逆向汲取」。
Legitimate Interest may be used for marketing purposes as long as it has a minimal impact on a data subject’s privacy and it is likely the data subject will not object to the processing or be surprised by it.