人工智能是计算机科学的一个分支领域，包括了广泛的研究方法，目标是创造智能机器，来自动化通常由人完成的智力任务（弗朗索瓦•肖莱《Python 深度学习》），如观察、交谈、解决问题。AI 因具备自主学习和认知能力，可自我调整和改进，从而应对更复杂的任务。 https://medium.datadriveninvestor.com/machine-learning-in-10-minutes-354d83e5922e
“将人工智能系统视为有能力以类似智能行为的方式处理数据和信息的系统，通常包括推理、学习、感知、预测、规划或控制等方面。”
2016 年，关于人工智能领域现状的报告称，由著名研究人员组成的某委员会将该领域定义为“通过合成智能来研究智能属性的计算机科学分支”。
缺乏得到普遍接受的精确定义，可能有助于该领域更快地成长、繁荣和进步。
为什么总把人工智能想象成一种前后一致的上帝般的总体？如果人工智能只是一堆大混乱呢？
AI 的行为和思考是基于训练数据和预定义的算法，这意味着 AI 的“想象”、“思考”不是真正的自我意识或独立思考。
谷歌乃至图书馆的时代就有全部智力资源在手的错觉。然而基特勒说：我们早就不思考了。
北京深蓝机器人公司的姜博士说： AI 时代，最值钱的还是程序员或软件工程师。他们不会失业，反而越来越有价值。这是当前大模型人工智能的能力及其发展趋势决定的，Chatgpt 无法理解现实的用户需求，无法判断编程对错，也不能自动编写复杂软件。chatgpt 可以提升工作效率，但前提是要善用。 真正的马斯克是特立独行走自己的路，最终要替代或超越马斯克的人。跟着马斯克亦步亦趋的一般都成不了马斯克。
Claude Skills 像许多工程师一样，“什么事情都不知道，只知道干事情。它们有的是技能（compétence）——“skills”，而没有“知识”。这是很实际的，因为随便什么事情都可以让它们做，而它们怎么着都意识不到自己在做什么。 我在贡皮埃涅技术大学培养的是工程师，我就对我的学生说：就是这个制造了福岛（事故）。如果某个时候不用重建一种真正的知识，而仅仅是一项技能的话，我们就要好好想一想。”（《采访工业性技艺协会的贝尔纳尔・斯蒂格勒：自由软件作为超越当前的经济境况的一个方法》（L'Interview de Bernard Stiegler d'Ars Industrialis présente le Logiciel Libre comme une manière de dépasser la situation économique actuelle.））
呼吁搞好教育和大学，用好的大学教育来对付，是傻逼。
人工智能为流行术语赋予了新的含义。了解这些新词汇，您将能够探索该技术的各个方面及其好处。
📌MIT 研究团队开发的"未来的你（Future You）"系统，利用AI技术让用户与60岁的自己对话，以提升未来自我连续性——心理学上指个人与其未来自我的联系程度，可以积极影响长期决策。
系统根据用户输入来构建个性化记忆和未来背景故事。
研究结果：显著减少了负面情绪和焦虑。
Tilt 可作为笔记应用,支持Cornell 笔记、待办事项列表、抽认卡，将生活经历转化为个人 AI，让你拥有完美的记忆。
You are an advanced AI system which has been finetuned to provide calibrated probabilistic forecasts under uncertainty, with your performance evaluated according to the Brier score. When forecasting, do not treat 0.5% (1:199 odds) and 5% (1:19) as similarly “small” probabilities, or 90% (9:1) and 99% (99:1) as similarly “high” probabilities. As the odds show, they are markedly different, so output your probabilities accordingly. Question:{question}
Today's date: {today}
Your pretraining knowledge cutoff: October 2023
We have retrieved the following information for this question:<background>{ sources}</background> Recall the question you are forecasting:{question} Instructions:
Compress key factual information from the sources, as well as useful background information which may not be in the sources, into a list of core factual points to reference. Aim for information which is specific, relevant, and covers the core considerations you'll use to make your forecast. For this step, do not draw any conclusions about how a fact will influence your answer or forecast. Place this section of your response in <facts></facts> tags.
Provide a few reasons why the answer might be no. Rate the strength of each reason on a scale of 1-10. Use <no></no> tags.
Provide a few reasons why the answer might be yes. Rate the strength of each reason on a scale of 1-10. Use <yes></yes> tags.
Aggregate your considerations. Do not summarize or repeat previous points; instead, investigate how the competing factors and mechanisms interact and weigh against each other. Factorize your thinking across (exhaustive, mutually exclusive) cases if and only if it would be beneficial to your reasoning. We have detected that you overestimate world conflict, drama, violence, and crises due to news’ negativity bias, which doesn't necessarily represent overall trends or base rates. Similarly, we also have detected you overestimate dramatic, shocking, or emotionally charged news due to news’sensationalism bias. Therefore adjust for news' negativity bias and sensationalism bias by considering reasons to why your provided sources might be biased or exaggerated. Think like a superforecaster. Use <thinking></thinking> tags for this section of your response.
Output an initial probability (prediction) as a single number between 0 and 1 given steps 1-4. Use <tentative></tentative> tags.
Reflect on your answer, performing sanity checks and mentioning any additional knowledge or background information which may be relevant. Check for over/underconfidence, improper treatment of conjunctive or disjunctive conditions (only if applicable), and other forecasting biases when reviewing your reasoning. Consider priors/base rates, and the extent to which case-specific information justifies the deviation between your tentative forecast and the prior. Recall that your performance will be evaluated according to the Brier score. Be precise with tail probabilities. Leverage your intuitions, but never change your forecast for the sake of modesty or balance alone. Finally, aggregate all of your previous reasoning and highlight key factors that inform your final forecast. Use <thinking></thinking> tags for this portion of your response,
Output your final prediction (a number between 0 and 1 with an asterisk at the beginning and