谁能绷住？😂

Oppo 心力球和 Anker 录音豆的区别 1、安克和飞书的产品经理，可能对录音这个事情有什么误解，他们觉得一天录半个小时就可以了。如果你是想收集全天上下文，就算开了他们那个会员，额度都不一定够你用 2、心力球的产品经理绝对是一个重度 AI 用户。这个产品续航长达 24 个小时，只要挂在身上，你就不用管了。它不留录音，会自动概括文本内容。然后你的所有的 Agent 都可以通过 MCP 获取这个内容，你的微信 Clawbot 也可以。所以虽然心力球 APP 里面内置了一个 Agent，但这个 APP 是不用打开的。通过微信、飞书、codex、claude code、grokbot 都可以访问 3、一天录音几个小时，一个月下来就是几百个小时。真要处理这么长的音频文件，对我来说成本极高，收益也不大。录音只是在高密度对话的时候有价值，那个时候用手机录音就可以了，我不太需要单独买个硬件。 4、对我来说，有价值的就是把每天大量的文字总结出来。让我知道我什么时间干了什么。我可以随口一句话告诉这个心力球：我喝咖啡了，我喝奶茶了，我喝酒了，我睡觉了，我醒了。就算你带了 Apple Watch，也不知道你今天下午 3 点吃了维生素。但是我可以一句话告诉心力球这个数据。 缺点：只能连接Oppo手机 优点：我恰好有个Oppo手机🤣

Dusting off this tweet from April because this gap in shared understanding of LLM capability is *widening*. It's now less "two groups of people speaking past each other" and more a sharp funnel. - Napkin math somewhere around 6B people (~75% of the population) have barely come in contact with LLMs at all. - Around 1-2B (~20%) are casual and infrequent users of free-tier ChatGPT-like products. This group sees derpy chatbots and treats them a bit like a better Google search, a writing aid, or etc. Maybe an agent tries to book you a flight. I have non-tech friends who (reasonably, imo) say they have not much use for it at all. Even many professionals outside of math&code are in this tier. For example, execs and many other functions spend a lot of their time talking to other people, so while they understand what is happening intellectually, it is still second-hand and a bit abstract. - Now we get to professional use of frontier-grade LLMs in math&code. Somewhere around 20M people (0.2%) see first-hand that large, complex projects that used to take them weeks/months can now be completed by agents with a prompt. Building apps, copying apps, translating apps, decompiling apps from binaries... This has all happened very quickly and recently - less than 1 year ago, I was writing code manually by hand, typing memorized computer code commands into a code editor character by character, occasionally pressing Tab to autocomplete a little chunk of code. - And finally we get to the ~5,000 people (~0.00006%) with access to frontier-grade systems internally. The external world has seen the preview. It looks like swarms of thousands of agents collaborating over weeks on software mega projects: minting zero days, running cyber attacks and defenses at machine speeds, discovering new science, advancing the frontier of mathematics. Things that would have taken top professionals in the industry years of work. Meanwhile, human review and comprehension are starting to fall behind. For example, people are still involved in the "archeology" of the OpenAI-HF incident from many months ago. Mathematicians may be poring over the 722 manuscripts on frontier mathematics for a while. The funnel is driven by a combination of factors: 1. The impact scales with ambition, problem size, and horizon. A question with a paragraph answer barely stresses the system. You need a reservoir of big, difficult problems that you really care about. This aspect drives the consumer / professional dimension of the funnel. 2. The jaggedness of the system (which I have written about a lot separately). Capability peaks in domains that are digital, verifiable and economically valuable. This is because LLM capability emerges from reinforcement learning on verifiable rewards on a curated environment mixture driven by revenue potential. This aspect primarily drives the area (e.g. math&code) dimension of the funnel. 3. Access. Free-tier, paid-tier, internal. So this is the weirdness of the moment. The general public has mostly not interacted with these systems. When they have, it looks like a derpy chatbot. The majority of professionals still see only a modest uplift. And a small sliver of professionals are experiencing the vertigo of the curve going vertical. And it is all happening at the same time.

Grok Bot now has its own email. Bot can use it to sign up for services, contact businesses for you, or schedule time with someone.