AI 行业热点
🐦 X/Twitter 热点
Andrej Karpathy (@karpathy)
- More on the pelican on the bicycle test from @simonw:
I uploaded the source here so it’s playable in the browser, forkable etc.
Look out for GTA Hobbiton dropping before GTA VI :) [392 ❤️ 14 🔄]
Swyx (@swyx)
- haven’t seen a full cycle of this guy but this place absolutely can chew you up and wastes 10 yrs of your life making you feel like you are doing something when you are not [2 ❤️]
- in prep for our computer use pod, gonna store a running list of codex cua wow moments.
here it is dealing with support chat for me to escalate for faster resolution
these humans have no idea they are talking to a bot
support guy tried to say its our fault, bot replied with complete receipts lmao [3 ❤️]
- @akshaynathan_ @AriX live now! [6 ❤️]
Peter Yang (@petergyang)
- Went to a community center in Canada and it has a full swimming pool, jacuzzi, sauna, and even lazy river.
In the most expensive Bay Area neighborhoods, the community center is just a fancy building with empty rooms that you can rent. [96 ❤️ 2 🔄]
- One of the biggest benefits of Hermes is that it builds its own skills to help you get work done.
But I had to ask @karan4d, @NousResearch co-founder: “How does Hermes avoid slop while doing this?”
Here’s his response:
“Hermes Curator [a background task] runs inside your agent and cleans up your skills and memory on a schedule, asking: Where’s the slop, and where can I make it more efficient?
And because it’s open source, you can hand it your own definition of slop and it rewrites its own cleanup loop your way.”
📌 Watch the full episode here: [90 ❤️ 7 🔄]
- Personality matters! A smart friend that’s annoying to talk to is no good. [186 ❤️ 6 🔄]
Thariq (@trq212)
- i think there are lots of parallels to what happened with chess [73 ❤️ 1 🔄]
- you can already see Jevons paradox at work in mathematics
there is more happening, it is easier to understand and mathematicians have more time to discuss it with us at higher abstraction levels
demand for people who think and know about math will go up [1191 ❤️ 43 🔄]
Amjad Masad (@amasad)
- Woah [91 ❤️ 3 🔄]
- You can watch the games live on the website. Mf is playing 3 concurrent games rn [16 ❤️]
- My LLM chess engine is now on LiChess autonomously playing real games against people and bots.
1253 Elo: [215 ❤️ 10 🔄]
Guillermo Rauch (@rauchg)
- PS: we’ve obviously had agents for a while. In fact, we had too many. Teams and individuals at Vercel started building and deploying agents. Dozens of them.
Using a web analogy, that’d be like every agent having its own domain name. Not a good UX. I just want ${company}.com!
@𝚟 solved that problem for us. It’s both an agent and a router. It has sub-agents, skills, and it knows how to delegate work to other agents.
Another analogy is that it’s a bit like a “monolith” or “monorepo”, but you have the escape hatch of “proxying” to another agent over the network when needed. Again, not unlike how routing on the internet evolved at scale.
And yes, there’s also the occasional purpose-built agent that people address directly. The analogy would be subdomain.company.com. Some agents deserve their own “front doors”, but I don’t think there should be too many.
And when in doubt, just @𝚟. [66 ❤️]
- We built an agent that powers our company’s internal operations called @𝚟.
Every day-to-day job at Vercel now involves @𝚟. It’s growing exponentially both in daily interactions and token use.
One can extrapolate to the day AI agents run entire companies from here. It’s an expert in finance, comms, docs, marketing, engineering, business analytics. It’s seeded by the skills we gave it and we update, but it’s also constantly improving.
It already keeps memories and personalized workflows and schedules on a per-user basis. For example, I knew skills.sh hit 1M skills and I shared this on these forums because I asked @𝚟 to periodically check and remind me.
It’s powered by and is also the basis for the design of @evedev_. We built this, it works fantastically well, we think every company should have it.
Before you @ me, I know you could also do this by picking your ‘BigAI slack integration’ du jour. But that’s not your agent, that’s their agent. If agents become the foundation of (and even synonymous with) modern companies, you being in complete control, from source → runtime → data → token, seems like a pretty big deal to me. [1233 ❤️ 47 🔄]
- AI alone is cool. But mastery + creativity + AI hits on a whole different level. Don’t let anyone discourage you from pursuing excellence and craft. Keep studying the blade. [3662 ❤️ 359 🔄]
Aaron Levie (@levie)
- We’re going to be in for a strange dynamic which is that some of the “hardest” work in the world is actually prone to automation first, particularly due to its verifiability.
Math, cyber, and code -while being insanely hard and high value fields- have the benefit of being able to be tested that it’s correct objectively. This has two immediate benefits: the training of the models offers clearer reward signals, and then the running of the models allows you to know that it’s working properly because you can test the results in a scalable way.
Conversely, in other domains of work, there’s much less instant verifiability. Which legal clauses your client will agree to, what marketing campaign to run with based on changing sentiment, which message your sales prospect will want to hear, what financial targets and budget to set for a business, and so on.
All of these domains have changing internal and external factors, they don’t have “one right answer”, they rely on the opinions and risk levels of the operators, they’re highly sensitive to getting the right input context first, and in many cases the right answer can’t even be known for quite some time after the model generates the results.
The implications of this distinction are that -even as model capability continues to increase exponentially- there will be a lot done at the applied AI layer than just the the model itself, and much of the processes themselves will even need to change over time to get the full gains from automation. We may even need all new capabilities to be able to “test” knowledge work over time as we have had with software. [318 ❤️ 26 🔄]
Ryo Lu (@ryolu_)
- my early mentors were these apps, especially Rdio, Mailbox, and Apple
they made new patterns that made software feel simpler and intuitive to touch
as we leave the world of apps behind, what parts of software will remain visible, and how could it feel? [390 ❤️ 6 🔄]
Garry Tan (@garrytan)
- Growth is good
AI will create unimaginable economic growth and that is the best white pill [302 ❤️ 30 🔄]
- The sense of wonder disappeared right at the moment the amount of wonder is going parabolic [173 ❤️ 6 🔄]
- Everyone mistakes the map for the territory
Meritocracy is that the territory matters more than the map
And in markets the outcome is the territory: did you make something people want? [195 ❤️ 8 🔄]
Nikunj Kothari (@nikunj)
- Warm NYC nights are magic 🪄 [416 ❤️ 2 🔄]
- What a wild world we’re living through. I wrote about the Series A squeeze recently. Here’s what else I’m seeing from my seat on the investing side..
- VC has effectively fully become vibes capital. The market reality at the early-mid stage is completely divorced from fundamentals. I can go longer with even a resemblance of a straight face predict what happens to a company when they go to fund raise.
Some rounds are insanely wild with nothing to show, some rounds that seem like a sure shot are struggling to raise the capital they need. If you’re the “in vogue sector”, you’ll be just fine. This has been happening for some while but it’s fully banana town now. And unlike most who think a correction happens I think this continues for 12-18 months (dry powder, AI tailwind) minimum. The most common phrase in VC land right now is “you gotta play the game on the field”. This is a spiral that continues to keep the volatility and prices high.
- Whereas on the public markets it’s also equally bananas. It used to be in the meme stock era that you’d see daily swings of >5% (+-). But now even trillion dollar stocks are not immune to swinging that much based on vibes and model releases. Memory and the KOSPI index are recent examples and this will happen to other sectors soon. Rotations are getting faster and faster.
In the long run, the same fundamentals of building a great company with control of your own destiny (profitable, clean cap table etc) will end up just working out fine. But in the short term, in this vortex of hyper competition where capital is needed as a weapon, you should make sure you understand what’s going on before you dip your toes in the capital markets.
No matter what it’ll be interesting to see how this shakes out when we look back in this era. Obligatory happy to chat if helpful! [372 ❤️ 21 🔄]
Peter Steinberger (@steipete)
- That’s a fairly new kind of spam. [271 ❤️ 7 🔄]
Dan Shipper (@danshipper)
- if you haven’t read War and Peace or some of the historical accounts of this like With Napoleon in Russia, you should [10 ❤️ 1 🔄]
- when you experience a language model doing a task that used to require you at every step and now doesn’t, it’s a gigantic agency rupture.
we tend to equate ourselves with our tasks, our outputs, and a rupture of this kind is akin to the loss of your identity and sense of self.
you are no longer required, and you had no say in the matter. it’s a kind of death.
however, agency ruptures with AI seem to follow a predictable pattern:
Initial agency rupture. Here you see the AI doing what you used to do, and you see only the AI. In your perception of reality the AI is highlighted, and the human work around getting the AI to do the thing, is invisible. you can see this in the way we use language: “AI solved XYZ Erdos Problem” is another way to say we’re in the initial rupture phase.
Seeing human scaffolding. After a little bit of experience with the model and its new capibility—programming, writing, math, etc—we start to see the edges of what’s possible with the model. Here, instead of just seeing the AI doing the task, we start to see the scaffolding required by you and other humans on either end to make sure the model does its work. At this stage, the scaffolding can feel like a secondary part of the work, but it is work nonetheless. We begin to say things like, “The AI is prompting me”, or “My job is just to babysit Claude.”
Agency reconstruction. After a long enough time with the model at its current level of capability, we start to reconstruct a new sense of agency that centers our own role in the work being done, and makes the model’s contribution mostly invisible. It is now a tool, it fast-forwards you through the boring or repetitive parts of the work, and what used to seem like scaffolding now seems like the actual work itself—the interesting part. You’ve had enough experience with the scaffolding to see its nuances, and how hard it is to get the model to reliably output high quality work. (As part of this, your conception of what quality work is changes—the floor is raised, and so is the ceiling.)
You can tell you’re at this point because you stop saying “The AI did this” and just say, “I did this” and the fact that you used AI is implied. For example, it would be weird for me to talk to someone @every and ask them if the AI built the most recent feature of a product. Of course it did! But we’re so used to the capability that it becomes invisible, and we re-center ourselves and our own conception of agency.
My theory is that the ability to metabolize agency ruptures and turn them into playfulness, and curiosity is a good leading indicator for whether you’re a person who likes and excels in the new AI economy or not.
Each time capabilities jump, you get new ruptures for existing fields touched by AI. And you get new ruptures for naive populations (like mathemeticians) who until recently hadn’t been affected.
if you know what the cycle looks like, it makes it much easier to ride it without freaking out. i think most people @every are naturally good at this [192 ❤️ 17 🔄]
- if ought implies can, and technology reshapes the field of human abilities—then technology reshapes oughts.
we should expect AI to fundamentally change our moral intuitions at the same time as it changes our abilities [18 ❤️ 1 🔄]
由 Follow Builders 自动生成 · 2026-08-03