#大佬观点

Grok @Bot has made a few simple yet powerful technical decisions that I believe make it easy and enjoyable to use. 1. The best UI is none at all. The product interface is dramatically simpler than alternatives without sacrificing functionality. How is this possible? It's one of the first products designed for current frontier model capabilities and has a UI restrained enough to remain easy to use as models improve exponentially. Everyone knows how to text. 2. A thin harness for the client, a thick harness for the server. You might have noticed the app feels very fluid to use, even for a beta product. This is primarily because of everything we didn't have to build. The app harness is essentially a single tool to send messages between the client and server. The complexity moves to the server, where you can still use the coding agent harness with specialized tools as needed. This helps make the UI fast and responsive on desktop and mobile. 3. An always-on computer. Most coding agents and assistants today start fresh with every question you ask. Some of these sessions are on your local machine and others happen in the cloud. We believe strongly that cloud is the future, which is why it's the only option. Further, rather than spinning up virtual machines for every conversation, your bots connect to their own computer. This means you can still run agents on the bot's persistent filesystem. It's closer to what programmers have been doing by using Tailscale from their phones to connect to a remote computer and run an agent TUI. You get those capabilities without the hassle. 4. Your bots can use the browser. Coding agents have shown that most work on a computer can be expressed and run as code. You can ask for a task in natural language and the agent will decide to write a script to complete it. This is amazing, but there's still many tasks which can't be completed without logging into a website and clicking around the browser. Models and harnesses are now good enough to reliably handle this. The combination of writing code and using browsers means you can automate almost any task on a computer. Further, you can ask Grok Bot to record you doing the task, and then turn it into something repeatable.

Has any of the AI companies ever presented a real plan for how they are going to cure even one disease in 5-10 years? This doesn't just sound crazy to ordinary people, but also to any clinician or drug developer I know. Beyond the fact that we still have very few true cures for chronic diseases, simply running a phase 3 trial to test if a potential treatment for cardiovascular disease actually works takes five years (e.g. ZEUS). I've said this before, but one thing that working in hospitals teaches you is to respect disease.

PRO TIP: If you’re not using Grok @bot you’re missing out. It has replaced OpenClaw, Hermes, & my local model ($10K Mac Minis). Get a Comet Pro Remote KVM to let the bot access your Mac environment. I’m going to sell my Minis (for more than I paid) next week.

18x improvement in intelligence per joule in 16 months.

For about 10 years now, I have argued that the *only* way forward is for AI technology to be widely available, shared, and open. Like the printing press and the Internet, AI amplifies human intelligence and efficiency by improving access to knowledge. To empower individuals, societies require a high diversity of AI systems with different value systems, linguistic abilities, philosophical/political biases, and specific expertise. We need diverse AIs for same reason we need a diverse press. Given the cost and complexity, this can only be achieved through open foundation models on top of which anyone can build systems with their languages, biases, expertise, and value systems. I have been more vocal about this over the last 4 years, since AI popped into the public discourse. I have made the argument in various forums: corporate C-suites, AI safety discussion groups, professional meeting, the US Senate, the UN Security Council, and the public sphere through media interviews, podcasts and social media posts. I totally agree with @finkd Mark Zuckerberg's recent piece in which he writes: "the notion that AI is so dangerous that the only safe path is an extreme concentration of power seems inherently problematic. Historically, hoping that an absolute power will benevolently provide for humanity if sufficiently enlightened has not led to safe or positive outcomes.” When @DarioAmodei writes: “some may object that we can simply keep AIs in check with a balance of power between many AI systems, as we do with humans", he is talking about me, among (thankfully) many others. It is the only good path forward. There will be nefarious uses of AI, as there have been with every technology ever invented. But it will be your Bad AI against my Good AI.

1/2 Thanks Gavin for an especially thoughtful exchange. I don't usually spend much time on social media but I wanted to engage here because it really brings out the heart of an important conversation. First, on regulation, I think that “either concentrate it in the hands of a chosen few companies and politicians via regulation or distribute it widely” is a false choice.  I know that there’s a sort of Silicon Valley shorthand where regulation = regulatory capture = concentration of power, but I’ve always found this to be an overly simplified picture of the world.  Many people outside this bubble think of regulation as something that constrains corporate power and benefits ordinary people.  I don’t necessarily agree with that perspective either, rather I think it’s complicated and really depends on what the “regulation” consists of.  But in particular I think that those in the “regulation = regulatory capture = concentration of power” frame often underrate the decentralizing power of objective and fair institutional processes.  A crude analogy is that the formal court system can sometimes feel stuffy and elitist, but it does a much better job of defending the rights of vulnerable individuals than the alternative, mob justice.  At their best, institutions can vest power in ideas rather than people, and thereby decentralize that power. This is why Anthropic has always made its policy proposals very carefully.  We try very hard to make proposals that disadvantage (slow down) frontier AI companies while *advantaging* smaller competitors.  California’s SB53 (which we supported), and even the much-maligned SB 1047 (which we were ambivalent on), completely exempt any company below a certain amount of revenue or model training costs from being covered at all (it was $500M for SB 53, lower for 1047 but we objected to that).  More recently the testing process we’ve advocated for at CAISI and the White House involves more rigorous tests for frontier models than off-frontier models — something that differentially advantages challengers.  Similarly, the “Pacing the Frontier” letter envisions (or at least Anthropic’s preferred implementation of it envisions) modulating the pace of the very best models while not constraining those who are catching up.  This hurts the business interests of the frontier labs and helps challengers, including open-weights! Overall my view is that AI is *structurally* a technology that tends to concentrate power, for reasons that have nothing to do with regulation (more to do with the extreme implications of the scaling laws).  Open-weights do help some with this but are nowhere near a sufficient solution because they simply shift the concentration somewhat to those with the most compute and chips (which are roughly the frontier labs plus maybe hardware providers).  By contrast I think the right “rules of the road” can simultaneously (a) address AI’s cyber/bio/alignment risks, (b) institutionally constrain the power of the frontier AI companies, and (c) leave room for open-weights models while also addressing the specific risks that they bring. BTW I do not think that the events of the last few months have “failed to result in [my] preferred regulatory path”.  The approach that the Trump administration is reported to be taking — pre-deployment testing for frontier models, and also testing of open-weights models when they get closer to the frontier — is one that I am very supportive of, though of course I have to see the details to be sure.  I am also supportive of Demis Hassabis’ ideas around a FINRA-like entity.  This contrasts with six months ago when most of the industry was still pushing for preemption of all state regulation and no apparent federal approach either.

2/2 Second, on the messaging around AI.  I do not agree that my messaging has been disproportionately negative.  In fact it has been about equally balanced between risks and benefits: I’ve written one major essay about each, and even in interviews where I discuss the risks, I make sure to frequently mention the incredible benefits as well as proposing possible solutions to the risks (short clips from my interviews that end up on social media tend to be disproportionately negative, as that gets clicks).  In fact, I wrote Machines of Loving Grace because I didn’t feel the AI industry was painting an inspiring enough picture of how the technology could radically transform the world for the better.  The bulk of the essay is devoted to refuting skepticism of AI’s potential in health and biology, and showing why I think it will actually be possible to cure most human disease in ~5-10 years, as crazy as it may sound to ordinary people and frankly to biologists as well (I used to be one!).  And, if you read my most recent essay (Policy on the AI Exponential), I discuss concrete proposals for how to streamline the FDA process to make sure the deluge of AI-accelerated drugs isn’t slowed down by the regulatory process.  I feel the urgency here: I lost my father to Hepatitis C only a few years before the development of direct-acting antivirals (sofosbuvir), which cure 95% of patients and probably would have cured him. I do agree that the public has a negative view of AI (and that this is a big problem), but I don’t think it is primarily caused by me or any other AI leader warning about AI’s risks.  I think it is fundamentally a crisis of trust.  I think that ordinary people don’t trust companies, governments, or the tech industry and always suspect that we are cooking up some new way to screw them over.  The causes of this go back decades and AI is just the latest iteration of it.  I don’t think that a glitzy marketing campaign with a positive spin (which some have advocated that Anthropic do) is the way to win back that trust — at this point, saying that AI will cure cancer is more a cliche than it is inspiring, and most people think it is deceptive.  The thing that will work is *actually curing cancer*.  I think by far the most accurate criticism of AI companies including Anthropic is that we haven’t yet delivered on our big promises to benefit the world.  That is totally on us, and I think it’s the criticism you should be making, instead of all this stuff about messaging and marketing. We are however doing our best to fix this: Anthropic is ramping up its efforts very quickly in biology and medicine, and we hope to have incredible results in the coming years and some early glimmers in the coming months.  When we’ve actually accomplished something real, the whole world will hear about it, as loudly as possible, you have my word on that.  But until then I don’t want to make empty promises, and in the meantime I feel compelled to speak honestly about the very real risks of AI and how to address them.  Honesty is the right thing on the merits, and in terms of public credibility and trust it is no worse than, and may in fact be better than, an approach that ignores or distracts from risks which people instinctively understand are real.

You cannot create God and put him on a leash.

Sholto, thank you for setting the record straight. Larger issue is that multiple very serious people in Silicon Valley have heard some variation of this and believe it to be true. And the reason it is believable to so many is that it is consistent with Dario’s public messaging and what he outlined in the essay you shared: this technology *might* be dangerous for humans in multiple ways, could lead to extreme concentration of economic power (as outlined in the essay) and therefore needs to be regulated thoughtfully. I agree with the potential risks and I believe Dario makes all of these arguments in good faith. 
As discussed on the pod, if one agrees that AI *might* be dangerous, there are two ways to address this potential risk. Either concentrate it in the hands of a chosen few companies and politicians via regulation or distribute it widely. Essentially boils down to whether one believes AI is too dangerous to concentrate or too dangerous to distribute. There are reasonable arguments on both sides, but I profoundly agree with Zuckerberg’s statement that: “The notion that AI is so dangerous that the only safe path is an extreme concentration of power seems inherently problematic. Historically, hoping that an absolute power will benevolently provide for humanity if sufficiently enlightened has not led to safe or positive outcomes.” And as Dario says in the aforementioned essay, “some may object that we can simply keep AIs in check with a balance of power between many AI systems, as we do with humans.” I believe this is the best path forward: I want as many AIs as possible to maximize the odds that one shares my own particular values. And as Dario notes, no human has ever been able to take over the world. At this point, I think safe to say that Dario has lost the argument. His messaging has failed to result in his preferred regulatory path. The fact that the only solution to the recent incident where an unreleased advanced OpenAI model hacked Hugging Face was an open-source model likely ended any chance of strict near-term regulation. Essentially every major company other than Anthropic has signed Jensen’s letter. However, Dario’s messaging has been massively helpful to efforts to ban datacenters here in America. I suspect we will see anti-datacenter advocacy groups runnings ads using clips of Dario warning about how dangerous AI could be for humans. His good faith efforts in favor of regulation are now increasing the odds that AI will not be beneficial for Americans and humans everywhere. I believe that there is a reasonable chance AI might help us cure most forms of disease such that we have extended lifespans and can enjoy these long lives in an abundant Star Trek like future. That is the future that I want and I think Dario is decreasing the odds of that future at this point. He is about to be the CEO of one of the most important public companies in the world and given that the pro-regulatory effort has failed (at least for now), I respectfully think he should make an effort to be a more positive advocate for his own industry. And if I am wrong and we do need to regulate this technology, he will be a more effective advocate for this in the future having been open-minded to the alternative. And for the sake of clarity and as I outlined on the pod, I think Anthropic has deep competitive advantages and is an amazing company. Ironically, the main risk I saw to Anthropic a few months ago was nationalization as a result of Dario’s own rhetoric and behavior.

I am absolutely begging anyone who works in tech who uses the term "singularity" to actually read Vernor Vinge and Ray Kurzweil. It doesn't just mean "wow there's a lot of progress in this one particular technology driving a massive capital cycle".

https://x.com/i/article/2088681782606536704

I've been reading Bethany Hughes book on the 7 Wonders & the myths of the Colossus of Rhodes (eg it did not span the harbor) As an experiment, I asked Google Deep Research to come make a prompt to describe the historical Colossus for veo 3. Nice, down to the location & riveting

I talk and teach about the frictions inherent in AI which will slow down economy wide adoption. But in my heart I don’t believe they are that bad. You just ask a machine to do things and it does them! How can frictions to doing this persist?

“Bring science, not science fiction, back to the AI debate.” At AI4 2026, @drfeifei pushed back against increasingly extreme narratives around artificial intelligence. As AI evolves rapidly, she argued that fear-mongering and unscientific rhetoric can make it harder for policymakers and the public to understand what the technology actually means. Instead, the AI conversation should be grounded in science, education, and healthy communication. For students, teachers, nurses, parents, and workers thinking about how AI could affect their jobs and their children's futures, understanding the technology matters. Her message is simple: AI is a rapidly evolving tool—and society needs a more rational conversation about how to use it. #ChinaAMC #CNQQ #AI4 #AI #ArtificialIntelligence #FeiFeiLi #FutureOfAI #AIInnovation #AITools Risk Disclaimer: Investment involves risk, including possible loss of principal. Any forecasts, projections, or opinions contained herein are for reference only and are not guaranteed to occur. The information in this material reflects prevailing market conditions and our judgment as of the release date, which are subject to change without further notice.

GLM 5.3 notes and why we should stop being so surprised about these very strong Chinese models (most of this is talking myself through some of my denial -- yes, these models are the real deal). https://www.interconnects.ai/p/glm-53-how-chinese-labs-keep-stride

There's a ton of good stuff in here, but to me this is the part that everyone mainstream is overlooking. It's literally the most important part. "It's ironic that today orbital datacenter compute is considered a niche...because the model suggests it will be a necessary condition for AI continuing to scale in the 2030s."