This was due to a heroic effort by many people at Anthropic working sometimes literally around the clock

It was not at all clear that we'd be able to do this in time, and so proud of everyone who made it happen.

Enjoy Fable. https://t.co/qAtqPadj3L

Based on internal evals:

▪️ Kimi K3 is top-tier at cybersecurity
There is chatter on X that Moonshot benchmark-overfit. These are stealth evals. Model has raw IQ.

▪️ Sol is a leap ahead in cyber capability
At a significantly higher cost, but quite remarkable still.

▪️ Fable refuses everything
We couldn’t get it to complete the run at all. What’s interesting is that Sol in comparison was much more open to helping with defensive cyber hardening

TL;DR: frontier, open-weight cybersecurity capability is here. Try it on https://t.co/HedSpZpo1a for defensive purposes.

The term "AGI" has aged very poorly. AI can't possibly me more different from human intelligence. It's *far better* than human intelligence, for most economically-relevant tasks.

But that doesn't make AIs better than humanity. There are wonderful things humans can do that these superintelligences (the better term) can't.

For one, we care-for and care-about other humans in a powerful and inherent way, that we then teach machines to emulate. We must keep that as the top priority in everything we do. We have to be as pro-human-life as it gets.

AIs can replace tasks you do, but they can't replace the proverbial you. This is why they horribly suck at writing! Even when given a corpus of your writing and 200 Skills and 50 subagents running in gRaPh LoOps, they produce robotic prose… because they are robots.

I know one definitive way that people can become irrelevant. They stop being themselves: lose their identity, delegate all their writing, their unique thoughts, the creative ways in which they can use the machines. Opting out of 'weighing in'.

I think we're safe though. There's nothing more distasteful right now than AI replies in social media or (🟢 T H I S T H I N G ) in landing pages. Quality and humanity will prevail.

If you thought the value of the AI ecosystem was going to only accrue to a few companies, the past few months have represented a turning point in what the future of AI might look like.

It's clear that there's going to be incredible innovation and growth coming out of the frontier AI labs, and they will continue to push the limits of what model progress looks like. They have the scale of compute, large revenue streams and customer bases, incredible researchers, large data pipelines, and more, to continue to stay at the forefront.

And at the same time, there’s an amazing ecosystem starting to play out to diffuse AI into the real world, taking on a variety of approaches that build on top of these frontier models or offer alternative visions that can credibly work as well.

Here are just a few of the categories that seem to be working right now:

* There’s an ecosystem of companies that will help enterprises and applied AI companies develop their own models tuned for specific use cases, and run the inference for them. This can drive additional performance gains and cost effective approaches to getting AI into workloads across different domains.

* Applied AI companies that are delivering the end-user experience and business process tools necessary to actually driving enterprise adoption - including legal, IT, security, HR, customer support, coding, and more. These companies can work with any model and act as a routing layer, and deeply understand the enterprise workflow, can drive change management, actually get to the data necessary to work with, and more.

* New labs are emerging that go deep in particular domains that are either not the focus areas of frontier labs or require a deep level of vertical expertise to stay ahead. Life sciences, financial services, healthcare, and more all have labs that will be able to bring completely new approaches to large enterprises across the economy.

* There’s all new infrastructure emerging to run models and agents effectively, protect and govern how they operate, store and secure the data they work with, and help enterprises orchestrate their activities. Multiple layers of this stack all are being built up right now that will help drive enterprise adoption.

* New services firms that can actually drive the change management in enterprises necessary to the diffusion of AI. There will be hundreds or even thousands of new firms that emerge in lines of business or specific industries that can enable agents to be adopted.

I’m probably even missing a few categories, but this is what an incredible healthy technology ecosystem looks like.

Way too early to call the winning architectures, and in reality it’s going to be a heterogenous environment as all other tech markets have become. Very exciting.

It’s fairly obvious that gate keeping models will not work at scale.

Competing in AI is too economically and strategically important for China at this point, and we’ve now crossed the rubicon where it’s clear that they can compete at near frontier levels. If this were even just 1 month ago and we saw kimi k3 our brains would be broken.

The solution to this isn’t to get more locked down and slow your own ecosystem. If that happens, you can guarantee that America loses the global battle (or just fights with more and more regulation to mixed success).

The solution is to -safely- ensure that you keep a high rate of progress and drive diffusion of the technology, build out infrastructure, enable US OSS, and more.