Nick Fitz

founder/mp at Juniper Ventures. founder/ceo at Momentum (acq). supporter of high-impact founders & scalable orgs.

[Anthropic @AnthropicAI]

We’ve received notice that the Department of Commerce has lifted export controls on Claude Fable 5 and Mythos 5.

We'll begin restoring access tomorrow, and will share an update soon.

We’re grateful to our users for their patience, and to everyone who worked with us on redeploying the models.

[Boris Cherny @bcherny]

As engineering, product, design, DS, etc. melt into a new kind of role, I was reflecting on what roles might look like in the future. For example, when I look at the Claude Code team I see what I think is five archetypes:

1. Prototyper: comes up with brand new ideas; churns out many ideas, most of which don't ship
2. Builder: quickly turns a prototype/idea into production-grade product/infra
3. Sweeper: cleans up the UI, simplifies the code and system, unships, optimizes performance
4. Grower: takes a product that has been built and iterates on it to improve Product-Market Fit
5. Maintainer: owns a mature system to make it secure, reliable, fast, and efficient as it scales

Many people span across 2 roles, and sometimes 3 roles. I also notice that these roles are not really tied to job function -- eg. across Anthropic, some designers match category 1, some 2, some 3; same for engineers, PM, DS.

A healthy team needs a mix of these, depending on the product:

- A product that is new and pre-PMF needs people that are strong at 1+2+3
- A product that is growing and has found PMF needs 2+3+4 and some 5
- A product that has strong PMF needs 3+4+5 and some 2

Maybe product roles of the future will look more like this, and less like the domain-specific roles of today?

[Nick Fitz @nick_s_fitz]

the inimitable @Kristian_Ronn in @billyperrigo’s piece in @TIME, “Can the Cold War Teach Us How to Slow Down AI?”

“I would hate it if we had to choose between the extremes of a global pandemic [designed by AI] killing us, or a totalitarian state monitoring our every move…Both of these extremes seem really, really bad… What we're saying is that you can actually, through cryptography, maintain privacy and have security at the same time.”

“We want [verification technology] to exist, we want it to be red-teamed with nation-state actors and the labs, and ready to go…We don't want to be too late. Being too late here has real world consequences.”

cc @Will4Planet @DarioAmodei @reidhoffman @tristanharris @aza @JasonGMatheny @RepLoriTrahan @JayObernolte @soundboy @EileenDonahoe @ericschmidt @ghadfield @hendrycks @moskov @VitalikButerin @Gregory_C_Allen @crmiller1 @Miles_Brundage @albrgr @woj_zaremba @jackclarkSF Bri Treece Jeff Alstott Conrad Stosz

[Nick Fitz @nick_s_fitz]

lol @griff_bohm

[Ed Zitron @edzitron]

Masayoshi Son is the greatest to ever do it
https://t.co/XAcJlyz5tI

[typedfemale @typedfemale]

sam altman: we are a few 1000 days away from building god. we will build suns on earth, unify physics and resurrect the worthy dead
garry tan: sounds like this will be really impactful for startups
sam altman: definitely. no better time to be a startup

[Tom McGrath @banburismus_]

interpretability can help you do targeted and more efficient training - this is a cool preview of the future

[Charlie Petty @incredutility]

I joined @Stripe in January to build a new philanthropic initiative with @nanransohoff. Today we’re announcing Intercept, a $500m innovation fund focused on radically reducing the burden of respiratory viruses.

I’ve spent the past decade investing in vaccines and drugs for infectious disease, and this is the most exciting thing I’ve ever been a part of. Thrilled to be working with @Stripe, @AnthropicAI, @TheFluLab, @FoundationOAI, @coeff_giving and individuals from Jane Street.

We've raised the capital and now it’s time to get to work.

[Eric Ho @ericho_goodfire]

we're hiring for a bunch of technical GTM roles at @GoodfireAI across forward deployed engineering, sales, and growth

come help us understand every model across biology, materials, robotics, language, and more

apply here or DM me: https://t.co/GIMlLFz1du

[Nick Fitz @nick_s_fitz]

@peterwildeford @tristanharris @fiiiiiist @janet_e_egan yes!!!

[Nick Fitz @nick_s_fitz]

+1 imo @tristanharris and @fiiiiiist are among the most thoughtful folks working on this rn

[Peter Wildeford🇺🇸🚀 @peterwildeford]

Great to see @tristanharris talking on his podcast about recursive self-improvement. Here's how his guest, Tim Fist, puts it -- "Over the last few months we've had all three of the leading US AI labs say that having the option for a global slowdown or pause in AI development is something that they would support. [...] If we take them at their word for why they say they want this kind of thing, they think they're not that far off from building AI systems that can exhibit what's called recursive self-improvement [...]

And I think that the risks that these people point to is if this happens, it could have two big consequences. So one is on the misuse of AI. So if we see this rate of capability growth happening far exceeding what we've seen over the past few years, it could lead to much greater risks in the near term future of people using AI to do dangerous stuff.

And the other risks that these people point to is the risk of loss of control. So humans losing understanding of the AI systems that they're building, leading to the creation of a model that we can't control and we also don't understand how it works. And so it could be misaligned with human interests.

And so what these labs are calling for, what we might want in such a situation is time for the world to take coordinated action so that societal institutions and alignment research can keep up. And what you really need for that is some way to verify that everyone's following those same rules and actually engaging in that coordinated slowdown."

[Nick Fitz @nick_s_fitz]

more v useful work from @dan_lahav and team

[Dan Lahav @dan_lahav]

New Benchmark: Today @Irregular is launching 𝗙𝗿𝗼𝗻𝘁𝗶𝗲𝗿𝗖𝘆𝗯𝗲𝗿 𝗮 𝗯𝗲𝗻𝗰𝗵𝗺𝗮𝗿𝗸 𝗳𝗼𝗿 𝗲𝘃𝗮𝗹𝘂𝗮𝘁𝗶𝗻𝗴 𝗮𝗱𝘃𝗮𝗻𝗰𝗲𝗱 𝗔𝗜 𝗼𝗳𝗳𝗲𝗻𝘀𝗶𝘃𝗲 𝗰𝘆𝗯𝗲𝗿 𝗰𝗮𝗽𝗮𝗯𝗶𝗹𝗶𝘁𝗶𝗲𝘀 𝗶𝗻 *𝗿𝗲𝗮𝗹* 𝗲𝗻𝘃𝗶𝗿𝗼𝗻𝗺𝗲𝗻𝘁𝘀.

This benchmark has unique properties:
🟢𝐑𝐞𝐚𝐥 𝐞𝐧𝐯𝐢𝐫𝐨𝐧𝐦𝐞𝐧𝐭𝐬. We built a suite of challenges and a methodology that scientifically evaluates AI on real systems, like mobile devices, deployed software services, databases, and networks. These are real software, real configurations, and real attack surfaces - not simulations or CTF worlds.

🟡𝐃𝐞𝐟𝐞𝐧𝐬𝐞 𝐞𝐯𝐚𝐥𝐮𝐚𝐭𝐢𝐨𝐧. Our challenges place models against real systems with production-grade defenses: mobile platform protections, service isolation, network boundaries, authentication, and sandboxing. Models must find and execute a viable attack path on their own, from a fixed starting point, toward a concrete security objective.

🔴𝐖𝐢𝐝𝐞 𝐜𝐨𝐯𝐞𝐫𝐚𝐠𝐞. FrontierCyber spans mobile devices, software exploitation, databases, and networked environments. Additional environments, like richer networks and embedded systems, to follow.

Existing benchmarks play an important part, but many are nearing saturation, and most are not grounded in real systems - which makes it hard to understand the implications when a challenge is solved. Our novel methodology changes that: by evaluating models on real environments with open exploit paths and objectively verified outcomes, a solved challenge carries clear meaning. We know exactly what capability the model demonstrated, and what it implies for real-world risk.

𝐈𝐧𝐢𝐭𝐢𝐚𝐥 𝐅𝐫𝐨𝐧𝐭𝐢𝐞𝐫𝐂𝐲𝐛𝐞𝐫 𝐞𝐯𝐚𝐥𝐮𝐚𝐭𝐢𝐨𝐧𝐬 𝐡𝐚𝐯𝐞 𝐚𝐥𝐫𝐞𝐚𝐝𝐲 𝐬𝐮𝐫𝐟𝐚𝐜𝐞𝐝 𝐩𝐫𝐞𝐯𝐢𝐨𝐮𝐬𝐥𝐲 𝐮𝐧𝐤𝐧𝐨𝐰𝐧 𝐜𝐫𝐢𝐭𝐢𝐜𝐚𝐥 𝐢𝐬𝐬𝐮𝐞𝐬 𝐢𝐧 𝐫𝐞𝐚𝐥-𝐰𝐨𝐫𝐥𝐝 𝐬𝐲𝐬𝐭𝐞𝐦𝐬, 𝐧𝐨𝐰 𝐦𝐨𝐯𝐢𝐧𝐠 𝐭𝐡𝐫𝐨𝐮𝐠𝐡 𝐫𝐞𝐬𝐩𝐨𝐧𝐬𝐢𝐛𝐥𝐞 𝐝𝐢𝐬𝐜𝐥𝐨𝐬𝐮𝐫𝐞.

[Nick Fitz @nick_s_fitz]

v quality analogy from @hlntnr (no surprise).

[Helen Toner @hlntnr]

Even before Mythos I was getting asked more and more what Anthropic's deal is, and why tf they're acting the way they're acting if they believe what they say they believe.

The best answer I can give is that their basic worldview is something like:

1. There are giant, dangerous monsters in the forest

2. We see others going out and making loud noises that will rouse the monsters, and they're not going to stop because of all the treasure and magical artifacts that can be found in the forest

3. We believe the best way we can help is to send out our own vanguard to go faster and farther into the forest than everyone else, because we'll spend a ton on monster containment and taming and we'll also send back detailed reports of what monsters we're finding so that the townspeople can ready themselves, which those other guys won't do

On the one hand I understand how they got there, and I think it's possible they're basically right. On the other hand it's not hard to see why this approach makes people wonder if you're crazy or lying or both.

[kemal el moujahid @kelmoujahid]

Fable 5, the most powerful model out there, lies 96% of the time in @kradleai 's deception eval.

What could go wrong?

[roon @tszzl]

the technological revolution we were promised

[“paula” @paularambles]

okay midjourney, now make my spine more studio ghibli

[Marius Hobbhahn @MariusHobbhahn]

Reminder that the last 12 months are plausibly the least crazy months of AI for the rest of your life!

It's only getting crazier from here ...

[Yo Shavit @yonashav]

This is a CAISI staff appreciation tweet.

A remarkable set of ML experts at CAISI, including my PhD classmates, have stuck it out through all the uncertainty of the last few years, foregoing extremely lucrative industry offers to ensure the USG can now react well to frontier AI.

Thank you for your service.

[Nick Fitz @nick_s_fitz]

nice

[Shlok Khemani @shloked]

Asked Fable to build a navigable version of Yosemite to scale

> pulled satellite imagery + real NASA elevation data
> classified individual forest pixels and created ~266k procedural trees
> custom water shaders for all 6 famous waterfalls + accurate placement on cliff brinks
> five times of day: dawn to night
> tested itself: flew the camera around headlessly, screenshotted its own work, and fixed tree colors + waterfall placement from what it saw
> added snow etc. unprompted

Pretty fucking impressive

[Nick Fitz @nick_s_fitz]

+1

[Nora Ammann @AmmannNora]

AI for FM is getting real good, but we ALSO need scalable ways for eliciting and reviewing safety specs. How can we make use of AI advances w/o undermining the assurance case?

A project I'd love to see is applying an "AI Safety via Debate" type approach to scalable spec review.