Al Clark

trying to see the future

[Al Clark @alllclark]

the performative 996 glorification in the US is tied up with people's desire to be a 'live player', someone with 'high agency', roosevelt's 'man in the arena'

people conflate high agency with brutal working hours b/c often high agency people put in a lot of hours.. and it's true

but the causality runs the other way.

someone with high agency is working on a problem they find meaningful, or fascinating, or whatever... *that's* why they're working so hard. you don't become high agency by giving your life to someone else's quest

[Bojan Tunguz @tunguz]

I for one am glad that the era of performative grindwork is finally over. Let AI agents work 24/7. Go home. Spend time with friends and family. Touch grass.

[Al Clark @alllclark]

the exact sort of thing that i would not have expected, and that now i'm going to be thinking about for the next week... incredible

[Markus J. Buehler @ProfBuehlerMIT]

Can we compile matter - for instance, a pine cone - and derive new active materials, end-to-end from observation to manufacturing? If physical systems can be formalized as composable mathematics, we can point AI that has been shown to resolve long-open mathematical problems at matter itself. Our new work turns bioinspired engineering from analogy into formal compilation: biology and mechanics become explicit, checkable, and executable, so AI reasoning can produce physical designs.

This is the first end-to-end demonstration in which a formally compositional multiscale model is carried from a biological hierarchy, through engineered design and fabrication specification, to executable manufacturing code - and then to a physically tested artifact.

Background:

Humans have long been inspired by biology to advance technology, but this has usually been an ad hoc process rather than a mathematically rigorous one. Natural materials such as pinecones achieve adaptive behavior through mechanisms organized across many scales. Engineering typically translates those mechanisms by analogy: identify a biological principle, build something inspired by it, and validate each new design as a separate case. This can produce remarkable results, but the knowledge does not readily compound. Instead, we represent each scale as a dynamical module with explicit states, stimuli, governing laws, and interfaces. Every scale-to-scale map must preserve the stimulus - response dynamics: evolve the fine-scale system and then map upward, or map upward first and then evolve. The two paths must agree. Because this condition is preserved under composition, locally valid interfaces remain consistent when assembled into the full hierarchy.

We then carry that structure into an engineered system, translate the target behavior into a verified fabrication specification, and compile it into G-code: the toolpaths, deposition sequence, temperatures, speeds, and other commands executed by a 3D printer. The intermediate translations are explicit, checkable, and executable rather than completed through an ad hoc handoff.

The formal guarantee is that given valid local models and interfaces, their composition remains valid. Whether those models and manufacturing assumptions accurately capture physical reality remains an empirical question. That is why we fabricated and tested the results.

We generated four actuator classes by crossing two stimuli - humidity and heat - with two responses: bending and twisting. The fourth, thermal twisting, required no new pipeline and no separate derivation within the framework. It emerged by composing a thermal stimulus module already validated in one case with a twisting module validated in another. The generated G-code produced the intended motion without manual redesign, and all four predictions fell within one experimental standard deviation of the measured response.

Why this matters:

1⃣For AI in science, this provides a physics-aware type system against which generative proposals can be checked - and rejected at the interface - before expensive simulation, fabrication, or experiment. It is roughly analogous to proof checking, but for the composition of physical mechanisms.
2⃣For engineering, the accessible design space can scale with a library of validated components rather than with the number of individually derived cases.
3⃣The mathematics, category theory, carries all the way into a physical object on a print bed. This points toward scientific knowledge as executable infrastructure: models that are not only described in papers, but typed, composable, verifiable, and able to compile into experiments.

Excellent work led by my student @leemmarom with @SkylarTibbits & @GioeleZardini.

Paper published in J. Mech. Phys. Solids along with code, Grasshopper scripts, and manufacturing G-code below.

[𝕝𝕖𝕠𝕟 @typesuser]

this + mathematically competent ai will lead to a cambrian explosion in materials and physical designs. making physical systems programmable at exactly the moment where programming becomes automated. wild

[Al Clark @alllclark]

@ShanuMathew93 agree - who is out there saying, of anything, "this would be better if it was dumber?"

we're going to find out how many things have been secretly dumb all along

[Al Clark @alllclark]

@teortaxesTex reminds me of people talking about a 'good school' where, beyond some baseline of admin/teaching, the quality of a school is 90%+ the quality of the students coming in

[Al Clark @alllclark]

@gfodor with the context they could feed it at nsa? i bet yes

[Al Clark @alllclark]

real good point in here,.... but imo home prices dropping is a *very* desirable outcome even though it comes with real & unavoidable medium-term pain...

for the boomer who owns their home.. if the price goes down they're really not much worse off. it's mosly an ego hit (many boomers are indeed fragile so @NickADobos is right this is going to be a political mess). could potentially be an immediate problem for the reverse-mortgage crowd - idk how those agreements are written - definitely a problem for whoever the counterparty is on those deals (whoops).

the person that policy SHOULD try to support (but won't b/c we live in a financialized gerontocracy) is the productive citizen who got a mortgage a high price, and is stuck having to short-sell a home which has gone down in price.

[Nick Dobos @NickADobos]

The true AI backlash won’t start until robots build houses, build entire cities in months, and decimate boomer’s housing investments.

[Al Clark @alllclark]

@NickADobos it'll be good though

people need things like housing, food, healthcare to be have a stable & decent life

it should be public policy to make those things cheap

[Al Clark @alllclark]

a few months ago i tried lovable & found it useful for getting some simple websites built quickly.

i deleted it today. agents have closed the gap on ease of use, & never having to fumble through a UI is such a relief

[Al Clark @alllclark]

great thread.

[T. Greer @Scholars_Stage]

Strong disagree.

I do think one’s preference on this reveals a lot about one’s outlook, however.

[Robert Scoble @Scobleizer]

Not available in USA.

[Object Zero @Object_Zero_]

Weapons of Mass Production

Today there are a handful of single assets that gate huge sectors of the economy. The criteria should be something like >50% of the global supply passes through this one cool thing.

• Falcon 9
Commercial access to space is 90% via the Falcon 9 launch system.

• Ulsan shipyard
Large high quality FPSOs and LNG tankers are almost exclusively manufactured here.

• Muroran forge press
Giant forged ingots >200 tons are mostly made in Japan and by this giant forge press.

• Zeiss vacuum grinder
The mirrors that allow ASML to do frontier EUV lithography are made by 1 machine.

There are a few others but you get the idea, what else should be on the list?

[Romi Lifshitz @RomiLifshitz]

Guys AI proved the Closest Vector Problem is computationally hard to approximate, this reinforces the security of lattice-based post-quantum cryptography. Huge ‼️

[Al Clark @alllclark]

@MTSlive @Brendan_McCord He's right, it's clearly an unworkable thing.

It might've been possible with the political economy of 50-75 years ago (unlikely), but it's hard to imagine the level of coordination that it would take to agree and enforce now.

[Ethan Mollick @emollick]

One of our big findings in our study at Procter and Gamble was that AI blurred the lines between jobs. Now OpenAI has a similar finding.

Organizational boundaries are becoming porous, the walls thinning. Companies are going to need to think about division of labor in a new way.

[Al Clark @alllclark]

@erat_perfect @Wealth_Mgmt_Guy good point no one would ever get money from their family & use it to start a business, or *build* a house, or anything productive

[Al Clark @alllclark]

@erat_perfect @Wealth_Mgmt_Guy pretty sure we want it invested in incremental useful assets.

the problem is useful assets are usually things that either

(1) are veto'ed by incumbents - like new housing; or
(2) have low capturable ROI - like improved infrastructure

[Paul Graham @paulg]

"Life is indescribably better!"

— a founder after getting a jerk to leave his board

[tang @_mlswe]

spend enough time with algebraic data types, and your mind starts bending reality into structure - everything becomes an abstract object defined by the operations it supports.

[martin_casado @martin_casado]

Yeah so, boom times always reward low integrity opportunists because greed is easy to exploit. However, these folks tend to get flushed out in the down turn.

It's hard to maintain a successful career over the long term without an ethical compass. Possible, but much harder.