Leon

1K posts

Leon banner
Leon

Leon

@leon_meier

Building AI agents in place of procurement teams

Berlin Katılım Şubat 2022
248 Takip Edilen368 Takipçiler
Sabitlenmiş Tweet
Leon
Leon@leon_meier·
Industrial countries may be headed for a dark age. For decades, world trade was built on three axioms: ⚡️ cheap energy ⛴️ open trade routes 🤝 stable alliances. That world made it rational to optimize everything for cost. This vulnerability is now finally exposed. (1/4)
English
1
0
0
40
Leon
Leon@leon_meier·
thinking in sessions is what keeps ai stupid
English
0
0
0
15
Leon
Leon@leon_meier·
there is something deeply satisfying about using cmd + shift + p in claude code
English
0
0
0
16
Leon
Leon@leon_meier·
Companies got used to a calmer world: - lean teams - concentrated supplier bases - long qualification cycles - and too much manual work to react quickly. That is fine when supply is stable. It is dangerous when energy shocks, route disruptions, and supply interruptions start compounding, which is exactly what markets are now trying to price. [1] Being prepared now means having alternatives before you need them: qualified fallback suppliers, better market visibility, and the ability to move fast under pressure. (4/4) [1] reuters.com/world/middle-e…
English
0
0
0
10
Leon
Leon@leon_meier·
Post-hormuz brings a new supply chain paradigm, that changes manufacturing, sourcing, and changes what “good procurement” means. 🔙 The old model rewarded whoever bought cheapest. 🔜 The next one will reward whoever can react fastest, when their suppliers declare force majeure. Most companies are not yet built for this change. (3/4)
English
1
0
0
15
Leon
Leon@leon_meier·
Industrial countries may be headed for a dark age. For decades, world trade was built on three axioms: ⚡️ cheap energy ⛴️ open trade routes 🤝 stable alliances. That world made it rational to optimize everything for cost. This vulnerability is now finally exposed. (1/4)
English
1
0
0
40
Leon
Leon@leon_meier·
hear me out: usage-based taxes 1) Citzens and companies pay proportionate to their your use of government services and facilities. automagically attributed with ai (🪄) 2) the more people use a service, the more funding that gov agency receives. 3) The cost to run and improve the agency is split equally among all verified users of that gov facility. e.g. - #all defense, grid, trains, parks, public health... - #uber overuse of roads - ... 4) No elections for local gov, they just hire the best people for the job from the free market. High-paying prestigious jobs. 5) All citizens sit on on the board of all gov facilities that they're using, where they vote on granular budget allocation, new hires, attribution of gov.facility use, etc. 6) Fed gov keeps all national functions. Same election process. Reviews performance of local gov by law-binding KPIs and OKRs. can hire and fire with executive authority in special scenarios. Can set tax-to-use attribution model. Rewards: - Gov innovation and consolidation of functions through competition over a scarce max amount of taxes. - Tax avoidance only possible through limiting their use of public property - Crowdsourcing local public works projects by wealthy citizens and companies to. - Each political partys only advocate for their thesis on optimal tax attribution logic. Hard mathematical models instead of political bs. Performance discussed publicly. - Infrastructure is maintained obsessively to avoid outages which could result in a direct drop in tax revenue. Disincentivizes: - Waste - Fraud - Abuse
English
0
0
1
37
Leon
Leon@leon_meier·
@kimmonismus They watched AI fomo ads and believed them
English
0
0
0
5
Riley Walz
Riley Walz@rtwlz·
made my computer dramatically play BBC news music before every meeting
English
601
6.3K
71.6K
4.3M
Leon
Leon@leon_meier·
everything must work from a fresh context window
English
1
0
1
30
Leon
Leon@leon_meier·
build the server vs. be the server
English
0
0
0
22
Leon
Leon@leon_meier·
all crms will become CLI companies
English
0
0
0
23
Leon
Leon@leon_meier·
@peer_rich you must not watch the news
English
0
0
0
21
Leon
Leon@leon_meier·
I often ask myself: 10 years from now, when I look back on what happened in this period in history, what would I have wanted myself to do in retrospect? Teaching my friends and family how to describe their intent to models and vibe-create anything is probably among the highest ROI things. Everyone has at least one beautiful idea in their lifetime. If they had the power to bring that idea to life, how could the world not be more beautiful.
English
0
0
0
15
Leon
Leon@leon_meier·
My ux friend has been getting super into cursor lately. it's about time i encroach on his territory #pixelpushers
English
0
0
0
20
Leon
Leon@leon_meier·
@dwarkesh_sp Hardware supply chains are as big a blocker for AI rollout as energy, if not bigger.
English
0
0
0
220
Dwarkesh Patel
Dwarkesh Patel@dwarkesh_sp·
EUV machines are the most complicated tools humans make. Their supply chain has over 10,000 individual suppliers, and any one of them not scaling fast enough can bottleneck the entire AI industry. An EUV tool fires lasers at a tiny tin droplet three times in precise sequence, blasting it hard enough to emit EUV light. That light bounces off 18 multilayer mirrors onto the wafer. Meanwhile, the two platforms inside the machine - one holding the stencil, one holding the chip - are flying back and forth at 9Gs in opposite directions. The successive passes have to land on top of each other to within 3 nanometers. If any part of this is off, yield goes to zero. Take just one component. The mirrors are mostly supplied by Carl Zeiss, who have probably fewer than a thousand people working on them. In turn, Carl Zeiss rely on machines from Switzerland to deposit each of the layers, and use a coating process co-developed with a different German company. None of these companies have woken up. They’re gradually increasing production, but nowhere near the levels necessary for what the labs want by the end of the decade. @dylan522p predicts production can't scale beyond about 100 EUV machines per year by 2030, no matter how much money gets thrown at the problem. In the medium term this is the key bottleneck on scaling.
English
52
117
1K
153.2K
Leon
Leon@leon_meier·
@garrytan It's so fucked that you can't get democratic politicians to care about shit that takes 25 years to work anymore. Says more about politicians' age than their geo though.
English
0
0
0
36
Garry Tan
Garry Tan@garrytan·
Merz called Germany's nuclear phase-out 'a serious strategic mistake.' Two months later: 'irreversible.' Meanwhile Germany is burning coal and the rest of the world is building reactors. Bring back nuclear everywhere. gli.st/nzb54xgl
English
32
27
400
19K