Slashing costs is the goal, but you need to choose the right market otherwise its radial tires all over again. Abundance is about repeatedly 1/10th-ing costs, in markets where demand grows with an even larger multiplier (1/3)
The False Promise of Labour Replacement Revenue
@immad's take: "AI companies are charging 1/3 of labor costs — but margins will get crushed."
Right now, AI pricing looks brilliant on paper. But there’s no moat. No network effects.
Once competitors show up, margins will disappear.
What looks like efficiency today, might be a race to the bottom tomorrow.
@gdb@Altimor@karpathy — how defensible is labour automation in the long term?
@barbinbrad@wingod Implementing Netsuite meant gradually ripping away the entire UI to eventually use just the ledger for financials. Or you could use Carbon, which already does what you want and you’ll get better support.
The next Louisiana Purchase? Here’s an idea: the United States acquires the Baja California Peninsula from Mexico for $1 to $5 trillion.
Every Mexican citizen living in Baja receives dual U.S.-Mexico citizenship, plus a $50,000 investment account.
Then America gets to work: world-class infrastructure, deep-water ports, desalination, nuclear energy, housing, universities, and industry. Tijuana and Mexicali could become major reindustrialization zones.
In return, the United States gains nearly 1,800 miles of some of the most spectacular coastline on Earth and the chance to build the great new economic region.
Is this a crazy idea? Of course. But so was the Louisiana Purchase in 1803.
Real jobs I’ve had:
- Selling cokes at football games
- Delivering newspapers
- Programming for a university (age 16)
- Network SW at Apple
- Working with great VCs
Fake jobs I’ve had
- Choosing a bad partner at a great firm
- Zoom calls with 16 people from the bank when shutting down
@bryan_johnson Travel one or two time zones at a time to minimize jet lag. Australia via Hawaii, Pago Pago, Fiji, New Caledonia, Brisbane, then Sydney is only one 2-hour jump. Continue westward on your return, the human circadian clock is slightly longer than 24 hours.
@Dylan_Morri@nextdeltav Manufacturing learning curves vary by industry. High volume with tight feedback loops necessary. Constant redesign blocks that, like initial R&D.
You will see a learning curve if you take an old, proven, inefficient turbine and mass produce it. A better turbine will take years.
@tszzl The models will (most likely) be hosted on GovCloud at Azure and AWS, and access granted just like all other export controlled material. Could explain why Amazon reported the scare from the highest levels. (5/5)
@tszzl Most of all, there is plenty of infrastructure, rules, and processes to handle how this works. About $5-10T of the economy is subject to EAR/ITAR rules. Yes it's a hassle to learn, but this isn't some new category concocted by fascists on a whim. (4/5)
@theo Amazing. In a few hours Fable blasted through work that befuddled Opus and Codex for the past week, and did so with mastery and clear explanations
@Dylan_Morri ERP is really two separate questions: workflow vs financials. Commercial ERP are abysmal at workflow because they’re designed entirely around accounting. Learn manufacturing accounting then you’ll understand why ERP systems have such a weird set of screens
A useful reminder from today's Saronic news:
The company wasn't merely funded by 8VC. It was born out of 8VC's Build program.
Congratulations @JTLonsdale and @notanotheralex
Designed, built, and launched in under a year – our dual-use Marauder MUSV is officially entering on-water trials and validating a new model for modern shipbuilding. 1/3
@DeveloperHarris Counter-to-counter / NFO is how you get faster-than-next-day shipping. TSA Known Shipper status lets you bypass a lot of the middlemen domestically. International is more effort but doable. This is why factories locate near great airports.
@aphysicist A model that can visualize physics (not just read about it in a book), and that learns from experience (not just sees the final results), will be able to solve most manufacturing problems from first principles and experimentation