I’ve done this in pure Python for a long time. Single file prototype that can mostly function from the command line. The process helps me understand all the sub problems and how they relate to each other. Best example is when you realize behaviors X, Y, and Z have so much in common that it makes sense to have a single component that takes a parameter to specify which behavior to perform.
It’s possible that already practicing this is why I feel slightly “meh” compared to others regarding GenAI.
What people, exactly? You could see the introduction of desktop computing and other types of computing in industry with a double digit increase to productivity, all other things being equal.
Any organization that properly adopted computers found out quickly how much they could improve productivity. The limiting factor was always understanding.
The trouble with AI tools is they don’t have this trajectory. You can be very versed on using them well, know all the best practices and where they apply and you get at best uneven gains. This is not the introduction of desktops 2.0
Next evolution: UX should allow end users to build the prompt, and then the tool is generated and deployed at a random URL. Tool also keeps original prompt, so any user can customize into a new (random URL) tool page.
Food and shelter are cheaper than at almost any time in human history. Additionally, people have more variety of healthy foods all year long.
No matter how cheap food and shelter are, there will always be people who can not acquire them. Halting all human progress until the last human is fed and sheltered is a recipe for stagnation. Other cultures handle this with strong family bonds - those few who can not acquire food or shelter for whatever reason are generally provided for by their families.
Most people don't have houses large enough to house multiple generations inside the house. Houses are sized for parents + kids. And those are the only dwelling units available or legally allowed for vast distances in any direction.
From what I've seen American bedrooms are far larger that the 12 square meter bedrooms that are normal for two or three children to share in my country. Grandparents don't need a separate wing, they need a room.
Food is not Baumol, productivity increases is how we went from 80% of the population working in primary food production to 1%. These increases have not stopped.
If you start exercising in your 20s, and never stop, it will be so much easier to maintain fitness in 40s 50s etc. The challenge is that the benefits are not yet visible in your 20s (when you’ll probably be healthy and at a proper weight regardless). Gotta lay that foundation for older age though!
EDIT - I misread the comment. It’s never too late to start, just be careful for injuries as that will block your ability to exercise.
As fascinating as these tools can be - are we (the industry) once again finding something other than our “customer” to focus our brains on (see Paul Graham’s “Top idea in your mind” essay)?
It seems so ... LLM-based coding tools are mostly about speed and cost of development - corporate accounting metrics, but what customers care about is mostly product features (& lack of bugs).
There is no customer advantage to developing cheap and fast if the delivered product isn't well conceived from a current and future customer-needs perspective, and a quickly shipped product full of bugs isn't going to help anyone.
I think the same goes for AI in general - CEOs are salivating over adopting "AI" (which people like Altman and Amodei are telling them will be human level tomorrow, or yesterday in the case of Amodei), and using it to reduce employee head count, but the technology is nowhere near the human level needed to actually benefit customers. An "AI" (i.e. LLM) customer service agent/chatbot is just going to piss off customers.
California is home to 1 in 8 Americans, and likely a much higher fraction of AI researchers, users and partner organizations to OpenAI (like Nvidia). The California AG has plenty of leverage beyond blocking/reversing the conversion. What leverage will OpenAI have after "leaving"[1] the California?
1. They're guaranteed to have an engineering office in the SF Bay. Not many of those folk will agree to relocate to Texas/Miami.
Yup the Tesla treatment. Can change HQ's all you want but the main engineering work, brains, and talent will be at a HQ in California no matter what. Sam will probably do this for brownie points with the current administration, it will be politicized news for a cycle, but after the dust settles the majority of non-admin people will still be working unchanged out of CA.
That’s assuming Altman is sincerely going to keep trying to develop “AGI” and not try to turn OpenAI into a profitable business. You don’t need AI researchers if you get good enough video generation and pornbots to become immortally wealthy and say fuck the rest. If this is the case, OpenAI could be a completely done product, all that’s left to do is stop spending so much money on SG&A and get those revenue streams cranking.
What's stopping OpenAI from offering telework? AI isn't dealing with high security or particularly sensitive data (that developers need to actively access - training data is all public or stolen works) and it's not a hardware product.
Unless you're Universal and Marvel, leaving Disney unable to buy out Universal's contract with Marvel, and unable to use classic comic book characters because the parks too close to Universals. Still cracks me up.
Not if the big holders aren't residents, they can move away just before like Rogan with his Spotify deal, or Jonathan Blow just before a game release after developing in California and going to public college there, etc.
Since it's a non-profit still holding it any gains to the non-profit entity upon the conversion don't go to California, and principal stakeholders can move away. Other funds raised from the IPO can be invested in other states untaxed (long term datacenter leases instead of booking the capital of building one) until they move the company away I think.
There will probably be a lot of smaller stakeholders that stay with a lot of money for the state, and California at least doesn't do the $15 million QSBS so they may get a lot from that tail of employees. A large portion of this tail of lower compensated employees may get laid off due to AI replacement before IPO and lose a lot of unvested years, if we are to believe OpenAI's own claims about timelines for job replacement in that field at lower levels.
I'd recommend anyone expecting to profit from OpenAI stock and aiming to avoid California taxes to look into the subject in depth with paid advisors. The California FTB is not stupid or naïve and has a history of successfully getting paid for stock that vested with a California nexus, even if the beneficiary moves out of state. Good luck!
You're right, it's harder with vesting stock compensation than other things you build up over time like an audience or a developing a game over a long span.
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