Because of benchmarking LLMs have also been pushed towards fluency in Python, and related frameworks like Django and Flask. For example, SWE-Bench Verified is nearly 50% Django framework PR tasks: https://epoch.ai/blog/what-skills-does-swe-bench-verified-ev...
It will be interesting to see how durable these biases are as labs work towards developing more capable small models that are less reliant on memorized information. My naive instinct is that these biases will be less salient over time as context windows improve and models become increasingly capable of processing documentation as a part of their code writing loop, but also that, in the absence of instruction to the contrary, the models will favor working with these tools as a default for quite some time.
No you don’t. The US government has already completed projects at this scale without total economic mobilization: https://en.wikipedia.org/wiki/Utah_Data_Center Presumably peer and near-peer states are similarly capable.
Datacenter construction is a one-time cost. The intelligence the datacenter (might) provide is ongoing. It’s not an equal one to one trade, and well within reach for many state and non-state actors if it is desired.
It’s potentially going to be a very interesting decade.
I don't think that's right. Free societies don't tolerate total mobilization by their governments outside of war time, no matter how valuable the outcomes might be in the long term, in part because of the very economic impacts you describe. Human-level AI - even if it's very expensive - puts something that looks a lot like total mobilization within reach without the societal pushback. This is especially true when it comes to tasks that society as a whole may not sufficiently value, but that a state actor might value very much, and when paired with something like a co-located reactor and data center that does not impact the grid.
That said, this is all predicated on o3 or similar actually having achieved human level reasoning. That's yet to be fully proven. We'll see!
The cost to run the highest performance o3 model is estimated to be somewhere between $2,000 and $3,400 per task.[1] Based on these estimates, o3 costs about 100x what it would cost to have a human perform the exact same task. Many people are therefore dismissing the near-term impact of these models because of these extremely expensive costs.
I think this is a mistake.
Even if very high costs make o3 uneconomic for businesses, it could be an epoch defining development for nation states, assuming that it is true that o3 can reason like an averagely intelligent person.
Consider the following questions that a state actor might ask itself: What is the cost to raise and educate an average person? Correspondingly, what is the cost to build and run a datacenter with a nuclear power plant attached to it? And finally, how many person-equivilant AIs could be run in parallel per datacenter?
There are many state actors, corporations, and even individual people who can afford to ask these questions. There are also many things that they'd like to do but can't because there just aren't enough people available to do them. o3 might change that despite its high cost.
So if it is true that we've now got something like human-equivilant intelligence on demand - and that's a really big if - then we may see its impacts much sooner than we would otherwise intuit, especially in areas where economics takes a back seat to other priorities like national security and state competitiveness.
The idea is that you get to choose your immediate neighbors (on any basis other than race, because race is always protected) if they share the same house with you. When you're running a business the tenants aren't your immediate neighbors, so you don't get to choose them based on certain protected criteria. You can only choose them based on their ability to pay, for instance, or any other criteria not deemed to be socially harmful.
> There seems to be some underlying principle that we'll ask you to put your property & other tenants' lives at risk in the service of Ending Discrimination, but not your own
Seriously? If you think that renting to minorities or other protected classes means "putting your property & other tenants' lives at risk," then I just don't know what to tell you here.
> That's legislation, not a principle. If I ask "why is mortgage interest deductible", the principle is "because it encourages homeownership" - not the 1986 Tax Reform Act.
Intentionally obtuse it is!
The reason it's permissible is because the exception is permitted under the Act. It's not predicated on some vague legal principal (nor, for that matter, is your example - that's a policy reason, not a legal one).
If you want the policy justification for permitting discrimination in one case but not the other, it's exactly what you outline above: there is a significant difference between renting out a portion of your own home, and renting a property exclusively for business purposes (i.e. real estate investment): https://fairhousing.foxrothschild.com/2010/06/articles/fha-b...
> I suspect legally most airbnb landlords are in the clear.
Watch it on this - despite the exceptions in the FHA, exceptions never apply to racial discrimination. IANAL, but the discrimination outlined in the article is unlawful, regardless of any exceptions. Plus, state law often supplements the FHA to close off many of the exceptions.
> No people should not be forced to let anyone in their homes. This is unreasonable.
The Fair Housing Act says otherwise (with respect to race and a few other categories), owner occupied rentals and small time single-family landlords excepted. No one is forcing you to rent out your property for profit, so if you don't want to let certain people in your house, don't rent it out on Airbnb.
It will be interesting to see how durable these biases are as labs work towards developing more capable small models that are less reliant on memorized information. My naive instinct is that these biases will be less salient over time as context windows improve and models become increasingly capable of processing documentation as a part of their code writing loop, but also that, in the absence of instruction to the contrary, the models will favor working with these tools as a default for quite some time.