I feel that in a sense, "we" (the collective society) can do a lot because of the productivity growth from technology "afford" (enable) us.
In another sense, what "we" (part of that society -- an individual, a group, a government) can do is limited by what we can "afford" (pay). We cannot command the bricks and mortar and steel and cement and labor and architects to build houses and infrastructure without some form of compensation -- money for the architects and builders and cement/steel/mortar/brick makers and movers to exchange for food, drink, and shelter.
And in this grim budget situation, "we" (the government) are running out of ways to ask for productivity (goods and services for healthcare, education, welfare, defense) because we are out of ways to compensate the providers.
What can a government do then?
- force them to offer productivity without equal compensation (communism, colonialism, slavery, forced labor, cheap labor, unequal trade agreements, etc.)
- promise to repay them later (government bonds)
- give them something that they think is valuable but is less so and decreasingly so (money printing)
- encourage giving without compensation (charitable work and donation)
- repay them with compensation collected from those who benefited the most from the economic productivity growth (taxing)
I think the quote "We can afford what we can actually do" encourages the audience to think more about what we (as a society) can do and less about how we (the individual) are compensated.
Reminds me of Mondragón, a corporation and federation of worker coops in Spain. It builds new coops to meet the needs of its community, and when a coop ends, workers are given financial support and trained for new jobs in its other coops.
LMArena might have some of the information you are looking for. It offers rankings of LLM models across main cloud offerings, and I feel that its evaluation method, human prompting and voting, is closer to real-world use case and less prone to data contamination than benchmarks.
In the "Leaderboard">"Language" tab, it lists the top models in various categories such as overall, coding, math, and creative writing.
In the "Leaderboard">"Price Analysis" tab, it shows a chart comparing models by cost per million tokens.
In the "Prompt-to-Leaderboard" tab, there is even an LLM to help you find LLMs -- you enter a prompt, and it will find the top models for your particular prompt.
With the recent flurry of historic events unfolding, I want to see it from different perspectives (e.g. U.S., Europe, Russia, China, pro-Palestine vs Pro-Israel), therefore I included channels from all these areas, even channels that may be considered propaganda. So keep a critical eye when watching them.
And it's a way for me to try out Vidstack and SvelteKit. Feels like the routing can be improved though.