We really need to band together to fund / sponsor targeted inducement prizes (a la Nobel laureate Michael Kremer) for open models.
Every 6-12 months, give out $200K to the first model to hit a min threshold on a set of ~5-10 hard benchmarks (+ perhaps one secret benchmark) using a total of 16GB / 32GB / 64GB / 128GB of VRAM (at a min context length of 200K), then move the threshold up. Quantization etc. is dealers choice, it just needs to nail the benchmark on a reference machine by using exactly that much VRAM (no mapping to RAM / disk etc.)
You could crowdsource the funding, and cross subsidize by adding targeted prizes focused on corporate needs (the classic one is PDF processing benchmarks), and say that 25% of each corporate prize funding also flows into the general prize pool.
For a lot of these open-source model companies, it's less about the $s (though $200K is nothing to sneeze at), it's the clear recognition that helps their model efforts stand out, gain usage etc.
They already invest in open-source AI, but nothing is truly free. Commercial AI will usually dominate because devs are paid to make it their primary effort. Goodwill and part-time contributions cannot reliably compete with livelihood and profit incentives.
I'd rather the US fund universal childcare, medicare for all, and free school lunches than give a cent to subsidize a technology the American public absolute hates.
Number one expense for SMB is healthcare, providing a nationalized healthcare service would likely unlock trillions in value (imagine what Americans would do if they got $200-500 more per paycheck?).
Instead we are forced to watch some of the wealthiest companies on the planet burn money for fun because apparently the government is "wasteful."
We really need to band together to fund / sponsor targeted inducement prizes (a la Nobel laureate Michael Kremer) for open models.
Every 6-12 months, give out $200K to the first model to hit a min threshold on a set of ~5-10 hard benchmarks (+ perhaps one secret benchmark) using a total of 16GB / 32GB / 64GB / 128GB of VRAM (at a min context length of 200K), then move the threshold up. Quantization etc. is dealers choice, it just needs to nail the benchmark on a reference machine by using exactly that much VRAM (no mapping to RAM / disk etc.)
You could crowdsource the funding, and cross subsidize by adding targeted prizes focused on corporate needs (the classic one is PDF processing benchmarks), and say that 25% of each corporate prize funding also flows into the general prize pool.
For a lot of these open-source model companies, it's less about the $s (though $200K is nothing to sneeze at), it's the clear recognition that helps their model efforts stand out, gain usage etc.
They already invest in open-source AI, but nothing is truly free. Commercial AI will usually dominate because devs are paid to make it their primary effort. Goodwill and part-time contributions cannot reliably compete with livelihood and profit incentives.
I'd rather the US fund universal childcare, medicare for all, and free school lunches than give a cent to subsidize a technology the American public absolute hates.
Redistribution can only get you so far. Creating new wealth is more sustainable.
So why did we stop doing that in favour of winner takes all weath centralisation?
Number one expense for SMB is healthcare, providing a nationalized healthcare service would likely unlock trillions in value (imagine what Americans would do if they got $200-500 more per paycheck?).
Instead we are forced to watch some of the wealthiest companies on the planet burn money for fun because apparently the government is "wasteful."
What a crock of shit.
How would nationalized healthcare get funded other than shifting that 200-500/check towards… nationalized healthcare?