The capitalist mindset. #Amazon is just another store. #Turkey is just another holiday destination. A #Cybertruck is just another mode of transport. #Nestle is just another coffee brand. Factory farmed #chicken is just another source of protein. #LLMs (#AI) are just another tool.
#Capitalism needs you to ignore the social and environmental costs, and think only of personal benefits.
When the greed becomes automatist, something like this happens here:
Β»Open Source World β FOSS infrastructure is under attack by AI companies: LLM scrapers are taking down FOSS projects' infrastructure, and it's getting worse.Β«
OK really it's called "Survival Game" but that's the basic idea. Some Cornell researchers decided to put various LLMs through their paces, giving them a limited number of tries to solve a variety of problems, and eliminating those that failed in successive rounds of evaluation. I do NOT have the time to read this comprehensively, but from the intro:
Our results show that while AI systems achieve the Autonomous Level in simple tasks, they are still far from it in more complex tasks, such as vision, search, recommendation, and language. While scaling current AI technologies might help, this would come at an astronomical cost. Projections suggest that achieving the Autonomous Level for general tasks would require 1026 parameters. To put this into perspective, loading such a massive model requires so many H100 GPUs that their total value is 4 Γ 107 times that of Apple Inc.βs market value. Even with Mooreβs Law, supporting such a parameter scale would take 70 years. This staggering cost highlights the complexity of human
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Hunger Games for AI
OK really it's called "Survival Game" but that's the basic idea. Some Cornell researchers decided to put various LLMs through their paces, giving them a limited number of tries to solve a variety of problems, and eliminating those that failed in successive rounds of evaluation. I do NOT have the time to read this comprehensively, but from the intro:
Our results show that while AI systems achieve the Autonomous Level in simple tasks, they are still far from it in more complex tasks, such as vision, search, recommendation, and language. While scaling current AI technologies might help, this would come at an astronomical cost. Projections suggest that achieving the Autonomous Level for general tasks would require 1026 parameters. To put this into perspective, loading such a massive model requires so many H100 GPUs that their total value is 4 Γ 107 times that of Apple Inc.βs market value. Even with Mooreβs Law, supporting such a parameter scale would take 70 years. This staggering cost highlights the complexity of human tasks and the inadequacies of current AI technologies.
