This year’s report includes “new analysis on foundation models, including their geopolitics and training costs, the environmental impact of AI systems, K-12 AI education, and public opinion trends in AI,” plus a look at policy in a hundred new countries. But the report goes into detail on many topics and sub-topics, and is quite readable and non-technical. Only the dedicated will read all 300-odd pages of analysis, but really, just about any motivated body could.
For the highest-level takeaways, let us just bullet them here:
– AI development has flipped over the last decade from academia-led to industry-led, by a large margin, and this shows no sign of changing. – It’s becoming difficult to test models on traditional benchmarks and a new paradigm may be needed here. – The energy footprint of AI training and use is becoming considerable, but we have yet to see how it may add efficiencies elsewhere. – The number of “AI incidents and controversies” has increased by a factor of 26 since 2012, which actually seems a bit low. – AI-related skills and job postings are increasing, but not as fast as you’d think. – Policymakers, however, are falling over themselves trying to write a definitive AI bill, a fool’s errand if there ever as one. – Investment has temporarily stalled, but that’s after an astronomic increase over the last decade. – More than 70% of Chinese, Saudi, and Indian respondents felt AI had more benefits than drawbacks. Americans? 35%. The full report can be found here.
Read more of this story at Slashdot.