2017 – AI Impacts

Effect of marginal hardware on artificial general intelligence

We do not know how AGI will scale with marginal hardware. Several sources of evidence may shed light on this question. Details Background Suppose that at some point in the future, general artificial intelligence can be

Human-level hardware timeline

We estimate that ‘human-level hardware’— hardware able to perform as many computations per second as a human brain, at a similar cost to a human brain—has a 30% chance of having already occurred, a 45%

Chance date bias

There is modest evidence that people consistently forecast events later when asked the probability that the event occurs by a certain year, rather than the year in which a certain probability of the event will

GoCAS talk on AI Impacts findings

By Katja Grace, 27 November 2017 Here is a video summary of some highlights from AI Impacts research over the past years, from the GoCAS Existential Risk workshop in Göteborg in September. Thanks to the folks there

Price performance Moore’s Law seems slow

By Katja Grace, 26 November 2017 When people make predictions about AI, they often assume that computing hardware will carry on getting cheaper for the foreseeable future, at about the same rate that it usually

2017 trend in the cost of computing

The cheapest hardware prices (for single precision FLOPS/$) appear to be falling by around an order of magnitude every 10-16 years. This rate is slower than the trend of FLOPS/$ observed over the past quarter century,

Price-performance trend in top supercomputers

A top supercomputer can perform a GFLOP for around $3, in 2017. The price of performance in top supercomputers continues to fall, as of 2016. Details TOP500.org maintains a list of top supercomputers and their

Computing hardware performance data collections

This is a list of public datasets that we know of containing either measured or theoretical performance numbers for computer processors. List Top 500 maintains a list of the top 500 supercomputers, updated every six

2016 ESPAI Narrow AI task forecast timeline

This is an interactive timeline we made, illustrating the median dates when respondents said they expected a 10%, 50% and 90% chance of different tasks being automatable, in the 2016 Expert Survey on progress in

When do ML Researchers Think Specific Tasks will be Automated?

By Katja Grace, 26 September 2017 We asked the ML researchers in our survey when they thought 32 narrow, relatively well defined tasks would be feasible for AI. Eighteen of them were included in our paper