Collections of humans organized into groups and institutions provide many historical examples of the creation and attempted control of intelligences that routinely outperform individual humans. A preliminary look at the available evidence suggests that individuals
Terms A AI timeline An expectation about how much time will lapse before important AI events, especially the advent of human-level AI or a similar milestone. The term can also refer to the actual periods of time (which are not
We are offering rewards for several inputs to our research, described below. These offers have no specific deadline except where noted. We may modify them or take them down, but will give at least one week’s notice
Computing hardware which is equivalent to the brain – in terms of FLOPS probably costs between $1 x 105 and $3 x 1016, or $2/hour-$700bn/hour. in terms of TEPS probably costs $200M – $7B, or or $4,700 – $170,000/hour
The computing power needed to replicate the human brain’s relevant activities has been estimated by various authors, with answers ranging from 1012 to 1028 FLOPS. Details Notes We have not investigated the brain’s performance in FLOPS in
Hardware in terms of computing capacity (FLOPS and MIPS) Brain performance in FLOPS 2019 recent trends in GPU price per FLOPS Electrical efficiency of computing 2018 price of performance by Tensor Processing Units 2017 trend in
It costs roughly $300-$3000 to buy enough storage space to store all information contained by a human brain. Support The human brain probably stores around 10-100TB of data. Data storage costs around $30/TB. Thus it costs roughly $300-$3000 to buy
Posted 23 July 2015 Cheap secondary memory appears to cost around $0.03/GB in 2015. In the long run the price has declined by an order of magnitude roughly every 4.6 years. However the rate has declined so much that prices haven’t substantially dropped since 2011 (in 2015).
Posted 13 July 2015 Participants Professor Steve Potter – Associate Professor, Laboratory of NeuroEngineering, Coulter Department of Biomedical Engineering, Georgia Institute of Technology Katja Grace – Machine Intelligence Research Institute (MIRI) Note: These notes were