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ai_timelines:brain_performance_in_flops [2022/09/21 07:37] (current)
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| | ====== Brain performance in FLOPS ====== |
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| | // Published 26 July, 2015; last updated 06 July, 2019 // |
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| | <p>The computing power needed to replicate the human brain’s relevant activities has been estimated by various authors, with answers ranging from 10<sup>12</sup> to 10<sup>28</sup> FLOPS.</p> |
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| | ===== Details ===== |
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| | ==== Notes ==== |
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| | <p>We have not investigated the brain’s performance in FLOPS in detail, nor substantially reviewed the literature since 2015. This page summarizes others’ estimates that we are aware of, as well as the implications of our investigation into brain performance in TEPS.</p> |
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| | ==== Estimates ==== |
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| | === Sandberg and Bostrom 2008: estimates and review === |
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| | <p><a href="http://www.fhi.ox.ac.uk/brain-emulation-roadmap-report.pdf">Sandberg and Bostrom</a> project the processing required to emulate a human brain at different levels of detail.<span class="easy-footnote-margin-adjust" id="easy-footnote-1-596"></span><span class="easy-footnote"><a href="#easy-footnote-bottom-1-596" title='From <a href="http://www.fhi.ox.ac.uk/brain-emulation-roadmap-report.pdf">Sandberg and Bostrom</a>, table 9: Processing demands (emulation only, human brain)(p80):</p> <ul> <li>spiking neural network: 10<sup>18</sup> FLOPS (Earliest year, $1 million: commodity computer estimate: 2042, supercomputer estimate: 2019)</li> <li>electrophysiology: 10<sup>22</sup> FLOPS (Earliest year, $1 million: commodity computer estimate: 2068, supercomputer estimate: 2033)</li> <li>metabolome: 10<sup>25</sup> FLOPS (Earliest year, $1 million: commodity computer estimate: 2087, supercomputer estimate: 2044)</li> </ul> '><sup>1</sup></a></span> For the three levels that their workshop participants considered most plausible, their estimates are 10<sup>18</sup>, 10<sup>22</sup>, and 10<sup>25</sup> FLOPS.</p> |
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| | <p>They also summarize other brain compute estimates, as shown below (we reproduce their Table 10).<span class="easy-footnote-margin-adjust" id="easy-footnote-2-596"></span><span class="easy-footnote"><a href="#easy-footnote-bottom-2-596" title='See appendix A, <span style="font-weight: 400;">Nick Bostrom and Anders Sandberg, “Whole Brain Emulation: A Roadmap,” 2008, 130.</span>'><sup>2</sup></a></span> We have not reviewed these estimates, and some do not appear superficially credible to us.</p> |
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| | === Drexler 2018 === |
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| | <p>Drexler looks at multiple comparisons between narrow AI tasks and neural tasks, and finds that they suggest the ‘basic functional capacity’ of the human brain is less than one petaFLOPS (10<sup>15</sup>).<span class="easy-footnote-margin-adjust" id="easy-footnote-3-596"></span><span class="easy-footnote"><a href="#easy-footnote-bottom-3-596" title='&#8220;Multiple comparisons between narrow AI tasks and narrow neural tasks concur in suggesting that PFLOP/s computational systems exceed the basic functional capacity of the human brain.&#8221;</p> <p><span style="font-weight: 400;">K Eric Drexler, “Reframing Superintelligence,” 2019, 182.</span>'><sup>3</sup></a></span></p> |
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| | === Conversion from brain performance in TEPS === |
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| | <p>Among a small number of computers we compared<span class="easy-footnote-margin-adjust" id="easy-footnote-4-596"></span><span class="easy-footnote"><a href="#easy-footnote-bottom-4-596" title='&#8220;The [eight] supercomputers measured here consistently achieve around 1-2 GTEPS per scaled TFLOPS (see Figure 3). The median ratio is 1.9 GTEPS/TFLOPS, the mean is 1.7 GTEPS/TFLOP, and the variance 0.14 GTEPS/TFLOP. &#8221; See <em>Relationship between FLOPS and TEPS </em><a href="http://aiimpacts.org/cost-of-teps/">here</a> for more details'><sup>4</sup></a></span>, FLOPS and TEPS seem to vary proportionally, at a rate of around 1.7 GTEPS/TFLOP. We also <a href="/doku.php?id=ai_timelines:brain_performance_in_teps">estimate</a> that the human brain performs around 0.18 – 6.4 * 10<sup>14</sup> TEPS. Thus if the FLOPS:TEPS ratio in brains is similar to that in computers, a brain would perform around 0.9 – 33.7 * 10<sup>16</sup> FLOPS.<span class="easy-footnote-margin-adjust" id="easy-footnote-5-596"></span><span class="easy-footnote"><a href="#easy-footnote-bottom-5-596" title="0.18 – 6.4 * 10<sup>14</sup> TEPS =0.18 – 6.4 * 10<sup>5</sup> GTEPS =0.18 – 6.4 * 10<sup>5</sup> GTEPS * 1TFLOPS/1.9GTEPS = 9,000-337,000 TFLOPS = 0.9 &#8211; 33.7 * 10<sup>16</sup>FLOPS"><sup>5</sup></a></span> We have not investigated how similar this ratio is likely to be.</p> |
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| | ===== Notes ===== |
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| | <ol class="easy-footnotes-wrapper"> |
| | <li><div class="li"> |
| | <span class="easy-footnote-margin-adjust" id="easy-footnote-bottom-1-596"></span>From <a href="http://www.fhi.ox.ac.uk/brain-emulation-roadmap-report.pdf">Sandberg and Bostrom</a>, table 9: Processing demands (emulation only, human brain)(p80): |
| | <ul> |
| | <li><div class="li">spiking neural network: 10<sup>18</sup> FLOPS (Earliest year, $1 million: commodity computer estimate: 2042, supercomputer estimate: 2019)</div></li> |
| | <li><div class="li">electrophysiology: 10<sup>22</sup> FLOPS (Earliest year, $1 million: commodity computer estimate: 2068, supercomputer estimate: 2033)</div></li> |
| | <li><div class="li">metabolome: 10<sup>25</sup> FLOPS (Earliest year, $1 million: commodity computer estimate: 2087, supercomputer estimate: 2044)</div></li> |
| | </ul><a class="easy-footnote-to-top" href="#easy-footnote-1-596"></a> |
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| | <span class="easy-footnote-margin-adjust" id="easy-footnote-bottom-2-596"></span>See appendix A, <span style="font-weight: 400">Nick Bostrom and Anders Sandberg, “Whole Brain Emulation: A Roadmap,” 2008, 130.</span><a class="easy-footnote-to-top" href="#easy-footnote-2-596"></a> |
| | </div></li> |
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| | <span class="easy-footnote-margin-adjust" id="easy-footnote-bottom-3-596"></span>“Multiple comparisons between narrow AI tasks and narrow neural tasks concur in suggesting that PFLOP/s computational systems exceed the basic functional capacity of the human brain.” |
| | <p><span style="font-weight: 400">K Eric Drexler, “Reframing Superintelligence,” 2019, 182.</span><a class="easy-footnote-to-top" href="#easy-footnote-3-596"></a></p> |
| | </div></li> |
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| | <span class="easy-footnote-margin-adjust" id="easy-footnote-bottom-4-596"></span>“The [eight] supercomputers measured here consistently achieve around 1-2 GTEPS per scaled TFLOPS (see Figure 3). The median ratio is 1.9 GTEPS/TFLOPS, the mean is 1.7 GTEPS/TFLOP, and the variance 0.14 GTEPS/TFLOP. ” See <em>Relationship between FLOPS and TEPS</em> <a href="/doku.php?id=ai_timelines:the_cost_of_teps">here</a> for more details<a class="easy-footnote-to-top" href="#easy-footnote-4-596"></a> |
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| | <span class="easy-footnote-margin-adjust" id="easy-footnote-bottom-5-596"></span>0.18 – 6.4 * 10<sup>14</sup> TEPS =0.18 – 6.4 * 10<sup>5</sup> GTEPS =0.18 – 6.4 * 10<sup>5</sup> GTEPS * 1TFLOPS/1.9GTEPS = 9,000-337,000 TFLOPS = 0.9 – 33.7 * 10<sup>16</sup>FLOPS<a class="easy-footnote-to-top" href="#easy-footnote-5-596"></a> |
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