<story><title>Cerebras Systems unveils a 1.2T transistor chip for AI</title><url>https://venturebeat.com/2019/08/19/cerebras-systems-unveils-a-record-1-2-trillion-transistor-chip-for-ai/</url></story><parent_chain><item><author>modeless</author><text>There are far more transistors in this chip than neurons in the human brain. In 100 of these chips, there are more transistors than there are synapses in the human brain.&lt;p&gt;I don&amp;#x27;t mean to suggest that transistors are equivalent to neurons or synapses; clearly they are very different things (though it is &lt;i&gt;not&lt;/i&gt; clear that neurons are much more computationally powerful than transistors, despite assertions from many people that this is the case). But I think it is still useful to compare the complexity of structure of chips vs. the human brain. We are finally approaching the same order of magnitude of complexity in structure.&lt;p&gt;Also note that this is not manufactured on TSMC&amp;#x27;s highest density process. Assuming TSMC&amp;#x27;s 3nm process development is successful, that will probably be 6x denser than the 16nm process used here.</text></item></parent_chain><comment><author>jacquesm</author><text>A few buckets of sand also contain more elements than there are synapses in the human brain. They clearly lack any structure, and so are computationally stuck at a big fat &amp;#x27;0&amp;#x27; no matter what you do with the sand (unless you want to turn it into a giant abacus or turn it into integrated circuits).&lt;p&gt;Where on the scale between a few buckets of sand and an actual working human brain this chip is is not so much a function of it&amp;#x27;s structure but of &lt;i&gt;what it does&lt;/i&gt;, and the brain&amp;#x27;s finer structures are so complex that even modelling a few neurons is going to crush that complexity downwards by so many orders of magnitude that we simply hope that we are not accidentally throwing out the useful bits in the simulation.&lt;p&gt;That&amp;#x27;s a roundabout way of saying that I think that:&lt;p&gt;&amp;gt; We are finally approaching the same order of magnitude of complexity in structure.&lt;p&gt;Is not necessarily true in a way that is relevant. The parts count or basic interconnection may have nothing to do with how the brain is connected internally, nor with how it functions at the lowest levels.</text></comment>
<story><title>Cerebras Systems unveils a 1.2T transistor chip for AI</title><url>https://venturebeat.com/2019/08/19/cerebras-systems-unveils-a-record-1-2-trillion-transistor-chip-for-ai/</url></story><parent_chain><item><author>modeless</author><text>There are far more transistors in this chip than neurons in the human brain. In 100 of these chips, there are more transistors than there are synapses in the human brain.&lt;p&gt;I don&amp;#x27;t mean to suggest that transistors are equivalent to neurons or synapses; clearly they are very different things (though it is &lt;i&gt;not&lt;/i&gt; clear that neurons are much more computationally powerful than transistors, despite assertions from many people that this is the case). But I think it is still useful to compare the complexity of structure of chips vs. the human brain. We are finally approaching the same order of magnitude of complexity in structure.&lt;p&gt;Also note that this is not manufactured on TSMC&amp;#x27;s highest density process. Assuming TSMC&amp;#x27;s 3nm process development is successful, that will probably be 6x denser than the 16nm process used here.</text></item></parent_chain><comment><author>jdsully</author><text>I haven’t seen a perceptron circuit done in less than 4 transistors plus a few diodes. However these chips are almost certainly digital and will use a lot more to perform the floating point math.&lt;p&gt;Single transistors can’t even compute our simplified model of a neuron let alone the complexities of the real thing.</text></comment>