<story><title>Google and a nuclear fusion company have developed a new algorithm</title><url>https://www.theguardian.com/environment/2017/jul/25/google-enters-race-for-nuclear-fusion-technology</url></story><parent_chain></parent_chain><comment><author>abefetterman</author><text>This is actually a really exciting development to me. (Note, what is exciting is the &amp;quot;optometrist algorithm&amp;quot; from the paper [1] not necessarily googles involvement as pitched in the guardian). Typically a day of shots would need to be programmed out in advance, typically scanning over one dimension (out of hundreds) at a time. It would then take at least a week to analyze the results and create an updated research plan. The result is poor utilization of each experiment in optimizing performance. The 50% reduction in losses is a big deal for Tri Alpha.&lt;p&gt;I can see this being coupled with simulations as well to understand sources of systematic errors, create better simulations which can then be used as a stronger source of truth for &amp;quot;offline&amp;quot; (computation-only) experiments.&lt;p&gt;The biggest challenge of course becomes interpreting the results. So you got better performance, what parameters really made a difference and why? But that is at least a more tractable problem than &amp;quot;how do we make this better in the first place?&amp;quot;&lt;p&gt;[1] &lt;a href=&quot;http:&amp;#x2F;&amp;#x2F;www.nature.com&amp;#x2F;articles&amp;#x2F;s41598-017-06645-7&quot; rel=&quot;nofollow&quot;&gt;http:&amp;#x2F;&amp;#x2F;www.nature.com&amp;#x2F;articles&amp;#x2F;s41598-017-06645-7&lt;/a&gt;</text></comment>
<story><title>Google and a nuclear fusion company have developed a new algorithm</title><url>https://www.theguardian.com/environment/2017/jul/25/google-enters-race-for-nuclear-fusion-technology</url></story><parent_chain></parent_chain><comment><author>briankelly</author><text>From the actual journal article:&lt;p&gt;&amp;gt; Two additional complications arise because plasma fusion apparatuses are experimental and one-of-a-kind. First, the goodness metric for plasma is not fully established and objective: some amount of human judgement is required to assess an experiment. Second, the boundaries of safe operation are not fully understood: it would be easy for a fully-automated optimisation algorithm to propose settings that would damage the apparatus and set back progress by weeks or months.&lt;p&gt;&amp;gt; To increase the speed of learning and optimisation of plasma, we developed the Optometrist Algorithm. Just as in a visit to an optometrist, the algorithm offers a pair of choices to a human, and asks which one is preferable. Given the choice, the algorithm proceeds to offer another choice. While an optometrist asks a patient to choose between lens prescriptions based on clarity, our algorithm asks a human expert to choose between plasma settings based on experimental outcomes. The Optometrist Algorithm attempts to optimise a hidden utility model that the human experts may not be able to express explicitly.&lt;p&gt;I haven&amp;#x27;t read the full article nor do I understand the problem space, but the novelty seems overstated based on this. Maybe they can eventually collect metadata to automate the human intuition.&lt;p&gt;Edit: here&amp;#x27;s their formal description of it: &lt;a href=&quot;https:&amp;#x2F;&amp;#x2F;www.nature.com&amp;#x2F;articles&amp;#x2F;s41598-017-06645-7&amp;#x2F;figures&amp;#x2F;2&quot; rel=&quot;nofollow&quot;&gt;https:&amp;#x2F;&amp;#x2F;www.nature.com&amp;#x2F;articles&amp;#x2F;s41598-017-06645-7&amp;#x2F;figures&amp;#x2F;2&lt;/a&gt;</text></comment>