<instructions>Your goal is to analyze the following comment and estimate how highly it will be upvoted by the Hacker News community.</instructions><comment><author>csantini</author><text>This is also one reason why Tensor Flow is open. Yes, Google wants it to become the standard, but it&amp;#x27;s also not a competitive advantage.&lt;p&gt;The advantage is not the Deep Learning algorithm.&lt;p&gt;Some theoretical progress has been made on Neural Networks lately, but largely it&amp;#x27;s the same stuff from the 90s, with much more GPUs and data.&lt;p&gt;The competitive advantage is the cloud, and the software mess that keeps it alive.&lt;p&gt;I think Deep Learning experts will be like Linux Kernel experts. You need 1000 kernel experts in the world, but you need 10 million javascript monkeys that code what dialog message appears when the user does something stupid in some app.</text><parent_chain><item><author>csantini</author><text>TL;DR: Deep Learning will become a commodity. Software will eat Deep Learning too.&lt;p&gt;I&amp;#x27;d like to clean up a bit the air from the hype fog:&lt;p&gt;DL is giving amazing results only when you have big sets of labelled data. Hence it will be much cheaper for companies to buy Google&amp;#x2F;Microsoft Vision&amp;#x2F;Audio REST APIs rather than paying the costs of: cloud + find data + deep learning experts. So, I don&amp;#x27;t think we will see a massive growth of DL gigs.&lt;p&gt;e.g. Google Vision API: &lt;a href=&quot;https:&amp;#x2F;&amp;#x2F;cloud.google.com&amp;#x2F;vision&amp;#x2F;&quot; rel=&quot;nofollow&quot;&gt;https:&amp;#x2F;&amp;#x2F;cloud.google.com&amp;#x2F;vision&amp;#x2F;&lt;/a&gt;&lt;p&gt;Except those areas where your own CNN implementation is needed (automotive, industrial automation), Deep Learning will be another &amp;quot;library&amp;quot; in the ever increasing Software Engineering mess of gluing many open source libraries and REST apis to get something useful done. You need 1 guy training a Neural Network for every 100 software monkeys maintaining the infrastructure complexity.
There are now many Software Engineering jobs because it&amp;#x27;s hard to glue and maintain publicly-available code to solve some specific business problem.&lt;p&gt;I think the the same applies for many Data Scientist jobs, which are these days more about fetching&amp;#x2F;cleaning&amp;#x2F;visualizing data than making machine learning on it.</text></item></parent_chain></comment><story><title>How to Get a Job in Deep Learning</title><url>http://blog.deepgram.com/how-to-get-a-job-in-deep-learning/</url></story>
<instructions>Your goal is to analyze the following comment and estimate how highly it will be upvoted by the Hacker News community.</instructions><comment><author>stephensonsco</author><text>For the people who want a job in deep learning, they are definitely around and they will be for a while.&lt;p&gt;It&amp;#x27;s true that DL will probably become just-another-library, but that will happen only once computing becomes extremely cheap on the petaflop scale (it isn&amp;#x27;t cheap yet). Even after that happens, the people that spend time doing DL now will be trained in a way of thinking that will be in demand for a long time.</text><parent_chain><item><author>csantini</author><text>TL;DR: Deep Learning will become a commodity. Software will eat Deep Learning too.&lt;p&gt;I&amp;#x27;d like to clean up a bit the air from the hype fog:&lt;p&gt;DL is giving amazing results only when you have big sets of labelled data. Hence it will be much cheaper for companies to buy Google&amp;#x2F;Microsoft Vision&amp;#x2F;Audio REST APIs rather than paying the costs of: cloud + find data + deep learning experts. So, I don&amp;#x27;t think we will see a massive growth of DL gigs.&lt;p&gt;e.g. Google Vision API: &lt;a href=&quot;https:&amp;#x2F;&amp;#x2F;cloud.google.com&amp;#x2F;vision&amp;#x2F;&quot; rel=&quot;nofollow&quot;&gt;https:&amp;#x2F;&amp;#x2F;cloud.google.com&amp;#x2F;vision&amp;#x2F;&lt;/a&gt;&lt;p&gt;Except those areas where your own CNN implementation is needed (automotive, industrial automation), Deep Learning will be another &amp;quot;library&amp;quot; in the ever increasing Software Engineering mess of gluing many open source libraries and REST apis to get something useful done. You need 1 guy training a Neural Network for every 100 software monkeys maintaining the infrastructure complexity.
There are now many Software Engineering jobs because it&amp;#x27;s hard to glue and maintain publicly-available code to solve some specific business problem.&lt;p&gt;I think the the same applies for many Data Scientist jobs, which are these days more about fetching&amp;#x2F;cleaning&amp;#x2F;visualizing data than making machine learning on it.</text></item></parent_chain></comment><story><title>How to Get a Job in Deep Learning</title><url>http://blog.deepgram.com/how-to-get-a-job-in-deep-learning/</url></story>