<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>aseipp</author><text>People constantly bring this point up every 2 weeks here, the cost competitiveness of TPUs for Google comes exactly from the fact they make them in house and don&amp;#x27;t sell them. They don&amp;#x27;t need sales channels, support, leads, any of that stuff. They can design for exactly one software stack, one hardware stack, and one set of staff. You cannot just magically spin up a billion-dollar hardware company overnight with software, customers, sales channels and support, etc.&lt;p&gt;Nvidia has spent 20 years on this which is why they&amp;#x27;re good at it.&lt;p&gt;&amp;gt; If it was separate to Google then there a bunch of companies who would happily spend some money on a real, working NVidia alternative.&lt;p&gt;Unfortunately, most people really don&amp;#x27;t care about Nvidia alternatives, actually -- they care about price, above all else. People will say they want Nvidia alternatives and support them, then go back to buying Nvidia the moment the price goes down. Which is fine, to be clear, but this is not the outcome people often allude to.</text><parent_chain><item><author>nl</author><text>It&amp;#x27;s crazy that Google doesn&amp;#x27;t spin-out their TPU work as a separate company.&lt;p&gt;TPUs are the second most widely used environment for training after Nvidia. It&amp;#x27;s the only environment that people build optimized kernels for outside CUDA.&lt;p&gt;If it was separate to Google then there a bunch of companies who would happily spend some money on a real, working NVidia alternative.&lt;p&gt;It might be profitable from day one, and it surely would gain substantial market capitalization - Alphabet shareholders should be agitating for this!</text></item></parent_chain></comment><story><title>TPU transformation: A look back at 10 years of our AI-specialized chips</title><url>https://cloud.google.com/blog/transform/ai-specialized-chips-tpu-history-gen-ai</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>jankeymeulen</author><text>The TPUs are highly integrated with the rest of the internal Google ecosystem, both hardware and software. Untangling that would be ... interesting.</text><parent_chain><item><author>nl</author><text>It&amp;#x27;s crazy that Google doesn&amp;#x27;t spin-out their TPU work as a separate company.&lt;p&gt;TPUs are the second most widely used environment for training after Nvidia. It&amp;#x27;s the only environment that people build optimized kernels for outside CUDA.&lt;p&gt;If it was separate to Google then there a bunch of companies who would happily spend some money on a real, working NVidia alternative.&lt;p&gt;It might be profitable from day one, and it surely would gain substantial market capitalization - Alphabet shareholders should be agitating for this!</text></item></parent_chain></comment><story><title>TPU transformation: A look back at 10 years of our AI-specialized chips</title><url>https://cloud.google.com/blog/transform/ai-specialized-chips-tpu-history-gen-ai</url></story>