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Software 2.0 is happening right now. GTP-3 and Tesla FSD are examples of this.

On the other hand software 1.0 was a victim of it success. People realized that they could build software companies with SQL hard coded into windows forms buttons. Theses people have never even heard the word extensibility. Like the rest of corporate America they are mostly focused on the next quarter results and drown out any voices from people who want to innovative for innovation sake.




> Software 2.0 is happening right now. GTP-3 and Tesla FSD are examples of this.

I agree with this. As an anecdote, I've spent the past decade explaining to clients that things like natural language question answering and abstractive summarization are impossible, and now we have OpenAI and others dropping pretrained models like https://github.com/openai/summarize-from-feedback that turn all those assumptions on their head. There are caveats, of course, but I've gone from a deep learning skeptic (I started my career with "traditional" ML and NLP) to believing that these sorts of techniques are truly revolutionary and we are only yet scratching the surface of what's possible with them.


> People realized that they could build software companies with SQL hard coded into windows forms buttons. Theses people have never even heard the word extensibility.

Is there anything wrong with this?


>> Is there anything wrong with this?

No. Building something useful is good. It's just not an example of technological progress. That's what they meant by a victim of it's own success. When something advances enough to be useful it's natural for a bunch of people to just make use of it as-is.


Depends. For a quick prototype or small project? Seems fine. For a project with changing requirements and planned long term use (read: most software), it's probably best to not mix all your technologies in a single layer.


From your examples, it seems like you mean AI applications. Is that what you mean by software 2.0, or am I missing something?




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