I think there have been two big changes (and some of this is a personal opinion).
1.
I think it is harder to think about software patents as valuable or even viable these days because the technology stacks keep changing at such a rapid pace. One of the reasons I truly treasure and love my R&D past is that we were just entering the mobile revolution and ubiquitous computing & social networking were huge disruptors but also opportunities to innovate. We could ask hard questions (e.g., How can I make ad hoc networking apps without depleting the battery) and have the time/resources to focus on finding the right solutions. Today, the pace is harder and patience shorter from investors. We see companies cutting corners and making unethical decisions in the name of valuation - without actually thinking about how it advances the broader technology discourse. I miss the humanity behind engineering and the people who genuinely thought of innovation as a way to make something better (not someone richer)
2.
I think the focus today is going to be on Artificial Intelligence. I am excited but also puzzled by what "invention" will mean when the "learning" is all by machines. Do they see nuances of behavior? So a huge asset for any inventor is not necessarily learning how to solve the problem for the FIRST time, but realizing that the problem may have been solved in a DIFFERENT domain and then finding a way to translate the context and the solutions to the current need. This to me was the most important (and most fulfilling) part of research - finding and making connections that matter. But when we come to AI, its learning is driven by the examples we provide. Are we providing enough diversity for it to make these connections across disciplines? I don't know. I think that anyone looking to write up a software patent today needs to ask "how does this method or system change if the interfaces between the components change?" -- needs us to start thinking in a new way about what invention means.
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I think there have been two big changes (and some of this is a personal opinion).
1.
I think it is harder to think about software patents as valuable or even viable these days because the technology stacks keep changing at such a rapid pace. One of the reasons I truly treasure and love my R&D past is that we were just entering the mobile revolution and ubiquitous computing & social networking were huge disruptors but also opportunities to innovate. We could ask hard questions (e.g., How can I make ad hoc networking apps without depleting the battery) and have the time/resources to focus on finding the right solutions. Today, the pace is harder and patience shorter from investors. We see companies cutting corners and making unethical decisions in the name of valuation - without actually thinking about how it advances the broader technology discourse. I miss the humanity behind engineering and the people who genuinely thought of innovation as a way to make something better (not someone richer)
2.
I think the focus today is going to be on Artificial Intelligence. I am excited but also puzzled by what "invention" will mean when the "learning" is all by machines. Do they see nuances of behavior? So a huge asset for any inventor is not necessarily learning how to solve the problem for the FIRST time, but realizing that the problem may have been solved in a DIFFERENT domain and then finding a way to translate the context and the solutions to the current need. This to me was the most important (and most fulfilling) part of research - finding and making connections that matter. But when we come to AI, its learning is driven by the examples we provide. Are we providing enough diversity for it to make these connections across disciplines? I don't know. I think that anyone looking to write up a software patent today needs to ask "how does this method or system change if the interfaces between the components change?" -- needs us to start thinking in a new way about what invention means.