So we started block 3 last week. So far, I'm not doing a great job of keeping up with this blog, but I'm not too surprised.
It's difficult to know where exactly I'm heading. There's a lot of opportunities, but it's a little hard to tell which will pay off the most. Our program is structured with three different types of research tracks:
Agents, which focuses on agent-based programming and the logical structure and function of agents;
Cognitive modeling, which focuses on modeling behavior in order to understand intelligence, cognition, neurology, etc.;
Linguistics and logic, which focuses on the role of reasoning and language in intelligence and communication.
One might think that the agents track would be the most fruitful in terms of AI careers and applications, but also the most difficult for individuals without a programming background. I decided to go with cognitive modeling, since that is most relevant to my previous education, but I also took (and am taking) the agents-track courses in addition. I was surprised to find that there was actually more programming (using R) in my cognitive modeling coursework than in my agents coursework, which instead consisted entirely of logics and the history thereof. For the first part of last block, the agents course was actually incredibly boring, but the latter half began to get a little more interesting, and in the end I feel like I learned a fair deal...but still have little clue how to go about programming an agent.
Thus, we're still in limbo. I would like to learn more about programming, data, and agent systems, but I'm not sure how I'll accomplish that with enough competence to be employable in those areas by the time I graduate.
Won't stop me from trying, though.
I'm interested in and plan to tackle areas of experimental research in psychology or neurology, gaming and game creation, and other somewhat open areas like ethics in AI or emotional systems. It's not exactly the most concise list of potential paths, but I think there're opportunities still open that'll make themselves clearer with time. I would love to do things that would synthesis tech with altruism, like games or AR for improving mental health or even therapy options, or working to create ethical policies for use of AI. I would also like to do research, but I'm a bit wary of that path--I feel strongly that research should be beneficial and not just blindly consumeristic, and I feel at times that research done purely in academic settings can be a little blind to the strides and needs of the non-academic world. But, I would not be at all opposed to embracing good opportunities in those areas.
This block, I'm taking a class in experimentation in psychology and linguistics (with a focus on ways to collect and handle data through channels like Ibex Farm and R), and a class on multi-agent systems, which I suspect will also be more theoretical than technical, but hopefully still informative. I am also auditing a class on coursera for programming with python, mostly as a refresher--by the end of the year (or maybe even by the end of the summer), I'd like to be proficient enough to handle the language creatively. If all goes well, python and R will both have a place in my skillset and resume.
Time to keep discovering and working hard!
It's difficult to know where exactly I'm heading. There's a lot of opportunities, but it's a little hard to tell which will pay off the most. Our program is structured with three different types of research tracks:
Agents, which focuses on agent-based programming and the logical structure and function of agents;
Cognitive modeling, which focuses on modeling behavior in order to understand intelligence, cognition, neurology, etc.;
Linguistics and logic, which focuses on the role of reasoning and language in intelligence and communication.
One might think that the agents track would be the most fruitful in terms of AI careers and applications, but also the most difficult for individuals without a programming background. I decided to go with cognitive modeling, since that is most relevant to my previous education, but I also took (and am taking) the agents-track courses in addition. I was surprised to find that there was actually more programming (using R) in my cognitive modeling coursework than in my agents coursework, which instead consisted entirely of logics and the history thereof. For the first part of last block, the agents course was actually incredibly boring, but the latter half began to get a little more interesting, and in the end I feel like I learned a fair deal...but still have little clue how to go about programming an agent.
Thus, we're still in limbo. I would like to learn more about programming, data, and agent systems, but I'm not sure how I'll accomplish that with enough competence to be employable in those areas by the time I graduate.
Won't stop me from trying, though.
I'm interested in and plan to tackle areas of experimental research in psychology or neurology, gaming and game creation, and other somewhat open areas like ethics in AI or emotional systems. It's not exactly the most concise list of potential paths, but I think there're opportunities still open that'll make themselves clearer with time. I would love to do things that would synthesis tech with altruism, like games or AR for improving mental health or even therapy options, or working to create ethical policies for use of AI. I would also like to do research, but I'm a bit wary of that path--I feel strongly that research should be beneficial and not just blindly consumeristic, and I feel at times that research done purely in academic settings can be a little blind to the strides and needs of the non-academic world. But, I would not be at all opposed to embracing good opportunities in those areas.
This block, I'm taking a class in experimentation in psychology and linguistics (with a focus on ways to collect and handle data through channels like Ibex Farm and R), and a class on multi-agent systems, which I suspect will also be more theoretical than technical, but hopefully still informative. I am also auditing a class on coursera for programming with python, mostly as a refresher--by the end of the year (or maybe even by the end of the summer), I'd like to be proficient enough to handle the language creatively. If all goes well, python and R will both have a place in my skillset and resume.
Time to keep discovering and working hard!
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