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To me it sounds like an Accenture submarine. "Come and let us charge you for doing something you can do yourself". Maybe I'm just a cynical techie, but I don't

To me it sounds like an Accenture submarine. "Come and let us charge you for doing something you can do yourself". Maybe I'm just a cynical techie, but I don't think some guy who hasn't studied anything technical is going to provide any value in talking to the AI. Chances are you will do much better with domain knowledge, eg a dev asking it for code, or a lawyer asking it for legal precedents.

alephnerd 4y ago
Linguistics (if you did it right) and Cognitive Science is deeply "technical" in the sense that you'll be knee deep in Tree Structure, Lexiostatistics, and Probability Theory to create datasets, reproducible grammars, and encode meaning.
- lordnacho 4y ago
  Sure, but Phelps is a history grad.
  - alephnerd 4y ago
    True, but that's more an artifact of Accenture's hiring practices in the UK (concentrating on hiring from a handful of Russell Group Unis where Engineering doesn't have much of a reputation compared to humanities/social science. on a separate note, the only notable NLP/AI groups in the UK are at Cambridge, Oxford, Edinburgh, and Imperial College, and most of them filter into SWE). The equivalent roles in the US will end up hiring people with a background in Linguistics, Cognitive Science, or Library and Information Sciences. This is seen in Anthropic's job listing for example.
bilbo0s 4y ago
You're on to something here. I really believe that in the long run, it will be the tech oriented domain experts who are the valuable ones. That's really who we've found we need at nearly every implementation step of our AI strategy. You need to know what data to get in your target domain. How to interpret that data. Some method of scoring that data. And all that's just table stakes. It goes on and on. Someone with a tech background is just not going to know about stenosis calculations the way a cardiologist will. Or legal precedents like a lawyer does. Or compressive strength values like a civil engineer does. And so on and so forth. AI generalists are also enormously valuable, but only to the Google, Microsofts, and OpenAIs of the world. Among those competing to make generalist AIs, it will be winner take all I'm afraid. Majority of the jobs created for generalist AI guys will be at big tech cos. The vast majority of the jobs generated in AI outside of big tech, will rely heavily on specialized knowledge of the domain experts. I even think colleges might want to consider adjusting the educational curriculum so that some cs knowledge is taught more like writing class. It's just something professionals will need to be familiar with and know how to do in the future. But not all that valuable in and of itself unless you can be one of the top guys. Someone who only knows CS? no other specialized knowledge? And they don't have the math chops of the OpenAI guys? Sorry, but you're just not going to be all that valuable in the future. Salaries for those kinds of people will start a slow decline for sure.

alephnerd 4y ago

Linguistics (if you did it right) and Cognitive Science is deeply "technical" in the sense that you'll be knee deep in Tree Structure, Lexiostatistics, and Probability Theory to create datasets, reproducible grammars, and encode meaning.

lordnacho 4y ago
Sure, but Phelps is a history grad.
- alephnerd 4y ago
  True, but that's more an artifact of Accenture's hiring practices in the UK (concentrating on hiring from a handful of Russell Group Unis where Engineering doesn't have much of a reputation compared to humanities/social science. on a separate note, the only notable NLP/AI groups in the UK are at Cambridge, Oxford, Edinburgh, and Imperial College, and most of them filter into SWE). The equivalent roles in the US will end up hiring people with a background in Linguistics, Cognitive Science, or Library and Information Sciences. This is seen in Anthropic's job listing for example.

bilbo0s 4y ago

You're on to something here. I really believe that in the long run, it will be the tech oriented domain experts who are the valuable ones. That's really who we've found we need at nearly every implementation step of our AI strategy. You need to know what data to get in your target domain. How to interpret that data. Some method of scoring that data. And all that's just table stakes. It goes on and on. Someone with a tech background is just not going to know about stenosis calculations the way a cardiologist will. Or legal precedents like a lawyer does. Or compressive strength values like a civil engineer does. And so on and so forth. AI generalists are also enormously valuable, but only to the Google, Microsofts, and OpenAIs of the world. Among those competing to make generalist AIs, it will be winner take all I'm afraid. Majority of the jobs created for generalist AI guys will be at big tech cos. The vast majority of the jobs generated in AI outside of big tech, will rely heavily on specialized knowledge of the domain experts. I even think colleges might want to consider adjusting the educational curriculum so that some cs knowledge is taught more like writing class. It's just something professionals will need to be familiar with and know how to do in the future. But not all that valuable in and of itself unless you can be one of the top guys. Someone who only knows CS? no other specialized knowledge? And they don't have the math chops of the OpenAI guys? Sorry, but you're just not going to be all that valuable in the future. Salaries for those kinds of people will start a slow decline for sure.