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This is the bargaining phase of denial. I've observed this in artists and other AI communities, where they comfort themselves with "But every job will be automa

This is the bargaining phase of denial. I've observed this in artists and other AI communities, where they comfort themselves with "But every job will be automated" "UBI is coming~". Its just a way to avoid making the hard transition. People who don't understand the basic 'theory/math', won't even understand things like parameter count, or the tradeoff between intelligence and response-time/running costs, a very important consideration for any real project. From everything we've seen in AI thus far, it has become more complicated, not less. Prompt engineering has not gotten easier, with the explosion of use cases, it takes real skill and imagination to understand how to optimize prompts. Looking at stable diffusion, new techniques like controlnet are incredibly powerful but beyond the average person to use. LORAs make fine-tuning accessible, but also expected of any professional in the future. Every white collar company beyond a hundred people, in the future, will probably want their own fine tuned models/plugins/model grounding. Hiring people to deliver even 10% extra accuracy is worth it because AI's are so useful. People need to understand how they work under the hood.

greatpostman 4y ago
Maybe. I work in an NLP research division of big tech. I just watched ChatGPT obsolete five years of applied NLP systems. We took open problems we were working on and saw that ChatGPT solved them out of the box.
- anonylizard 4y ago
  Well, previously you were a 'researcher' working on 'open problems'. Now the problem has been solved, time to become an 'engineer' working on implementing/optimising the solutions. The usage of AI will spike 100x going forward, from a mere curiosity inside the company which only affects management decisions (Say sentiment analysis), to extremely intensive direct interactions with customers. This will drastically increase the need for reliability and tractability of the results. NLP researchers simply have to accept 50% of what they did is useless, and reorient around the other 50%, its the risk of researching in an open field.
- crop_rotation 4y ago
  Curious to know what product you worked on and how is the team dealing with the realization of ChatGPT and all. Have you thought of what to take up next?
crop_rotation 4y ago
> People who don't understand the basic 'theory/math', won't even understand things like parameter count, or the tradeoff between intelligence and response-time/running costs, a very important consideration for any real project. I am not sure anyone needs to know the parameter count if you are using GPT4 or similar powerful LLM. Most people also would never need to know "the tradeoff between intelligence and response-time/running costs". > People need to understand how they work under the hood. Most people don't understand how computers work, and yet derive immense value from them (Non engineers, even most programmers I have met have no clue how the computer works mostly)
gl-prod 4y ago
You know, people are playing with OpenAI's playground without knowing any fancy "theory/math" and are getting pretty good results. Besides, making your own AI is not easy. Unless you're a big shot company, you'll probably just use an API of an existing one.
- dimitrios1 4y ago
  With enough time, it will be democratized. Everything eventually does. It's the reality of living in the techno-information age. With enough time, enough of the information gets accumulated and used by enough of the masses. Used to be that only large established cabinetmaking shops could produce quality cabinets at scale, now any joe schmoe can rig up a CNC machine, buy a 600$ dewalt planer, and a few other budget tools and can do it in their garage. It used to be only hollywood studios could produce movies, scenery, and editing at professional levels, now film nerds with programming chops are creating Mandolorian like experiences with Unreal engine. It used to be only large recording studios could produce the latest beats and set trends in various music genres. Now nerds like Zedd (well not anymore but he started out that way) do it on their personal computers and do it better than most producers.

greatpostman 4y ago

Maybe. I work in an NLP research division of big tech. I just watched ChatGPT obsolete five years of applied NLP systems. We took open problems we were working on and saw that ChatGPT solved them out of the box.

anonylizard 4y ago
Well, previously you were a 'researcher' working on 'open problems'. Now the problem has been solved, time to become an 'engineer' working on implementing/optimising the solutions. The usage of AI will spike 100x going forward, from a mere curiosity inside the company which only affects management decisions (Say sentiment analysis), to extremely intensive direct interactions with customers. This will drastically increase the need for reliability and tractability of the results. NLP researchers simply have to accept 50% of what they did is useless, and reorient around the other 50%, its the risk of researching in an open field.
crop_rotation 4y ago
Curious to know what product you worked on and how is the team dealing with the realization of ChatGPT and all. Have you thought of what to take up next?

crop_rotation 4y ago

> People who don't understand the basic 'theory/math', won't even understand things like parameter count, or the tradeoff between intelligence and response-time/running costs, a very important consideration for any real project. I am not sure anyone needs to know the parameter count if you are using GPT4 or similar powerful LLM. Most people also would never need to know "the tradeoff between intelligence and response-time/running costs". > People need to understand how they work under the hood. Most people don't understand how computers work, and yet derive immense value from them (Non engineers, even most programmers I have met have no clue how the computer works mostly)

gl-prod 4y ago

You know, people are playing with OpenAI's playground without knowing any fancy "theory/math" and are getting pretty good results. Besides, making your own AI is not easy. Unless you're a big shot company, you'll probably just use an API of an existing one.

dimitrios1 4y ago
With enough time, it will be democratized. Everything eventually does. It's the reality of living in the techno-information age. With enough time, enough of the information gets accumulated and used by enough of the masses. Used to be that only large established cabinetmaking shops could produce quality cabinets at scale, now any joe schmoe can rig up a CNC machine, buy a 600$ dewalt planer, and a few other budget tools and can do it in their garage. It used to be only hollywood studios could produce movies, scenery, and editing at professional levels, now film nerds with programming chops are creating Mandolorian like experiences with Unreal engine. It used to be only large recording studios could produce the latest beats and set trends in various music genres. Now nerds like Zedd (well not anymore but he started out that way) do it on their personal computers and do it better than most producers.