5 ms·

My 25-year adventure in AI and ML

194 points by ibobev 2y ago

Evidlo 2y ago
I saw this guy recently left UTK, which is close to my hometown. He made a blog post which made me rethink going into academia after grad school.
- gbnwl 2y ago
  Which one and in which direction did you rethink? Your comment made me curious so I looked at his posts and he has a one about leaving academia because he wasn't happy in 2022, and a more recent one about rejoining it some months ago. https://austinhenley.com/blog/leavingacademia.html https://austinhenley.com/blog/leavingacademia.html https://austinhenley.com/blog/rejoiningacademia.html https://austinhenley.com/blog/rejoiningacademia.html
  - Evidlo 2y ago
    I didn't see the more recent post, so thanks for the link. I should say that I'm still in grad school (nearing the end), so the decision hasn't been made yet. The direction I'm thinking is away from academia. I love the academic environment, access to university resources and close proximity to lots of domain experts. However my experience as of late has been pretty isolating, as my group is almost fully remote despite nearly everyone living in the same town making motivation difficult some times. I also sometimes miss exercising my practical engineering skills, as my current work is entirely analytical/simulation. Overall its been less rewarding than I had hoped.
mtrovo 2y ago
> Although I was on an AI team, I often pushed back against applying AI unless we had a really compelling reason. What is the user problem we are trying to solve? Do we really need an LLM or could a few if statements suffice? Are we sure that natural language is the appropriate interface for this? This practical approach to AI feels refreshing in a field drowning in buzzwords. I’ve built tools where simple regression models outperformed neural networks, and convincing teams was an uphill battle. It's hard to not get pushback from teams for not going all-in on AI when it seems decisions and budgets are hype-driven.
- d_sem 2y ago
  This is a perfect lesson in why strong communication skills are important in engineering organizations. It's leaderships responsibility to learn from engineering what is technically feasible but its also engineering's responsibility to communicate well enough to convince their organization on the right path forward.
- spacecadet 2y ago
  For years I worked at a company doing manufacturing automation with a generative CAD component. People would constantly throw out, "use ML" "use AI", everything was just regressions and open cascade... and those people never understood that it worked just fine without buzzwords.
  - BOOSTERHIDROGEN 2y ago
    Could you offer more insight into how regression analysis and open cascade are utilized in manufacturing processes?
- cm2187 2y ago
  CV driven development!
- extr 2y ago
  I have pushed back in a similar way many times (wrt LLMs), the response I typically get is some combination of: - A custom/heuristic driven approach would perform better but will take much longer to build so would be lower ROI. - There is a strategic angle to using AI here (building competency). We aren't sure what new use cases will open up in the medium term and we need to be fluent with building AI products. - There is a perceptual/marketing angle to using AI here. We need to convince the market/investors we are on the bleeding edge (hype). 3 is widely mocked but is a completely rational allocation of resources when you need to compete in a market for funding.
  - _glass 2y ago
    Prolog is AI, so whenever I see such a problem, I use miniKanren, implementing Relational/Logic programming in a light-weight way. Bleeding edge AI it is.
random_noise 2y ago
[dead]
mlepath 2y ago
I have had a somewhat similar journey but 14 years instead of 25 and I always wonder how it would be different today. We were lucky enough to grow up with the industry and progressively learn more complexity. The kids out of school today are faced with decades worth of complexity on day one on the job.
- fallous 2y ago
  This is true for every field. Everyone has had to step into a field that was built upon the hard-won experience of others and had to get up to speed, and the easiest way to do so is to recognize that fact and take advantage of the wisdom of those who came before.
- mnky9800n 2y ago
  Physicists have centuries to catch up on just to get started. I think they will survive. The main issue today is more the saturation of useless information in my opinion. There’s little time for your own thoughts as too much time is spent sorting the thoughts others want you to think.
villeso 2y ago
[flagged]
vouaobrasil 2y ago
For a lot of people, AI is a fun journey where they create things that are amazing. And I agree, the results are quite amazing. But it's also a sad thing that the world works this way because scientists like this never think of the larger social consequences of their work. They are insulated and elevated to lofty social positions while their creations fundamentally alter the social fabric. AI is one of those things that is quite dangerous and the fact that large corporations attract people by glorifying their intellect is a recipe for disaster.
- dale_glass 2y ago
  I'm not sure what this means exactly, because AI is a wide field that covers so much and angers a great many people for many different reasons. But IMO it's pointless to hope for something else. AI at its core turns out to be pretty simple. No matter what the best intentioned scientist did, somebody else would think differently. For example, Stable Diffusion was originally released with a filter that refused to generate porn. There's your scientist thinking of social consequences. But does anyone even still remember that was a thing? Because I'm pretty sure every SD UI in existence at this point has it disabled by default.
  - vouaobrasil 2y ago
    > No matter what the best intentioned scientist did, somebody else would think differently. This is exactly an argument that supports technological determinism. We simply can't decide -- we have no ability for oversight to stop technology from evolving. That's precisely why I think AI is so dangerous.
    - dale_glass 2y ago
      IMO, the dangers of AI are mostly overrated. AI is just a new fancy way of generating pictures and text. It does those things better in some regards, but the danger is the same we already had.
      - vouaobrasil 2y ago
SteveSmith16384 2y ago
It makes such a refreshing change to have a web page not cluttered with adverts and popups. Just nice, clean, well-spaced-out text and simple organisation.

194 points by ibobev 2y ago

I saw this guy recently left UTK, which is close to my hometown. He made a blog post which made me rethink going into academia after grad school.

gbnwl 2y ago
Which one and in which direction did you rethink? Your comment made me curious so I looked at his posts and he has a one about leaving academia because he wasn't happy in 2022, and a more recent one about rejoining it some months ago. https://austinhenley.com/blog/leavingacademia.html https://austinhenley.com/blog/leavingacademia.html https://austinhenley.com/blog/rejoiningacademia.html https://austinhenley.com/blog/rejoiningacademia.html
- Evidlo 2y ago
  I didn't see the more recent post, so thanks for the link. I should say that I'm still in grad school (nearing the end), so the decision hasn't been made yet. The direction I'm thinking is away from academia. I love the academic environment, access to university resources and close proximity to lots of domain experts. However my experience as of late has been pretty isolating, as my group is almost fully remote despite nearly everyone living in the same town making motivation difficult some times. I also sometimes miss exercising my practical engineering skills, as my current work is entirely analytical/simulation. Overall its been less rewarding than I had hoped.

mtrovo 2y ago

> Although I was on an AI team, I often pushed back against applying AI unless we had a really compelling reason. What is the user problem we are trying to solve? Do we really need an LLM or could a few if statements suffice? Are we sure that natural language is the appropriate interface for this? This practical approach to AI feels refreshing in a field drowning in buzzwords. I’ve built tools where simple regression models outperformed neural networks, and convincing teams was an uphill battle. It's hard to not get pushback from teams for not going all-in on AI when it seems decisions and budgets are hype-driven.

d_sem 2y ago
This is a perfect lesson in why strong communication skills are important in engineering organizations. It's leaderships responsibility to learn from engineering what is technically feasible but its also engineering's responsibility to communicate well enough to convince their organization on the right path forward.
spacecadet 2y ago
For years I worked at a company doing manufacturing automation with a generative CAD component. People would constantly throw out, "use ML" "use AI", everything was just regressions and open cascade... and those people never understood that it worked just fine without buzzwords.
- BOOSTERHIDROGEN 2y ago
  Could you offer more insight into how regression analysis and open cascade are utilized in manufacturing processes?
cm2187 2y ago
CV driven development!
extr 2y ago
I have pushed back in a similar way many times (wrt LLMs), the response I typically get is some combination of: - A custom/heuristic driven approach would perform better but will take much longer to build so would be lower ROI. - There is a strategic angle to using AI here (building competency). We aren't sure what new use cases will open up in the medium term and we need to be fluent with building AI products. - There is a perceptual/marketing angle to using AI here. We need to convince the market/investors we are on the bleeding edge (hype). 3 is widely mocked but is a completely rational allocation of resources when you need to compete in a market for funding.
- _glass 2y ago
  Prolog is AI, so whenever I see such a problem, I use miniKanren, implementing Relational/Logic programming in a light-weight way. Bleeding edge AI it is.

random_noise 2y ago

[dead]

mlepath 2y ago

I have had a somewhat similar journey but 14 years instead of 25 and I always wonder how it would be different today. We were lucky enough to grow up with the industry and progressively learn more complexity. The kids out of school today are faced with decades worth of complexity on day one on the job.

fallous 2y ago
This is true for every field. Everyone has had to step into a field that was built upon the hard-won experience of others and had to get up to speed, and the easiest way to do so is to recognize that fact and take advantage of the wisdom of those who came before.
mnky9800n 2y ago
Physicists have centuries to catch up on just to get started. I think they will survive. The main issue today is more the saturation of useless information in my opinion. There’s little time for your own thoughts as too much time is spent sorting the thoughts others want you to think.

villeso 2y ago

[flagged]

vouaobrasil 2y ago

For a lot of people, AI is a fun journey where they create things that are amazing. And I agree, the results are quite amazing. But it's also a sad thing that the world works this way because scientists like this never think of the larger social consequences of their work. They are insulated and elevated to lofty social positions while their creations fundamentally alter the social fabric. AI is one of those things that is quite dangerous and the fact that large corporations attract people by glorifying their intellect is a recipe for disaster.

dale_glass 2y ago
I'm not sure what this means exactly, because AI is a wide field that covers so much and angers a great many people for many different reasons. But IMO it's pointless to hope for something else. AI at its core turns out to be pretty simple. No matter what the best intentioned scientist did, somebody else would think differently. For example, Stable Diffusion was originally released with a filter that refused to generate porn. There's your scientist thinking of social consequences. But does anyone even still remember that was a thing? Because I'm pretty sure every SD UI in existence at this point has it disabled by default.
- vouaobrasil 2y ago
  > No matter what the best intentioned scientist did, somebody else would think differently. This is exactly an argument that supports technological determinism. We simply can't decide -- we have no ability for oversight to stop technology from evolving. That's precisely why I think AI is so dangerous.
  - dale_glass 2y ago
    IMO, the dangers of AI are mostly overrated. AI is just a new fancy way of generating pictures and text. It does those things better in some regards, but the danger is the same we already had.
    - vouaobrasil 2y ago

SteveSmith16384 2y ago

It makes such a refreshing change to have a web page not cluttered with adverts and popups. Just nice, clean, well-spaced-out text and simple organisation.