Anonymous wrote:No one is getting on a plane designed by AI. No one is moving into a skyscraper designed by AI. No one is launching a rocket designed by AI. No one is buying a car created by AI. No one is relying on a power plant built by AI. And on and on. There is a nexus of creativity and technical ingenuity in engineering that cannot be replicated by AI. And if AI ever gets to the point where it displaces engineers, civilization will have already collapsed long ago.

People are overestimating where AI is presently. Look at what Google has been doing recently. Your searches are getting AI responses, which can be helpful for simple things. But it always misses nuance, context and complexity. AI is making us dumber by the minute. But engineering can't afford to be dumb.

Anonymous wrote:

Anonymous wrote:

Anonymous wrote:

Anonymous wrote:AI doesn't even understand physics. See this
https://www.thealgorithmicbridge.com/p/harvard-and-mit-study-ai-models-are

It gets the physics completely wrong but gets the orbits right -- but people did that too in the distant past before they figured out Newtonian mechanics (epicycles). AI (or at least the current version of deep networks) optimize for prediction and matching, not concept abstraction. I keep on top of this research for my work, and AI is too far away from this. The situation is far worse in biology.

And before someone jumps in to say that it's only a matter of time, hardly anyone (in academic research or at companies) is optimizing for this. AI firms have bet on AGI, but most of those designs are just beefed up transformers -- which are powerful but have serious limitations.

It's only a matter of time before someone decides you're too expensive and decides to focus the AI on your job. It doesn't need to understand the full physics—you have all types of computer programs that don't "understand" the physics but are fantastic tools for design work. AI will piece them together and make them more useful. And it learns. So what it doesn't get today, will be "understood" in 6-12 months.

Did you guys read the article? This is elementary mechanics -- if it fails miserably on this, I don't want it designing bridges (or ICs for that matter). The current computer programs that aid engineering, design etc. are all built with the underlying physics that embody decades of theory and modeling. AI can't even run a proper web query -- I am not that hopeful that it will abstract design specs into appropriate physics (or control theory or systems modeling) and "ask" the right questions of the "dumb" programs.

All the tall claims about AI weather modeling, physics inspired neural networks work well up to a point but fail miserably on edge and not-so-edge cases because of lack of abstraction. Most of the stuff at NeurIPS and other conferences is not quite there and it's not for lack of trying. The frameworks just aren't appropriate. AI/ML performance in biology is even more miserable. The designer proteins don't fold properly, don't express in cells etc etc. We are pretty far from the promised AI utopia.

If you can insert physics into CAD design, you can teach AI. And AI's capacity for learning is increasing extremely quickly. You're talking about current limitations—it's improved past those limitations already. You're cooked.

Anonymous wrote:No one is getting on a plane designed by AI. No one is moving into a skyscraper designed by AI. No one is launching a rocket designed by AI. No one is buying a car created by AI. No one is relying on a power plant built by AI. And on and on. There is a nexus of creativity and technical ingenuity in engineering that cannot be replicated by AI. And if AI ever gets to the point where it displaces engineers, civilization will have already collapsed long ago.

People are overestimating where AI is presently. Look at what Google has been doing recently. Your searches are getting AI responses, which can be helpful for simple things. But it always misses nuance, context and complexity. AI is making us dumber by the minute. But engineering can't afford to be dumb.

Anonymous wrote:

Anonymous wrote:

Anonymous wrote:AI doesn't even understand physics. See this
https://www.thealgorithmicbridge.com/p/harvard-and-mit-study-ai-models-are

It gets the physics completely wrong but gets the orbits right -- but people did that too in the distant past before they figured out Newtonian mechanics (epicycles). AI (or at least the current version of deep networks) optimize for prediction and matching, not concept abstraction. I keep on top of this research for my work, and AI is too far away from this. The situation is far worse in biology.

And before someone jumps in to say that it's only a matter of time, hardly anyone (in academic research or at companies) is optimizing for this. AI firms have bet on AGI, but most of those designs are just beefed up transformers -- which are powerful but have serious limitations.

give it 18 more months.

They say this every 18 months.

Anonymous wrote:

Anonymous wrote:

Anonymous wrote:I’m an engineer. AI can’t do what I do, i.e., creative thought.

Yeah, you can stay for the creative thought—for now—and it can do the rest. You might keep your job, but all the entry level people won't. Same with architecture, but even that is going to go when you can eventually tell an AI, design me a classic new england saltbox for this plot of land—it will visualize it and then do the schematics in a few seconds.

You’ve been reading too much science fiction. Where’s my flying car?

Anonymous wrote:

Anonymous wrote:AI doesn't even understand physics. See this
https://www.thealgorithmicbridge.com/p/harvard-and-mit-study-ai-models-are

It gets the physics completely wrong but gets the orbits right -- but people did that too in the distant past before they figured out Newtonian mechanics (epicycles). AI (or at least the current version of deep networks) optimize for prediction and matching, not concept abstraction. I keep on top of this research for my work, and AI is too far away from this. The situation is far worse in biology.

And before someone jumps in to say that it's only a matter of time, hardly anyone (in academic research or at companies) is optimizing for this. AI firms have bet on AGI, but most of those designs are just beefed up transformers -- which are powerful but have serious limitations.

give it 18 more months.

Anonymous wrote:

Anonymous wrote:

Anonymous wrote:AI doesn't even understand physics. See this
https://www.thealgorithmicbridge.com/p/harvard-and-mit-study-ai-models-are

It gets the physics completely wrong but gets the orbits right -- but people did that too in the distant past before they figured out Newtonian mechanics (epicycles). AI (or at least the current version of deep networks) optimize for prediction and matching, not concept abstraction. I keep on top of this research for my work, and AI is too far away from this. The situation is far worse in biology.

And before someone jumps in to say that it's only a matter of time, hardly anyone (in academic research or at companies) is optimizing for this. AI firms have bet on AGI, but most of those designs are just beefed up transformers -- which are powerful but have serious limitations.

It's only a matter of time before someone decides you're too expensive and decides to focus the AI on your job. It doesn't need to understand the full physics—you have all types of computer programs that don't "understand" the physics but are fantastic tools for design work. AI will piece them together and make them more useful. And it learns. So what it doesn't get today, will be "understood" in 6-12 months.

Did you guys read the article? This is elementary mechanics -- if it fails miserably on this, I don't want it designing bridges (or ICs for that matter). The current computer programs that aid engineering, design etc. are all built with the underlying physics that embody decades of theory and modeling. AI can't even run a proper web query -- I am not that hopeful that it will abstract design specs into appropriate physics (or control theory or systems modeling) and "ask" the right questions of the "dumb" programs.

All the tall claims about AI weather modeling, physics inspired neural networks work well up to a point but fail miserably on edge and not-so-edge cases because of lack of abstraction. Most of the stuff at NeurIPS and other conferences is not quite there and it's not for lack of trying. The frameworks just aren't appropriate. AI/ML performance in biology is even more miserable. The designer proteins don't fold properly, don't express in cells etc etc. We are pretty far from the promised AI utopia.

Anonymous wrote:I’m an engineer. AI can’t do what I do, i.e., creative thought.

Anonymous wrote:

Anonymous wrote:I’m an engineer. AI can’t do what I do, i.e., creative thought.

Yeah, you can stay for the creative thought—for now—and it can do the rest. You might keep your job, but all the entry level people won't. Same with architecture, but even that is going to go when you can eventually tell an AI, design me a classic new england saltbox for this plot of land—it will visualize it and then do the schematics in a few seconds.

Anonymous wrote:

Anonymous wrote:

Anonymous wrote:AI doesn't even understand physics. See this
https://www.thealgorithmicbridge.com/p/harvard-and-mit-study-ai-models-are

It gets the physics completely wrong but gets the orbits right -- but people did that too in the distant past before they figured out Newtonian mechanics (epicycles). AI (or at least the current version of deep networks) optimize for prediction and matching, not concept abstraction. I keep on top of this research for my work, and AI is too far away from this. The situation is far worse in biology.

And before someone jumps in to say that it's only a matter of time, hardly anyone (in academic research or at companies) is optimizing for this. AI firms have bet on AGI, but most of those designs are just beefed up transformers -- which are powerful but have serious limitations.

It's only a matter of time before someone decides you're too expensive and decides to focus the AI on your job. It doesn't need to understand the full physics—you have all types of computer programs that don't "understand" the physics but are fantastic tools for design work. AI will piece them together and make them more useful. And it learns. So what it doesn't get today, will be "understood" in 6-12 months.

Did you guys read the article? This is elementary mechanics -- if it fails miserably on this, I don't want it designing bridges (or ICs for that matter). The current computer programs that aid engineering, design etc. are all built with the underlying physics that embody decades of theory and modeling. AI can't even run a proper web query -- I am not that hopeful that it will abstract design specs into appropriate physics (or control theory or systems modeling) and "ask" the right questions of the "dumb" programs.

All the tall claims about AI weather modeling, physics inspired neural networks work well up to a point but fail miserably on edge and not-so-edge cases because of lack of abstraction. Most of the stuff at NeurIPS and other conferences is not quite there and it's not for lack of trying. The frameworks just aren't appropriate. AI/ML performance in biology is even more miserable. The designer proteins don't fold properly, don't express in cells etc etc. We are pretty far from the promised AI utopia.

Anonymous wrote:It will never replace engineering as long as regular people think it is just “engineering”. There are at least 15 different fields under that umbrella.

Anonymous wrote:

Anonymous wrote:AI doesn't even understand physics. See this
https://www.thealgorithmicbridge.com/p/harvard-and-mit-study-ai-models-are

It gets the physics completely wrong but gets the orbits right -- but people did that too in the distant past before they figured out Newtonian mechanics (epicycles). AI (or at least the current version of deep networks) optimize for prediction and matching, not concept abstraction. I keep on top of this research for my work, and AI is too far away from this. The situation is far worse in biology.

And before someone jumps in to say that it's only a matter of time, hardly anyone (in academic research or at companies) is optimizing for this. AI firms have bet on AGI, but most of those designs are just beefed up transformers -- which are powerful but have serious limitations.

It's only a matter of time before someone decides you're too expensive and decides to focus the AI on your job. It doesn't need to understand the full physics—you have all types of computer programs that don't "understand" the physics but are fantastic tools for design work. AI will piece them together and make them more useful. And it learns. So what it doesn't get today, will be "understood" in 6-12 months.

Anonymous wrote:AI will certainly replace some engineering work. But AI can't sign off on plans, someone has to take responsibility to review and approve etc etc. and if you don't have entry level engineers then you won't have mid level or senior engineers either.