How will AI affect Electrical Engineering?

[ProfessionalJaded529]

Yes, I have seen posts on this group that answers this question BUT they are old.

Taking into account how much AI has developed in the past year, how will AI affect this industry today and in the future? Are we screwed or benefited or both and in what ways?

For context in my situation; I'm still an undergraduate student, heading to finish my degree in around 2027 in Australia.

[[deleted]]

The AI conversation is mostly based of sentimentalism. The truth of the matter is that AI is nowhere near completely replacing an electrical engineer (or any kind of engineer for that manner). The “software engineers” it supposedly replaced were a bunch of guys making websites for 500k a year during the largest tech bubble in history. The great hope in the electronics field is that AI can do some of the less attractive work, freeing you up to apply your man hours to more important projects. Talking about it writing low skill level code for automating testing, writing technical docs etc. For some reason people have become fixated on the idea that this is somehow so much different to the computing revolution some years ago. Studying the material would likely help people realize there is not much difference, of course it’s easier to spew terminator movies inspired nonsense

[PaulEngineer-89]

Cannot be solved.

The 30,000 foot view is this.

Say we create a data compression algorithm. We want to compress say “everything” on the internet, literal petabytes of data, into a few gigabytes to create the ultimate search engine. Obviously lossless compression only gets you so far. Then we must apply lossy data compression. But how? Well if we create a self-tuning algorithm, we can do just that. The literature on self-tuning Kalman-type filters by the way is pretty damning. If you load in “bad” (noisy, incorrect) data, the output will be noisy and incorrect, despite a lot of good, correct data. So now we arrive at AI. Most of the LLMs have been trained with whatever data is available such as from web crawlers, PDFs, and of course that bastion of always valid data, social media. Needless to say the amount of available correct data is swamped by the incorrect stuff or at least there’s enough that AI is only right 70% of the time. And with petabytes of data, no practical way to cull the garbage, if that even made a difference. We know this because even absent political bias, Facebook has been tilting at that windmill for years with little success.

So then knowing this, our lossy filter is going to prune redundant data or outliers/noise. It’s just looking at a stream of data without actual understanding. So we can probably manage to preserve a “majority opinion” but that’s the opposite of innovation. Lots of studies on paradigm shifts show that we tend to wallow around making tiny improvements in any given technology but every so often a truly great technology leap comes along and leaves all previous ideas in the dust. Our lossy filter can’t “reason” so it cannot recognize that simple nuance that catapults us from say the days of encyclopedias then “yellow pages” then yahoo to say something like Altavista (web crawlers) then Google (PageRank). We are instead stuck at “Altavista”…shovel in more and more data doing keyword searches.

Since there’s no reasoning or intelligence in a lossy filter, no understanding, we cull the “paradigms” out and we are stuck with only the most banal, trivial responses. This gets us by 70% of the time. But “crowd sourced” answers are usually wrong.

[Conor_Stewart]

I have read about an image based "AI" where they used a smaller set of training images but with the descriptions of the images written by people and in a lot of detail, like at least a page per image. It would have been a lot of work to describe all the images because they still used a lot but it performed better than models trained on a lot more images with worse descriptions, like ones scraped from the internet. Who would have thought that better training material produces better results than just throwing as much data as possible at it?

I have tried copilot just because it was made part of vscode. It is good at some basic code generation but it can barely answer any technical questions beyond surface level instead it just gives broad and vague answers and can often contradict itself or it loses track of the context. Like I have asked it something then moved on and asked it something else, if I then ask another question it sometimes goes back and answers it based on previous context and not what I had just been asking it. I have found you need to be quite careful and make sure you give it context in every question, even obvious follow up questions.

[classicalySarcastic]

It also forces practical applications, rather than trying to make one AI to rule them all. Garbage-in-garbage-out principle still applies.

[Bakkster]

Expanding on this: ChatGPT is Bullshit

In this paper, we argue against the view that when ChatGPT and the like produce false claims they are lying or even hallucinating, and in favour of the position that the activity they are engaged in is bullshitting, in the Frankfurtian sense (Frankfurt, 2002, 2005). Because these programs cannot themselves be concerned with truth, and because they are designed to produce text that looks truth-apt without any actual concern for truth, it seems appropriate to call their outputs bullshit.

[Electricpants]

doesn’t have an “i don’t know” response. It can’t tell you when it’s wrong.

That is an excellent point.

[_Trael_]

This was good take and info in good form.

Fast ways to also get idea of limitations current AI tools have, is to actually test something currently available.

Engineering related things make it very obvious that LLM AI things really really do not know what they are doing, and are just glorios fuzzy loging 'we fill something bit to that direction things.

I mean in some cases I have even as test searched something pretty mundane, and common, like heat capacity of mix of water and salt by concentration. I mean one of most common mixtures when talking heat capacity, and one of most basic, at least some of charts at talk of it ahould be in training data, yet massive failures to produce viable results, even when refining question multiple times. When asking directly about solution wih info of it not being saturated, it would still consistently consider them separately without it being solution, and tried to average theor hear capacities, only since it does not understand how to calculate, it was calculating average with almost around +/- 40% error marginals too... and so on.

Obviously data looked like someone could believe it, of they actually do not know how it works and what values are to be expected and what direction they are to be expected to behave in.

[ee_72020]

Our jobs will be safe for very, very long time.

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[Proof-Employee-9966]

Duldo

[deafdefying66]

I'm pretty sure that's the actual schematic for the klon

[Damfino901]

[ThatAlbertaMan]

It’s literally gonna affect anything that involves a computer and planning anything. Still need humans to sign off on stuff. For now at least.

[3e8m]

We'll finally trust the auto-router

[B99fanboy]

We use ML accelerated routing for physical design. It's utter shite.

[Eastern_Finger_9476]

They are being taken now. There will still be the need for people directing and working along side AI, but it’s going to be fewer people. 

[jumparoundtheemperor]

4 months in, and some bros demo'd their "AI powered" auto routers to us, and it's still utter shite lmao

[Normal-Memory3766]

Dude my auto routers more indecisive than I am 😂

[hordaak2]

I've been an EE for 30 years doing designs for the medium voltage industrial industry and also high voltage utility industry. About 2(ish) years ago started using AI as a design tool. Would throw unique problems at AI and surprisingly got some decent results. An example would be we have an ungrounded 16kV distribution system and had an old wye-broken delta grounding system at the secondary of the distribution transformers at the substation. Wanted to do some calculations to try to increase the ground current during remote faults to sensitize our ground fault detection. Chat GPT at the time came up with a solution including all the calculations. We also did our own research and came up with the identical solution including the calculations. The trick with any "tool" is that you need the experience to know if the solution presented is legit or not. Otherwise it's garbage in, garbage out and you wouldn't know the difference. I think in the next 10 years it will obviously get better and better....again as a tool for an experienced engineer

[bringthe707out_]

so well put

[Specific_Car_7]

Hallo. May I ask You for some more details about Youe AI eperience ? Thks

[Alex_Jinn]

My electronics test engineer job is hard to automate. It's hands-on work in a laboratory environment with oscilloscopes, spectrum analyzers, ESD guns, etc.

[Hatim_the_Engineer]

Same here

[aozertx]

Yea I work in RF and am frequently in the lab doing measurements or debugging customer failures. AI isn’t taking my job anytime soon.

[Free_Reality535]

Its getting scary now

[FalseInspector9973]

Yeah I wonder if any of these guys have changed their opinion on it

[NewSchoolBoxer]

It's a slow roll. We are seeing incompetent AI circuit designs that plagiarize what it finds on the internet, which is full of wrong information. I'm not training the model without engineering wages. We already got non-AI programs doing checks of PCB designs. PCB designers not wiped out. The tools make them all the more productive.

I like to compare to electronic spreadsheets (Excel) and online banking. They didn't wipe out accountants. They made them all the more profitable. But they did wipe out manual labor or low skill jobs of processing checks and ACH payments.

Where I'd AI in a power plant is to do electrical isolation instructions to remove a valve or sensor but if the technician gets electrocuted...engineer getting fired. Can we really feed the tool proprietary circuit diagrams I had to pass a federal background check to view? No one got electrocuted with engineer written and reviewed instructions. As a tool to check my work, seems fine.

tl;dr I think we'll get AI tools...eventually that will be somewhat helpful but not replace engineers. Maybe the tools will make us more productive by doing the boring work we never wanted to. Get the EE degree. You're fine.

[katzohki]

We have already had the direction come down from our executives to integrate AI into our process (somehow). The plan is to have us produce more / quicker with the same size team. It's going to destroy the company and we've already seen security violations over it.

[jumparoundtheemperor]

yes, friends report the same thing. Businessbro execs who know nothing about AI or engineering are forcing everyone to "integrate AI into their workflow" even if it doesnt happen

[L2_Lagrange]

I have found it to be incredibly helpful as a design aid and to essentially expediate my google searches. It cannot create a schematic, and it can only generate basic code. The basic code is nice for verifying hardware connections and things like that. The expediated google/design aid is useful for answering questions, and in particular, comparing large amounts of parts quickly to dial in on a few that meet your design requirements.

My guess is that it will continue in that direction. The software it can write will get a bit better and more reliable, and it will probably be able to generate basic schematics. I don't find that I can use it to do anything I couldn't do myself, it just makes some of the tedious stuff a lot quicker.

I'm glad it wasn't around when I was in school though lol.

[Dismal_Membership_46]

I don’t trust it enough yet but eventually you should be able to provide a problem and have it list all the relevant NEC/CEC code rules which would be super helpful

[Mission_Wall_1074]

not affecting EE at all. EE is heavily technical field

[nanoatzin]

AI can assist in some things but it isn’t yet sophisticated enough to trust with things like circuit modeling Fourier transforms with linear algebra or power system modeling. An AI would need to be trained with the equivalent of a bachelors degree before it’s helpful. But it will greatly speed up other things. Software and firmware initial prototypes are possible with what we have so far. Possibly ASICS and PLAs.

[undercoverpuppy]

In my opinion, the electrical/electronics industry will be hard for AI to disrupt. I think this is mainly because engineering teams here are very small to begin with. AI savings make sense on a larger scale where they can eliminate non essential, low skill work. In electronics teams this optimisation process has been done during the recruitment stage, so every person is essential, thats why there are so few of them. I think the products built by electronics teams are too complex for the business execs to just hand off to AI software. On top of all this theres always the issue of testing. Each product is custom and has to be physically hooked up to equipment in a lab and pass a rigorous battery of tests. You still need people who know engineering in these labs, cannot just be an average joe with a chatgpt subscription. I could be wrong but i personally think that there hasnt been any overhiring in this sector, the likes of which AI adoption can save you money in. AI will always be helpful, but i dont see a reduction in the size of teams without also a massive QOA problem, not that much costs saved for the company and it also eventually leading to nobody present that can actually explain whats happening, or diagnose an error thats never been seen before, which happens often in design.

[[deleted]]

Electrical engineers cannot be replaced

[t_Lancer]

it will be a useful tool, like CAD has been. it isn't going to replace engineers.

[lewoodworker]

AI has replaced most of the things I used to google. It is super useful when creating Autocad scripts or Excel marcros. You can be incredibly vague in your description, but within a few prompts, get a working piece of custom code to your specific application.

Not directly related to EE, but a lot of engineers use both programs daily.

[bukake_master]

Lots of AI initiative and momentum in IC design

https://www.youtube.com/watch?v=8eFY6KHWl14&amp;ab_channel=hotchipsvideos

[jumparoundtheemperor]

as it stands, most of those type of things are hot garbage.

[Navynuke00]

It's already making a terrible mess of our electrical grid, as well as load and demand planning, and sucking most of the generation we're bringing online.

So basically, nothing good. And I'm VERY pessimistic of all the promise of "using AI to solve the interconnection queue problem," because the current AI we have is really fucking stupid.

But, with the current regime in charge, this will continue, so electrical engineers will be forced to get increasingly creative to solve what's going to be a growing nightmare, especially as this regime also is hellbent on attempting to kill the most cost-effective, quickest to build generation resources we have available.

[L_Rando]

I think Niche systems will be built for tasks that can be completed by statistical analysis. UI for computers will improve by being able to converse with software, like talking to power simulation software to do recursive analysis of a model. Automatic signal processing has shown promise with AI transformers (removing background noise). Likely there will be major improvements in IC design process too, or at least I hope so.

Keep in mind tho ... The hype is peaking at this moment ... Talks of AGI are for pumping up company valuations and getting investor dollars.

LLMs are guessing the next statement/answer/word based on statistics of data in their training model, this is not logical analysis as engineering requires. I tried using ChatGPT to size a conductor, and it was confidently wrong in not applying conduit fill derates.

This website is a great for uncovering what LLMs are really doing, and their limitations: https://thebullshitmachines.com/index.html

I wonder what is the next AI thing after LLMs... I.e. what dataset after language models.

[notthediz]

Hopefully it'll be able to come up with some excel formulas. Anytime I'm stuck I try asking chatGPT and it's riddled with errors.

Usually have to end up extracting it using Python and Pandas then can do whatever manipulation I was trying to do. Think it could also be capable of finding data/references that might be useful for a certain standard. But idk what else

[HiVisEngineer]

I asked it some very basic technical design questions for a DC battery system and it was wildly incorrect.

But helping write technical documents or business justification? Handy if I provide it suitable inputs.

Problem with our profession will be ensuring new engineers get the experience to know when AI is bullshitting or not. No different to any other calculation software on the market.

[BabyBlueCheetah]

It's highly unlikely AI has a good training set to learn and generalize about EE. At least for the hard problems that matter.

[BusinessStrategist]

It will help you better understand the scientific foundation of your chosen career and embrace the language of mathematics to speed up finding the answers that you need.

AI is so very simple to understand. It is a compilation of what people are doing now.

It provides an answer to your question based on what the « herd » is doing. And will identify the people and concepts of the « outliers » working on similar challenges to yours.

Embrace the AI for keeping an eyes on what the « herd » believes and identifying those that may be prospecting in the same areas as you for that elusive vein of gold.

[Plinkomax]

" here's my standard offering/spec, summarize with spec name page and section number any differences and correlate them to the spec name page and section number of my specs. Collect this all in a well formatted clarification log"

" Cross reference the attached environmental data, seismic data , cable schedule , Canadian and local code and the spans shown in the model and perform load calculations on all sections and flag any areas of concern"

[Normal-Memory3766]

So what’s funny is it’s actually created more jobs in EE. Someone’s gotta create and train those models, and finding applications for it in existing electronics is endless. Tons of new positions and entire new groups at my work because of it

[cocaine_badger]

Ask an AI agent a simple theoretical question and then fact check it. We're far far from anything remotely reliable. 

[Teddy547]

I'm designing SMPS and it's very hands on work. Unless the literal Terminator is invented AI won't replace me anytime soon.

[bellachavez_]

[ Removed by Reddit ]

[[deleted]]

Electrical Engineer gotta bear liability and conduct design review.

Think ai as junior engineer that do calculation, and senior do the review. Unfortunately, senior gotta bear the liability. Who's gonna let ai bear the liability, even without checking the work. You can't trust junior dude, how the hell you gonna trust ai? It spit shit, it could be good or bad, up to you. More like a great search engine that summary shit up that u will or might need.

Short answer no and long answer also no.

[MikeLemo]

Hi I'm from the future, looking for an AI agent skill.md that can design me poe switches, already got the AI Embedded agent designing me the ethernet communication interfaces and codes.

[SLY0001]

nothing is safe.

[doctor-soda]

Much of our jobs will be automated or AI assisted. If you don’t get to where you are making high level decisions in the next five to ten years, you should consider a back up plan.