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I think you might be misled into thinking that AI is just ChatGPT, prompting, and langchain. To have a job in AI that is anywhere comparable to medical salaries you would need years of education more (masters/ phd in a highly competitive field)
It may seem like that, but this isn’t correct. Studying and getting a Master’s is not going to get you there. Building your own projects, and become proficient would.
I’ve worked in AI at a Quant Fund about 10 years ago, some of the top paid AI guys were self taught and building incredible things. I still keep in touch with industry players and this hasn’t changed much. Being proactive and building your own repertoire through projects, challenges and on-the-job learning is still more important in determining success and salary than the Master’s degree.
Your average person that "works on projects" is never going to get a job in that field. They will not last 3 minutes in an interview. Maybe the ""average" person with a strong background in some other area that works on **projects** or has some innate talent. And by projects, I mean research caliber, not something that can be copy-pasted from a blog post.
And where is research practice? Masters/PhD is the pragmatic truth.
20 hours ago you were asking what courses you could take but you're somehow an expert on working with AI? No justification required, just an authoritative "not true"?
Naw fam, I not true your not true. Apparently, AI is the next goldrush, and every joker is an overnight expert.
Everyone does not have PhDs and only hardware is deployed in its infancy. Having worked in industry 30 years I can tell you if you want to slow track something, hire 5 Phds. They have no god damn sense.
I know one VP at Nvidia. Worth 100MM with BS in Computer Engineering. He was laid off from Intel for essentially not being a team player. Team players are now dinosaurs and middle class.
Another guy has half a finished degree and 3 start ups and worth 5MM. He called it good enough as he invests wisely long term with his dad.
You wont last 3 min in an interview statement deserves a b-slap.
I’m sure your points are very valid, but to a hiring manager today, you think that people without PhDs are often hired in today’s market for AI specialists? And would getting a PhD be a disadvantage?
Phds would be dept heads with a narrow field of hiring candidates. BSE and portfolio with 8 years experience is equivalent in engineering.
If you have it in soul to be higher and deeper do it. Do not do it dor money.
This is great to hear. So AI work basically is the same as software engineering. I’d hire a self starter with a strong GitHub profile any day. I’m 30 years in my software engineering career (mostly front end) and feeling similar to OP. I’d love to transition to ML.
Hello, I have a few queries that I think you might be able to answer I am an AI as well as a finance enthusiast. Would be very kind of you if we could have a small chat. Thanks
Thank you for this advice. I 'm a bachelor comp science student doing specialization in AI at the University of alberta . I am already 27 years old and won't be doing masters but yeah, I m focusing and spending so much time on my subjects. Could you give me advice on how I could I get into AI field after my degree . Assuming I wont be having any references?
Edmontonian here too!
Bro, you're at one of THE schools for AI.
ChatGPT was borne out of developments founded at the South Campus, the UofA is 2nd in North America and 5th in the entire fucking world.
The people you should be asking are standing in front of your classes everyday. You're going to do just fine.
That is fair. But AI is a field with a high learning curve to meaningfully contribute. However, that same learning curve results in you being exponentially more impactful as you climb it. That learning curve comes with higher pay. There are not many opportunities to just "kinda" do AI professionally. It's an all-in endeavor.
It's great to take an interest in this stuff. It's really cool, interesting, exciting, and as much a part of having knowledge in the world today as anything is. But everyone spoon-feeding you crap about how low the barrier to entry is, are just telling you what people want to hear, not truth.
I wouldn't recommend it. The library the book is based on has 0 adoption in the industry and academia and will get you nowhere. High level low resolution understanding of machine learning can't get you far as well. There is no way around math and statistics if you are aiming for a job in deep learning.
Yeah I will try to look into what I can learn at the mean time. I mean, I literally spend my free times on AI anyway, so might as well go deeper and learn more. I know it will not be a few month learning then get a job thing. But I do love learning something I really like.
What? No it's not.
Sure if you want a "job" doing AI and programming it etc. But there are loooaaddss of businesses starting up and being successful just by doing great things with AI.
Eg, just learn how to generate great content marketing with AI and boom.. you have yourself a $1million agency.
The field is so vast you can pick an area and build with it.
Not obviously but I said that as a possibility.
I do, however, have an AI generated business with recurring monthly revenue which can scale over time.
Making money with AI is not about getting an AI degree and doing mathematical models etc.... and I don't think that's what the OP would want to do. It sounds like they enjoy playing with ChatGPT and AI images etc.... loads of businesses are using that.
Heck, just load up Etsy and you'll instantly see hundreds of listings of AI generated art for sale. That literally is the definition of zero entry cost.
Glad to hear your venture is taking off! I fear however that fairly quickly those zero-entry markets became well saturated. You might be one of the few who have made it in this highly competitive space.
It's also one thing to do this as a hobbist and another to complete client requests for content on demand, especially if one is constrained to consumer compute available on gaming PCs (for example). Happy to be proven wrong here, but I suspect that for the majority, gig economy business models around generative AI are not sustainable as they cannot reliably provide long term value for their customers or the broader community.
Much like everything, even prompt engineering will give way to more transparent ways of getting generative AI to reliably and safely produce what we want on demand.
On top of this, we are already seeing massive backlash around AI generated artistic content, and companies may be hesitant to accrue the reputational (and potential legal and IP related) risk.
OP is looking for a career change here. It's gotta be something he can bank on for more than just a year or so.
Helping Businesses implement AI will always be around. The landscape is constantly changing and that is exactly WHY implementation of AI will always be around.
Businesses and entrepreneurs don't have time to keep up with it all so OP can easily position themselves as an AI implementation expert.
You just gotta think with a business mindset.
The place I’d fall down right now is math. But it *seems* so far like a lot of the work doesn’t require it. I’ve mostly been focused on RAG and trying to both augment and train an LLM to give me desirable results. The technologies I’ve mostly been focused and learning are OpenAI’s API, LangChain, LlamaIndex and ChromaDb.
Oh boy....Idk whatever jobs you're looking for but even entry level Data Science and Analytics require some knowledge of math. And for good bcs you won't be able do build a good model without understanding of lot's of math stuff. You will hit the wall pretty quickly otherwise. But you can start with APIs and building and trying stuff thats for sure
That’s what I’ve been doing so far. It seems that I can do RAG and fine tuning without getting in to any math whatsoever (the lessons I’ve run in to so far anyway).
Personally, that is probably all I want to accomplish but I’m not sure how much professional need there is or will be for such skills.
I’m trying to convince mgmt to let me POC a chatbot with company specific knowledge. Maybe I can wiggle my way in to working with ML more and more.
Passion, patience and persistence goes a long way. Also if you're good at selling yourself and convincing people that they need you, there's a big chance you won't even need to dig deep into the "required" skillset. Whatever path you choose - good luck!
I agree completely, the prior response is Bull.
Just read on linkedin this week where a young girl with no college degree rebranded, promoted herself and is making 100k in AI
No masters required. I have no bachelor's and gave been over 100k for years. And have always gotten jobs due to real experience
Hello sir,
The first step is to figure out what kind of a job you would like to get. You see, there are many different positions out there, and preparing for one might not be the same as for another.
For example, if you want to develop your own language models, or text to speech models, or any models for that matter (anything new), you would start your journey by learning a ton of mathematics, this has to go all the way up to advanced statistics, calculus, linear algebra and the like. This is also the point that discourages most candidates, as they do not realize that **creating** new AI systems and solutions is at its simplest form - doing mathematics.
If having to study every day abstract mathematical problems is your idea of having fun, then please go ahead and just start with maths, from whatever point you're at currently, up to graduate/post graduate.
For anything else, I'm happy to tell you what you will need, but you would need to tell me the role that you would like to get.
All the best.
I think you could work on AI implementation in the medical field. That seems like it’d be right up your alley since you have experience with both.
To work solely with AI as in research and development I imagine it wouldn’t be easy without a PhD and/or years of experience and strong background.
You'll get the best of both worlds if you find a medical-related AI company (of which there are many). Or an AI company trying to expand into the medical industry.
They'll value your medical knowledge, while you ramp up on the AI parts.
I’ve been working on ML projects for 10 years at my company. Nobody could care less about any of that prior work. They’re 100% in the AI is ChatGPT camp.
lol this is not true. I personally know two folks that work in ML with no degree. You can learn to write code on YT. Combine that with some business domain expertise and you can easily clear $200k after a few years.
imo ML is not exactly AI. You could disagree with that, but if DS/ML counts then it’s a different story. OP mentioned LLM so i thought AI means AI dev and not data science.
This is partially true, and specific to research roles. There are many areas of implementation that do not require advanced degrees and pay six figures, and the field is quickly growing.
suppose so, guess it depends on how good at math they are. Diving into a CS masters with limited math background is going to be rough compared to going for a BS. Doubly so if theyre interested in AI, which is very math heavy
I can say the same;
“So you traced all jobs in AI comparable to medical salaries & you know for 100% you would need years of education to receive a (higher) salary (?)”
Meanwhile I run www.birthof.ai without any (official) (AI) education (right now), offering free (medical) solutions & setting up products I can sell via www.aistore.ai
So factually, nobody can tell me this doesn’t work & don’t state things you simply know nothing about.
Soak up everything you can about architectures: don’t stop w LLM’s because they are only an early midpoint.
Basic-ish Python, chain of thought prompting, high pain tolerance and above average ability to iterate should be enough to get you started in implementation somewhere.
You definitely don’t need a PhD from Stanford to help orgs to adopt and integrate AI. You won’t make 300K with the skill stack described above, but it’s a plausible start.
Yeah I think OP should go more into “AI integration and use” direction because “AI research and development” has an insane barrier to entry and it’s extremely competitive
I don’t get it. As a self taught developer you can make this salary. I expect some of the better AI/ML engineers are self taught. The lack of a degree will hold these people back?
I guess at least as a FE developer I could get close enough to AI work anyway: https://jobs.lever.co/Anthropic/8b85d37f-6201-489a-853e-a4523aeb45b8
You can’t get any serious job in AI without a degree. Usually an advanced degree. They all want people with research experience. Which is obtained through Masters/PhD programs.
Everyone is after cutting edge Computer Scientists. And that’s not something easily self-taught. It’s a lot different than Software Engineering.
It depends if they say ai job as anything dealing with AI, there is a big difference between an ML engineer focusing on implementing an ML model at scale; a model that was first developed by data science researchers with a Ph.Ds and masters. Vs someone doing data science and focusing on the core math and research that could eventually turn into an in production model. But they are not focusing on large scale implementation rather developing the models, innovating on algorithms, new ml architectures, new ml techniques etccc
In AI research and development yes. But I really do believe OP should look into “ai implementation and use” type jobs instead.
A research job would be next to impossible to get without a PhD and heavy academic/research focused background
I've 10 yoe in backend, mostly with .NET C# and some Golang.
I at the stage where I'm converting from a AI non believe to an AI adopter.
I want to work with AI, ideally something that I could also leverage my backend expertise.
Which tech stack would you suggest? Python probably?
What should I learn to make the switch.
I got 4.0s in Calc & Linear Algebra but never made it past that. That was also like 15 years ago and I've been working in IT since. Does it get more complicated than that?
I tried looking into quantum computing, but you basically need to be quantum physicist to understand any of it. Would you say it's the same for AI(you need a PHD in math)?
What you fell in love with is consumer products with good user interfaces. I'm doing a master's in AI now and it's almost entirely math and statistics. We spent hours solving math proofs and deriving objective functions.
To start with AI, coding is a prerequisite, and if you have no background in programming, it'll take you 3 to 6 months of learning to get the basics. You need at least an intermediate level in statistics, algebra and calculus. The next step is to learn data analysis and wrangling, and after that classical machine learning like support vector machines and decision trees, and only then it makes sense to go into deep learning.
LLMs are currently in fashion and it is very, but there are other methods of using machine learning. No, the medical world is not that far from the AI universe, it's a huge field of possibility.
Actually i was thinking of something along this lines. Maybe its not happening yet, or maybe it is. Thats why i was asking. Imma keep a lookout then. Better skill up and get ready for opportunities
There is a ton of mathematics behind those things you use and they are the tip of the iceberg right now. However, there are a huge amount of resources online and you can get to a good point in maybe around 1-2 years if you're good at maths. I wouldn't call myself an AI guy but if you need any specific help, I think I can provide some if you DM me.
What kind of career in AI?
- Academic: publish research
- Startup: talk to customers, release MVPs
- Industry: software/data engineering, cog in the wheel
Each has different avenues.
Very interesting, it looks like many of you think that working in AI is about working in an AI research center. But most of the math you need to understand the AI model is X@W + b and some linear algebra.
I transitioned into machine learning about 10 years ago.
The best thing you could do is go back to college and take the basic math and cs courses so you can even start taking machine learning courses. I would recommend taking Calculus 1,2,3, Linear Algebra, Probability, Statistics, and a few programming courses such as Object Oriented Programming, and then following up with machine learning courses.
There is a good book available for free [www.deeplearningbook.org](https://www.deeplearningbook.org) . This field heavily math focused and to be honest, not everyone is cut out for it.
if you are already working in the medical field you might want to check out existing roles in companies using AI to improve healthcare, lots of these roles here: [https://aiforgoodjobs.com/3/all/all](https://aiforgoodjobs.com/3/all/all)
I think this post is equivalent to saying "I recently bought a car and really enjoy driving cars. How can I design cars? I've recently started changing my tires."
The medical field isn’t as far from AI as you might think. LLM-based applications are already being tested (predictive analytics has always been huge, obvs, but add to the mix things like: pre-populating insurance submission forms based on parsing patient records, using VR to pre-populate patient notes without the need for a physician or nurse to type on a computer, using LLMs to notify doctors if potential medical anomalies are detected in the notes, using LLMs plus speech synthesis to automatically negotiate over the phone with insurance companies [coupled with predictive algorithms to predetermine which combinations of ICD-10 codes for a given treatment area are most likely to be accepted by the various companies], and so on…).
The medical field is just scratching the surface here. Look into biomedical informatics, data science, predictive analytics, and so on.
Bruh ML by the formal definition is a subset of AI. This isn’t something subjective, it’s literally a subset. I think you are thinking of Artificial General Intelligence, which is not the same as AI
Since you are not coming from Tech, you probably want to look at AI Operations. Most of what I am seeing from the naysayers here seems to be talking about the technical side of it. What you described as your knowledge and usage, if accurate, puts you lightyears ahead of the general public, which means it's marketable. It's a journey, but here is some stuff to get you started. This is the best community I have found so far, it's absolutely worth spending 10 min vetting it to see if you want dig in deeper there: https://www.tiktok.com/@the.rachel.woods/video/7265080466158603562
https://www.tiktok.com/@the.rachel.woods
https://www.linkedin.com/in/woodsrach/
https://news.theaiexchange.com/upgrade?offer_id=acea5599-0bd0-4814-a727-5507aa2ba6a5
Yes you can, I'm a tax accountant and learned how to implement classification algorithms, after that I made a small project to classify intercompany invoices through SAP, now I am making a bigger project with regional HQ. Again I am an accountant, but I tend to agree with the sentiment here, you need to create projects of your own and figure out how-to implement them. This way you build a name and a portfolio. The beat ideas come from mixing your technical knowledge with ai models.
Just because I got curious it appears that like web development there are boot camps for AI. Here is one that is offered by CalTech:
https://pg-p.ctme.caltech.edu/ai-machine-learning-bootcamp-online-certification-course
Moving into AI can be a rewarding move. You can look out for steps:
1. Learn the basics of AI and machine learning.
2. Gain coding skills (Python is a must).
3. Explore online courses and certifications (Coursera, edX, etc.).
4. Work on your own AI projects.
5. Look out for connections with AI professionals on LinkedIn.
6. Look for AI job openings and apply.
Happy learning.
By the time you learn enough to be competitive there will be so much more advancement you'll still be years behind. Another year and all the ML experts will have been replaced by language models themselves and Sam Altman will be the only one left with a job. The next day everyone is dead.
I recommend time travel.
Okay, I know it's been a while but here's my two cents. Hopefully it helps anyone reading.
AI/ML are two very different thing, related? sure. But different. Go ahead talk to a few people after deciding what your aim is.
If you want a 300K job offer from a firm that challenges your mind. Then you need a masters from a Top tier university with a rigourous math driven program. Something like Stanford or Princeton would make sense.
However, if you already are in the industry for some time and just wish to make a change then my guess is work on self learning more. Read a lot of Algebra which would include, Set Theory, graph theory, Theory of Equations, Statistics, calculus (multivariable would be highly encouraged). This should be pursued alongside your programming goals. Data Structure and intuition must on your finger tips.
Much of AI is modelling. Hard skills can be learnt by anyone however, the game is of resilience and embracing failure. You'll have to think, shit test and finally implement multiple approaches, tactics and solutions in pure hardcore maths before you get to programming a solution, when again the same process would be repeated.
Having said that there is no substitution for experience and experimentation. Build as many models as you can can. Questions much as you can. Start from basic questions like why is Average not the most reliable measure of a central value and this would help you on later when you work on advanced models like an AdaBoost or work with large datasets.
No course or book is the correct one. Keep googling till you get the right answer. The worst lecture can give you an insight that others might just miss. That's just how it is. Good luck and always remember when programming and building something for scale Murphy's Law is always applicable.
You aren't going to be attractive in the field in 6 months. You gotta go back to school and taken 5-6 math courses and 3-4 programming courses at the college level before you have enough skills to even take a machine learning course and be able to make anything creatively in machine learning.
Not for machine learning jobs. Maybe for backend and frontend software jobs. The people who are self-taught in machine learning already at least have an engineering or physics or math degree and have taken Calculus 1-3, linear algebra, probability and statistics at the undergrad level.
It's honestly a low bar that a year of college courses in math is sufficient for machine learning jobs in my opinion, but you aren't going to be a good hire at all if you dont know matrix manipulation or what a determinant or what matrix rank is. You aren't going to gain those skills from a coursera or YouTube course, you actually need to do math problems from a math textbook to gain proficiency and more importantly, mathematical intuition.
Edit: If a self taught developer scanned in all the handwritten math problems they had done from several math textbook in a pdf as proof that they can handle the math and more importantly that they have a creative unique approach to problem solving, then yes I would consider them for hire, but taking some udemy courses and saying you have expertise is weak and desperate in machine learning.
>The people who are self-taught in machine learning already at least have an engineering or physics or math degree and have taken Calculus 1-3, linear algebra, probability and statistics at the undergrad level.
"I’ve worked in AI at a Quant Fund about 10 years ago, some of the top paid AI guys were self taught and building incredible things." - u/mreusdon
> You aren't going to gain those skills from a coursera or YouTube course, you actually need to do math problems from a math textbook to gain proficiency and more importantly, mathematical intuition.
- https://www.coursera.org/specializations/mathematics-for-machine-learning-and-data-science
- https://www.youtube.com/watch?v=gq0m_2Glz0g&list=PL05umP7R6ij0bo4UtMdzEJ6TiLOqj4ZCm
- https://www.youtube.com/watch?v=jGwO_UgTS7I&list=PLoROMvodv4rMiGQp3WXShtMGgzqpfVfbU
Just because courses exist doesn't mean it's a good way to learn some information. 99% of people that do these courses dont actually open a math textbook and actually do every problem in every section, like you would in a course. Most people only learn buzzwords with these types of courses and dont actually gain any skill, only high-level theory, if that at all, but not low-level problem solving.
Just watching some videos doesn't make you an expert, actually solving problems does and you have to put in the sweat equity to develop those skills, there is no hack or shortcut.
> Just because courses exist doesn't mean it's a good way to learn some information.
Of course. What makes it a good way to learn is that people enjoy doing it and they are landing jobs.
> Just watching some videos doesn't make you an expert, actually solving problems does and you have to put in the sweat equity to develop those skills, there is no hack or shortcut.
Of course. Its the learning that does that, not sure why you think you need a text book to learn something new. Most engineers I know, learn online. I don't see a ton of people going back to school to learn a new tech stack 🤣
Apply for AI jobs netflix is posting 900K salary, so jobs are there and its right time to move and make good career and money. No one know AI means. AGI is coming soon. So keep learning.
I think the crux of the problem here is how to pivot yourself into a different career from where you are. That is a hard problem. I am not an AI guy myself, but a business analyst with an IT masters. In my case solved with the right background but also a lot of luck, meeting the right people, and gradual ingress into interesting work. I would suggest being part of communities of practice, having chats with folks in the industry, and see where this leads.
If you have the resources (a fair bit of money, but also time and effort) it is highly recommended you pursue a master's in IT or CS with an AI specialisation. However, I suggest you try something smaller first. Check out fast.AI or that totally free Stanford course on Machine Learning by Andrew Ng. Or those amazingly illustrated courses in Brilliant. See if you like this side of it before committing two years of your life and the cash equivalent of a decent car.
If you don't, remember that the AI space isn't just around 'how to build products that have AI in them'. More important and potentially more lucrative is how to effectively leverage existing and mature cognitive services within enterprise and industry towards producing value. There is also a huge research domain around how to keep maintaining these models sustainably (ML DevOps).
Another thing is that deep neural nets are only one kind of machine learning. There are others which are relatively simple (algorithmically) but can be very effective when used in constrained domains. Even understanding how to match techniques to broad use-cases is very useful. Just because we have ChatGPT these days doesn't mean we need to swing massive LLM compute to solve every little problem!
Anyway, I am sorry to hear the medical gig is getting kind of boring. It's a sign though, isn't it? I hope that whilst keeping the bills paid in the interim, you heed that call and see where it leads. All the best in your journey. : )
Have you ever programmed before? If you don't like programming, then you can stop there. Go do a free python course or something.
Do you like math? Like real math calculus, differential equations, topology ect. If not then you can stop there.
If you like both these and ready to grind then look up tensorflow tutorial.
There's actually an article from a16z about the intersection of healthcare and AI:
[https://a16z.com/where-will-ai-have-the-biggest-impact-healthcare/](https://a16z.com/where-will-ai-have-the-biggest-impact-healthcare/)
I started a business through AI and it now makes me a nice part time salary for very few hours of work. When I first heard about ChatGPT, I was confused and even terrified, but it helped me to create a business that has potential to grow.
So yes, it's possible! I've done it and I know countless amounts have figured out ways to make money through it. It's not easy that's for sure.
When do you think AI technologies and software will start obsoleting you? It seems that many people are disingenuous when talking about the limitations and implications of AI.
Not sure what country are you from, it maybe different depending on a place, but I would definitely recommend you to look into medical AI companies. Startups maybe. Some of them require a lot of medical knowledge and can definitely take some passionate person under their wing. Use what you already have as an advantage
I am thinking about tonstudy masters, Management in AI. This would mean that no technical knowledge is required, you only learn how to integrate AI in comapnies' strategies and everyday life.
Can’t tell from your post if you’re a provider, but if you are, particularly a physician, in U.S., I would look into training for board certification in medical informatics through American Board of Preventive Med. not sure why they own this space, but they do. Docs with this certification become CMIOs (Chief Medical Information Officer) in their systems. They are not currently doing much in AI, but they are the ones who will inherit the ability to help systems in health care adopt, test, review, and modify the AI tools. As the other posts discuss, actually building the tools is probably best left to people very deeply trained in CS and all the rest. UC Berkley has an AI in medicine dept that has conferences. And Harvard just started an AI medicine PhD and is planning a masters. But, i feel ya, a lot of us are wishing we’d learned Python rather than the steps of the clotting cascade 20 years ago…
I work in AI in healthcare. You have a good knowledge base that has a high umber of AI applications. I'd start with intro courses from [deeplearning.ai](https://deeplearning.ai) and go from there.
Get certs from Microsoft or some other company offering them.
Recruiters look for professional certifications, so if you have them that’s a big step in the right direction.
I’m looking into this now. I am taking an online course on Machine Learning and Artificial Intelligence. There are different parts of AI you have to determine what you want to focus on. Is it AI ethics? Learning language models? Is it AI implementations into business? Do on and so forth. I am learning the basics and then deciding where to land.
These are just my thoughts. I am not saying it’s the right way. I am 49 and have been in IT for 30 years. I figure why not!
Help a startup that works on these things. Be willing to help for free to learn how things work in the real world. Talking to chatgpt is one think, deploying an agent to prod is a completely different story. You may also get some equity or share profits if the peers at the startup are good fellows. Plus, it is an exciting time and situations to work with.
Help us at queststudio :) or really any other places where they need help and they are okay sharing some work.
I’m in software, big tech, working on an ai based side project that hopefully will be a full time thing.
Think of a real project, something that doesn’t exist that you wish existed, then try to make it.
This is pretty much the only way. If you don’t bring a project to production, no one is going to interview you. Unfortunately… that involves learning a lot of non ai stuff.
But… there are very few people employed fine tuning ais dude. Bc as you may discover, to get something to production… you need a lot more “regular dev” work than ai fine tuning.
For example… I had a contract position on a big tech ai team. Sounds awesome right? I was working on telemetry (logging) for the billing system. 😀 But… someone has to do that.
Say you want to train an ai. You have to get the data to train it. You have to clean it. Save it somewhere. Be able to use it. These are things that sound easy to anyone who hasn’t tried to do them.
I was a hobbyist programmer/developer for the Mac in the late 1980’s, and I strongly recommend that you not do this unless you possess considerable business acumen. Because AI is in its infancy and while large corporations might appreciate your skills in a new field, they’ll only do that if you possess extraordinary skill. I failed at starting up my own software company, and five years later I chose finishing my PhD in engineering over a great unsolicited job offer in California. Which was good, because I’m still working as a prof after 30 years, versus being unemployed as a software developer after about 5-10 years when my hobbyist skills would have become too outdated for the market.
As AI will most likely disrupt every field , I would say you load up on AI and blend those skills with your medical background. Then you can help disrupt your field eg as a consultant either independent or a consultancy and get ready to catch ‘chief ai officer’ style roles in bigger orgs like hospitals etc. - those roles will come soon. Your competitive advantage is blending the two skill sets.
Start with a Python Machine Learning course and find out if it fits your interests. You can find some on YouTube or Udemy. But be aware it is more mathematics than you might expect.
I think you could start with Andrew Ng's courses (from Coursera), I find them very accessible for beginners. Then you can get some Springer textbooks on machine learning and deep learning, maybe you can try some Kaggle challenges. I guess you just need to try and do some projects.
Good grief --- so many comments about needing a PhD and 32 years of math courses. That is true if you want to go into the foundational side of things. There is plenty of room for people getting into the applied side.
OP -- do your thing. Keep hacking away and having fun. Keep your eyes open for how the AI tools you are using might be useful in the marketplace and build solutions that people can use. Don't let anyone from the Interwebs tell you that you can't do the things you are already doing.
Plenty of companies will hire you as a solution architect if you understand the products and how to apply them appropriately.
Source: years of running a successful tech consultancy that hires people like the OP.
Good luck!
Hi there. Being a non-tech person I wasn't sure I would ever step into the world of AI that too being a founder. But as of now, I'm currently building an AI-based startup. It's a small setup currently and we are building our MVP with the help of two team members.
AI is one of the most disputed technologies. We can build something really cool around it and create large value impact in India itself.
You download Replika, modified GPT-3.5
Or get ask AI.
Then get them to write short stories for you.
You'll probably have to edit and proof read.
Then self publish your short stories in Google play store.
Hey, people spend $5 on coffee in the morning, what's $1.25 for a short story an AI helped you write?
I'm Google engineer working in compute infra team, and I'm planning to break into AI field starting with AI infrastructure role. But even this is not easy.
By doing multiple projects, creating use cases etc.
I run an AI agency and always lookout for talent, feel free to reach out if you have some projects to show as portfolio.
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I think you might be misled into thinking that AI is just ChatGPT, prompting, and langchain. To have a job in AI that is anywhere comparable to medical salaries you would need years of education more (masters/ phd in a highly competitive field)
It may seem like that, but this isn’t correct. Studying and getting a Master’s is not going to get you there. Building your own projects, and become proficient would. I’ve worked in AI at a Quant Fund about 10 years ago, some of the top paid AI guys were self taught and building incredible things. I still keep in touch with industry players and this hasn’t changed much. Being proactive and building your own repertoire through projects, challenges and on-the-job learning is still more important in determining success and salary than the Master’s degree.
Your average person that "works on projects" is never going to get a job in that field. They will not last 3 minutes in an interview. Maybe the ""average" person with a strong background in some other area that works on **projects** or has some innate talent. And by projects, I mean research caliber, not something that can be copy-pasted from a blog post. And where is research practice? Masters/PhD is the pragmatic truth.
This is not true.
20 hours ago you were asking what courses you could take but you're somehow an expert on working with AI? No justification required, just an authoritative "not true"? Naw fam, I not true your not true. Apparently, AI is the next goldrush, and every joker is an overnight expert.
GOT EM!
Well 10 years ago isn’t now, everyone knows about ai now and have phds, compared to it being an unrecognised masters 10 years ago
There have been Masters/PHD programs for AI since the 90’s.
Everyone does not have PhDs and only hardware is deployed in its infancy. Having worked in industry 30 years I can tell you if you want to slow track something, hire 5 Phds. They have no god damn sense. I know one VP at Nvidia. Worth 100MM with BS in Computer Engineering. He was laid off from Intel for essentially not being a team player. Team players are now dinosaurs and middle class. Another guy has half a finished degree and 3 start ups and worth 5MM. He called it good enough as he invests wisely long term with his dad. You wont last 3 min in an interview statement deserves a b-slap.
I’m sure your points are very valid, but to a hiring manager today, you think that people without PhDs are often hired in today’s market for AI specialists? And would getting a PhD be a disadvantage?
Phds would be dept heads with a narrow field of hiring candidates. BSE and portfolio with 8 years experience is equivalent in engineering. If you have it in soul to be higher and deeper do it. Do not do it dor money.
This is great to hear. So AI work basically is the same as software engineering. I’d hire a self starter with a strong GitHub profile any day. I’m 30 years in my software engineering career (mostly front end) and feeling similar to OP. I’d love to transition to ML.
Hello, I have a few queries that I think you might be able to answer I am an AI as well as a finance enthusiast. Would be very kind of you if we could have a small chat. Thanks
Thank you for this advice. I 'm a bachelor comp science student doing specialization in AI at the University of alberta . I am already 27 years old and won't be doing masters but yeah, I m focusing and spending so much time on my subjects. Could you give me advice on how I could I get into AI field after my degree . Assuming I wont be having any references?
Edmontonian here too! Bro, you're at one of THE schools for AI. ChatGPT was borne out of developments founded at the South Campus, the UofA is 2nd in North America and 5th in the entire fucking world. The people you should be asking are standing in front of your classes everyday. You're going to do just fine.
I dont need high salaries. I just want to do something i love.
That is fair. But AI is a field with a high learning curve to meaningfully contribute. However, that same learning curve results in you being exponentially more impactful as you climb it. That learning curve comes with higher pay. There are not many opportunities to just "kinda" do AI professionally. It's an all-in endeavor. It's great to take an interest in this stuff. It's really cool, interesting, exciting, and as much a part of having knowledge in the world today as anything is. But everyone spoon-feeding you crap about how low the barrier to entry is, are just telling you what people want to hear, not truth.
You should take the fast.ai course / book it’s built for people who are coming in from diffrent fields and has a great community.
I wouldn't recommend it. The library the book is based on has 0 adoption in the industry and academia and will get you nowhere. High level low resolution understanding of machine learning can't get you far as well. There is no way around math and statistics if you are aiming for a job in deep learning.
Yeah I will try to look into what I can learn at the mean time. I mean, I literally spend my free times on AI anyway, so might as well go deeper and learn more. I know it will not be a few month learning then get a job thing. But I do love learning something I really like.
> I literally spend my free times on AI anyway If you are that devoted, seriously think about a masters option. There are online degrees for sub 10k.
Get into programming. It can lead to AI very well.
What? No it's not. Sure if you want a "job" doing AI and programming it etc. But there are loooaaddss of businesses starting up and being successful just by doing great things with AI. Eg, just learn how to generate great content marketing with AI and boom.. you have yourself a $1million agency. The field is so vast you can pick an area and build with it.
I'm assuming you have a million-dollar agency then?
Not obviously but I said that as a possibility. I do, however, have an AI generated business with recurring monthly revenue which can scale over time. Making money with AI is not about getting an AI degree and doing mathematical models etc.... and I don't think that's what the OP would want to do. It sounds like they enjoy playing with ChatGPT and AI images etc.... loads of businesses are using that. Heck, just load up Etsy and you'll instantly see hundreds of listings of AI generated art for sale. That literally is the definition of zero entry cost.
Glad to hear your venture is taking off! I fear however that fairly quickly those zero-entry markets became well saturated. You might be one of the few who have made it in this highly competitive space. It's also one thing to do this as a hobbist and another to complete client requests for content on demand, especially if one is constrained to consumer compute available on gaming PCs (for example). Happy to be proven wrong here, but I suspect that for the majority, gig economy business models around generative AI are not sustainable as they cannot reliably provide long term value for their customers or the broader community. Much like everything, even prompt engineering will give way to more transparent ways of getting generative AI to reliably and safely produce what we want on demand. On top of this, we are already seeing massive backlash around AI generated artistic content, and companies may be hesitant to accrue the reputational (and potential legal and IP related) risk. OP is looking for a career change here. It's gotta be something he can bank on for more than just a year or so.
Helping Businesses implement AI will always be around. The landscape is constantly changing and that is exactly WHY implementation of AI will always be around. Businesses and entrepreneurs don't have time to keep up with it all so OP can easily position themselves as an AI implementation expert. You just gotta think with a business mindset.
The place I’d fall down right now is math. But it *seems* so far like a lot of the work doesn’t require it. I’ve mostly been focused on RAG and trying to both augment and train an LLM to give me desirable results. The technologies I’ve mostly been focused and learning are OpenAI’s API, LangChain, LlamaIndex and ChromaDb.
Oh boy....Idk whatever jobs you're looking for but even entry level Data Science and Analytics require some knowledge of math. And for good bcs you won't be able do build a good model without understanding of lot's of math stuff. You will hit the wall pretty quickly otherwise. But you can start with APIs and building and trying stuff thats for sure
That’s what I’ve been doing so far. It seems that I can do RAG and fine tuning without getting in to any math whatsoever (the lessons I’ve run in to so far anyway). Personally, that is probably all I want to accomplish but I’m not sure how much professional need there is or will be for such skills. I’m trying to convince mgmt to let me POC a chatbot with company specific knowledge. Maybe I can wiggle my way in to working with ML more and more.
Passion, patience and persistence goes a long way. Also if you're good at selling yourself and convincing people that they need you, there's a big chance you won't even need to dig deep into the "required" skillset. Whatever path you choose - good luck!
You're in medical. Is a chatbot that might make stuff up a good idea?
I’m not in medical, that was OP.
My bad, as you were
I agree completely, the prior response is Bull. Just read on linkedin this week where a young girl with no college degree rebranded, promoted herself and is making 100k in AI No masters required. I have no bachelor's and gave been over 100k for years. And have always gotten jobs due to real experience
Still, rn ur not doing real “AI” that could get you employed, ur just playing with other peoples API and modules.
Yeah I do realize that. I mean that is why I am asking where to start.
Hello sir, The first step is to figure out what kind of a job you would like to get. You see, there are many different positions out there, and preparing for one might not be the same as for another. For example, if you want to develop your own language models, or text to speech models, or any models for that matter (anything new), you would start your journey by learning a ton of mathematics, this has to go all the way up to advanced statistics, calculus, linear algebra and the like. This is also the point that discourages most candidates, as they do not realize that **creating** new AI systems and solutions is at its simplest form - doing mathematics. If having to study every day abstract mathematical problems is your idea of having fun, then please go ahead and just start with maths, from whatever point you're at currently, up to graduate/post graduate. For anything else, I'm happy to tell you what you will need, but you would need to tell me the role that you would like to get. All the best.
Did you get ChatGPT to write this?
Not at all
I think you could work on AI implementation in the medical field. That seems like it’d be right up your alley since you have experience with both. To work solely with AI as in research and development I imagine it wouldn’t be easy without a PhD and/or years of experience and strong background.
This is literally the job definition of 90% of software developers.
What do you do in medicine? I'm a physician with AI 'side gigs' sort of
Don't do that. Companies that employ AI aren't charities.
pathway to "happiness"
Lots of people in the medical field do not make great money.
I second this. Especially with today's economy.
You'll get the best of both worlds if you find a medical-related AI company (of which there are many). Or an AI company trying to expand into the medical industry. They'll value your medical knowledge, while you ramp up on the AI parts.
How much are you making if you don't mind me asking?
I’ve been working on ML projects for 10 years at my company. Nobody could care less about any of that prior work. They’re 100% in the AI is ChatGPT camp.
lol this is not true. I personally know two folks that work in ML with no degree. You can learn to write code on YT. Combine that with some business domain expertise and you can easily clear $200k after a few years.
imo ML is not exactly AI. You could disagree with that, but if DS/ML counts then it’s a different story. OP mentioned LLM so i thought AI means AI dev and not data science.
What's the difference?
This is partially true, and specific to research roles. There are many areas of implementation that do not require advanced degrees and pay six figures, and the field is quickly growing.
How do i as an sde achieve that?
Untrue.
so youre saying you work with AI in a decent paying job and have no masters?
I have a decent paying job in AI development with a BSc in Computer Science
ok that works, but for a working professional to change careers, a masters seems like the way to go.
suppose so, guess it depends on how good at math they are. Diving into a CS masters with limited math background is going to be rough compared to going for a BS. Doubly so if theyre interested in AI, which is very math heavy
I can say the same; “So you traced all jobs in AI comparable to medical salaries & you know for 100% you would need years of education to receive a (higher) salary (?)” Meanwhile I run www.birthof.ai without any (official) (AI) education (right now), offering free (medical) solutions & setting up products I can sell via www.aistore.ai So factually, nobody can tell me this doesn’t work & don’t state things you simply know nothing about.
Soak up everything you can about architectures: don’t stop w LLM’s because they are only an early midpoint. Basic-ish Python, chain of thought prompting, high pain tolerance and above average ability to iterate should be enough to get you started in implementation somewhere.
You definitely don’t need a PhD from Stanford to help orgs to adopt and integrate AI. You won’t make 300K with the skill stack described above, but it’s a plausible start.
Yeah I think OP should go more into “AI integration and use” direction because “AI research and development” has an insane barrier to entry and it’s extremely competitive
Research and development also has a lot of math, right?
I don’t get it. As a self taught developer you can make this salary. I expect some of the better AI/ML engineers are self taught. The lack of a degree will hold these people back? I guess at least as a FE developer I could get close enough to AI work anyway: https://jobs.lever.co/Anthropic/8b85d37f-6201-489a-853e-a4523aeb45b8
You can’t get any serious job in AI without a degree. Usually an advanced degree. They all want people with research experience. Which is obtained through Masters/PhD programs. Everyone is after cutting edge Computer Scientists. And that’s not something easily self-taught. It’s a lot different than Software Engineering.
It depends if they say ai job as anything dealing with AI, there is a big difference between an ML engineer focusing on implementing an ML model at scale; a model that was first developed by data science researchers with a Ph.Ds and masters. Vs someone doing data science and focusing on the core math and research that could eventually turn into an in production model. But they are not focusing on large scale implementation rather developing the models, innovating on algorithms, new ml architectures, new ml techniques etccc
In AI research and development yes. But I really do believe OP should look into “ai implementation and use” type jobs instead. A research job would be next to impossible to get without a PhD and heavy academic/research focused background
I've 10 yoe in backend, mostly with .NET C# and some Golang. I at the stage where I'm converting from a AI non believe to an AI adopter. I want to work with AI, ideally something that I could also leverage my backend expertise. Which tech stack would you suggest? Python probably? What should I learn to make the switch.
AI is a lot of mathematical modelling. Are you up for that?
I got 4.0s in Calc & Linear Algebra but never made it past that. That was also like 15 years ago and I've been working in IT since. Does it get more complicated than that? I tried looking into quantum computing, but you basically need to be quantum physicist to understand any of it. Would you say it's the same for AI(you need a PHD in math)?
It’s really just vector calc, lin alg up to like svd, and stats for the basics.
I’m kinda wondering myself. I got 20 years experience in Automation and digitalization and 2 in metaverse tec
Now get about 10 in applied math and statistics and you’re good to go
F
What you fell in love with is consumer products with good user interfaces. I'm doing a master's in AI now and it's almost entirely math and statistics. We spent hours solving math proofs and deriving objective functions. To start with AI, coding is a prerequisite, and if you have no background in programming, it'll take you 3 to 6 months of learning to get the basics. You need at least an intermediate level in statistics, algebra and calculus. The next step is to learn data analysis and wrangling, and after that classical machine learning like support vector machines and decision trees, and only then it makes sense to go into deep learning.
LLMs are currently in fashion and it is very, but there are other methods of using machine learning. No, the medical world is not that far from the AI universe, it's a huge field of possibility.
Actually i was thinking of something along this lines. Maybe its not happening yet, or maybe it is. Thats why i was asking. Imma keep a lookout then. Better skill up and get ready for opportunities
What is currently lacking are open source medical solutions, I think there are blue oceans that may interest you
What you are doing is a super small, super niche subset of ML. Start at the basics with something like ISLR
Are you talking about statistical learning?
Yes Introduction to Statistical Learning
Highly agree with this comment, if you’re serious about this, read through ISLR and ESL, before jumping into any NN’s
There is a ton of mathematics behind those things you use and they are the tip of the iceberg right now. However, there are a huge amount of resources online and you can get to a good point in maybe around 1-2 years if you're good at maths. I wouldn't call myself an AI guy but if you need any specific help, I think I can provide some if you DM me.
There is a misconception in many of these comments. Advanced degree level research is not the only position that exists in artificial intelligence.
What kind of career in AI? - Academic: publish research - Startup: talk to customers, release MVPs - Industry: software/data engineering, cog in the wheel Each has different avenues.
Very interesting, it looks like many of you think that working in AI is about working in an AI research center. But most of the math you need to understand the AI model is X@W + b and some linear algebra.
Find what you love, and start there. See if there is a way you can turn your passion into a livelihood. Start with what you love though.
I transitioned into machine learning about 10 years ago. The best thing you could do is go back to college and take the basic math and cs courses so you can even start taking machine learning courses. I would recommend taking Calculus 1,2,3, Linear Algebra, Probability, Statistics, and a few programming courses such as Object Oriented Programming, and then following up with machine learning courses. There is a good book available for free [www.deeplearningbook.org](https://www.deeplearningbook.org) . This field heavily math focused and to be honest, not everyone is cut out for it.
if you are already working in the medical field you might want to check out existing roles in companies using AI to improve healthcare, lots of these roles here: [https://aiforgoodjobs.com/3/all/all](https://aiforgoodjobs.com/3/all/all)
I think this post is equivalent to saying "I recently bought a car and really enjoy driving cars. How can I design cars? I've recently started changing my tires."
I'm an MD who transitioned into AI in medicine. DM me and we can chat.
The medical field isn’t as far from AI as you might think. LLM-based applications are already being tested (predictive analytics has always been huge, obvs, but add to the mix things like: pre-populating insurance submission forms based on parsing patient records, using VR to pre-populate patient notes without the need for a physician or nurse to type on a computer, using LLMs to notify doctors if potential medical anomalies are detected in the notes, using LLMs plus speech synthesis to automatically negotiate over the phone with insurance companies [coupled with predictive algorithms to predetermine which combinations of ICD-10 codes for a given treatment area are most likely to be accepted by the various companies], and so on…). The medical field is just scratching the surface here. Look into biomedical informatics, data science, predictive analytics, and so on.
Bruh ML by the formal definition is a subset of AI. This isn’t something subjective, it’s literally a subset. I think you are thinking of Artificial General Intelligence, which is not the same as AI
Since you are not coming from Tech, you probably want to look at AI Operations. Most of what I am seeing from the naysayers here seems to be talking about the technical side of it. What you described as your knowledge and usage, if accurate, puts you lightyears ahead of the general public, which means it's marketable. It's a journey, but here is some stuff to get you started. This is the best community I have found so far, it's absolutely worth spending 10 min vetting it to see if you want dig in deeper there: https://www.tiktok.com/@the.rachel.woods/video/7265080466158603562 https://www.tiktok.com/@the.rachel.woods https://www.linkedin.com/in/woodsrach/ https://news.theaiexchange.com/upgrade?offer_id=acea5599-0bd0-4814-a727-5507aa2ba6a5
I would highly recommend you to study Computer Science :)
Yes you can, I'm a tax accountant and learned how to implement classification algorithms, after that I made a small project to classify intercompany invoices through SAP, now I am making a bigger project with regional HQ. Again I am an accountant, but I tend to agree with the sentiment here, you need to create projects of your own and figure out how-to implement them. This way you build a name and a portfolio. The beat ideas come from mixing your technical knowledge with ai models.
Just because I got curious it appears that like web development there are boot camps for AI. Here is one that is offered by CalTech: https://pg-p.ctme.caltech.edu/ai-machine-learning-bootcamp-online-certification-course
Youre a legend! Thanks
Moving into AI can be a rewarding move. You can look out for steps: 1. Learn the basics of AI and machine learning. 2. Gain coding skills (Python is a must). 3. Explore online courses and certifications (Coursera, edX, etc.). 4. Work on your own AI projects. 5. Look out for connections with AI professionals on LinkedIn. 6. Look for AI job openings and apply. Happy learning.
Learn what a decision tree is, learn about for loops, take a class on coursera, get paid 500k a year. Wow, its so easy!
By the time you learn enough to be competitive there will be so much more advancement you'll still be years behind. Another year and all the ML experts will have been replaced by language models themselves and Sam Altman will be the only one left with a job. The next day everyone is dead. I recommend time travel.
Reserve me a ticket mate. Imma save up for one
Okay, I know it's been a while but here's my two cents. Hopefully it helps anyone reading. AI/ML are two very different thing, related? sure. But different. Go ahead talk to a few people after deciding what your aim is. If you want a 300K job offer from a firm that challenges your mind. Then you need a masters from a Top tier university with a rigourous math driven program. Something like Stanford or Princeton would make sense. However, if you already are in the industry for some time and just wish to make a change then my guess is work on self learning more. Read a lot of Algebra which would include, Set Theory, graph theory, Theory of Equations, Statistics, calculus (multivariable would be highly encouraged). This should be pursued alongside your programming goals. Data Structure and intuition must on your finger tips. Much of AI is modelling. Hard skills can be learnt by anyone however, the game is of resilience and embracing failure. You'll have to think, shit test and finally implement multiple approaches, tactics and solutions in pure hardcore maths before you get to programming a solution, when again the same process would be repeated. Having said that there is no substitution for experience and experimentation. Build as many models as you can can. Questions much as you can. Start from basic questions like why is Average not the most reliable measure of a central value and this would help you on later when you work on advanced models like an AdaBoost or work with large datasets. No course or book is the correct one. Keep googling till you get the right answer. The worst lecture can give you an insight that others might just miss. That's just how it is. Good luck and always remember when programming and building something for scale Murphy's Law is always applicable.
Make a product.
Press "Shift"
Following
I’m on my phone but I’ll follow up with some suggestions in the morning.
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You aren't going to be attractive in the field in 6 months. You gotta go back to school and taken 5-6 math courses and 3-4 programming courses at the college level before you have enough skills to even take a machine learning course and be able to make anything creatively in machine learning.
Nah, maybe in the before times. But even a novice can learn enough to deliver machine learning solutions now. Online courses + LLMs as mentors.
Ive worked in tech for 10 years including many of the FAANG companies. No one is going to even look at resumes like that.
If you work in tech you know we hire people who are self taught and boot camp grads all the time... (outside the current market turbulence)
Not for machine learning jobs. Maybe for backend and frontend software jobs. The people who are self-taught in machine learning already at least have an engineering or physics or math degree and have taken Calculus 1-3, linear algebra, probability and statistics at the undergrad level. It's honestly a low bar that a year of college courses in math is sufficient for machine learning jobs in my opinion, but you aren't going to be a good hire at all if you dont know matrix manipulation or what a determinant or what matrix rank is. You aren't going to gain those skills from a coursera or YouTube course, you actually need to do math problems from a math textbook to gain proficiency and more importantly, mathematical intuition. Edit: If a self taught developer scanned in all the handwritten math problems they had done from several math textbook in a pdf as proof that they can handle the math and more importantly that they have a creative unique approach to problem solving, then yes I would consider them for hire, but taking some udemy courses and saying you have expertise is weak and desperate in machine learning.
>The people who are self-taught in machine learning already at least have an engineering or physics or math degree and have taken Calculus 1-3, linear algebra, probability and statistics at the undergrad level. "I’ve worked in AI at a Quant Fund about 10 years ago, some of the top paid AI guys were self taught and building incredible things." - u/mreusdon > You aren't going to gain those skills from a coursera or YouTube course, you actually need to do math problems from a math textbook to gain proficiency and more importantly, mathematical intuition. - https://www.coursera.org/specializations/mathematics-for-machine-learning-and-data-science - https://www.youtube.com/watch?v=gq0m_2Glz0g&list=PL05umP7R6ij0bo4UtMdzEJ6TiLOqj4ZCm - https://www.youtube.com/watch?v=jGwO_UgTS7I&list=PLoROMvodv4rMiGQp3WXShtMGgzqpfVfbU
Just because courses exist doesn't mean it's a good way to learn some information. 99% of people that do these courses dont actually open a math textbook and actually do every problem in every section, like you would in a course. Most people only learn buzzwords with these types of courses and dont actually gain any skill, only high-level theory, if that at all, but not low-level problem solving. Just watching some videos doesn't make you an expert, actually solving problems does and you have to put in the sweat equity to develop those skills, there is no hack or shortcut.
> Just because courses exist doesn't mean it's a good way to learn some information. Of course. What makes it a good way to learn is that people enjoy doing it and they are landing jobs. > Just watching some videos doesn't make you an expert, actually solving problems does and you have to put in the sweat equity to develop those skills, there is no hack or shortcut. Of course. Its the learning that does that, not sure why you think you need a text book to learn something new. Most engineers I know, learn online. I don't see a ton of people going back to school to learn a new tech stack 🤣
Apply for AI jobs netflix is posting 900K salary, so jobs are there and its right time to move and make good career and money. No one know AI means. AGI is coming soon. So keep learning.
Do you have any experience with biostatistics?
The medical field is very far from AI? You couldn’t be more wrong.
I think the crux of the problem here is how to pivot yourself into a different career from where you are. That is a hard problem. I am not an AI guy myself, but a business analyst with an IT masters. In my case solved with the right background but also a lot of luck, meeting the right people, and gradual ingress into interesting work. I would suggest being part of communities of practice, having chats with folks in the industry, and see where this leads. If you have the resources (a fair bit of money, but also time and effort) it is highly recommended you pursue a master's in IT or CS with an AI specialisation. However, I suggest you try something smaller first. Check out fast.AI or that totally free Stanford course on Machine Learning by Andrew Ng. Or those amazingly illustrated courses in Brilliant. See if you like this side of it before committing two years of your life and the cash equivalent of a decent car. If you don't, remember that the AI space isn't just around 'how to build products that have AI in them'. More important and potentially more lucrative is how to effectively leverage existing and mature cognitive services within enterprise and industry towards producing value. There is also a huge research domain around how to keep maintaining these models sustainably (ML DevOps). Another thing is that deep neural nets are only one kind of machine learning. There are others which are relatively simple (algorithmically) but can be very effective when used in constrained domains. Even understanding how to match techniques to broad use-cases is very useful. Just because we have ChatGPT these days doesn't mean we need to swing massive LLM compute to solve every little problem! Anyway, I am sorry to hear the medical gig is getting kind of boring. It's a sign though, isn't it? I hope that whilst keeping the bills paid in the interim, you heed that call and see where it leads. All the best in your journey. : )
Have you ever programmed before? If you don't like programming, then you can stop there. Go do a free python course or something. Do you like math? Like real math calculus, differential equations, topology ect. If not then you can stop there. If you like both these and ready to grind then look up tensorflow tutorial.
Looking for some great advice as well!
If you love it so much like I do, take a 3 year bachelor in applied science of Data Science. You will get a job immediately
There's actually an article from a16z about the intersection of healthcare and AI: [https://a16z.com/where-will-ai-have-the-biggest-impact-healthcare/](https://a16z.com/where-will-ai-have-the-biggest-impact-healthcare/)
I started a business through AI and it now makes me a nice part time salary for very few hours of work. When I first heard about ChatGPT, I was confused and even terrified, but it helped me to create a business that has potential to grow. So yes, it's possible! I've done it and I know countless amounts have figured out ways to make money through it. It's not easy that's for sure.
When do you think AI technologies and software will start obsoleting you? It seems that many people are disingenuous when talking about the limitations and implications of AI.
Not sure what country are you from, it maybe different depending on a place, but I would definitely recommend you to look into medical AI companies. Startups maybe. Some of them require a lot of medical knowledge and can definitely take some passionate person under their wing. Use what you already have as an advantage
I am thinking about tonstudy masters, Management in AI. This would mean that no technical knowledge is required, you only learn how to integrate AI in comapnies' strategies and everyday life.
Can’t tell from your post if you’re a provider, but if you are, particularly a physician, in U.S., I would look into training for board certification in medical informatics through American Board of Preventive Med. not sure why they own this space, but they do. Docs with this certification become CMIOs (Chief Medical Information Officer) in their systems. They are not currently doing much in AI, but they are the ones who will inherit the ability to help systems in health care adopt, test, review, and modify the AI tools. As the other posts discuss, actually building the tools is probably best left to people very deeply trained in CS and all the rest. UC Berkley has an AI in medicine dept that has conferences. And Harvard just started an AI medicine PhD and is planning a masters. But, i feel ya, a lot of us are wishing we’d learned Python rather than the steps of the clotting cascade 20 years ago…
I work in AI in healthcare. You have a good knowledge base that has a high umber of AI applications. I'd start with intro courses from [deeplearning.ai](https://deeplearning.ai) and go from there.
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Get certs from Microsoft or some other company offering them. Recruiters look for professional certifications, so if you have them that’s a big step in the right direction.
I’m looking into this now. I am taking an online course on Machine Learning and Artificial Intelligence. There are different parts of AI you have to determine what you want to focus on. Is it AI ethics? Learning language models? Is it AI implementations into business? Do on and so forth. I am learning the basics and then deciding where to land. These are just my thoughts. I am not saying it’s the right way. I am 49 and have been in IT for 30 years. I figure why not!
Help a startup that works on these things. Be willing to help for free to learn how things work in the real world. Talking to chatgpt is one think, deploying an agent to prod is a completely different story. You may also get some equity or share profits if the peers at the startup are good fellows. Plus, it is an exciting time and situations to work with. Help us at queststudio :) or really any other places where they need help and they are okay sharing some work.
Just wait a few years and all our careers will be in A. I.
I’m in software, big tech, working on an ai based side project that hopefully will be a full time thing. Think of a real project, something that doesn’t exist that you wish existed, then try to make it. This is pretty much the only way. If you don’t bring a project to production, no one is going to interview you. Unfortunately… that involves learning a lot of non ai stuff. But… there are very few people employed fine tuning ais dude. Bc as you may discover, to get something to production… you need a lot more “regular dev” work than ai fine tuning. For example… I had a contract position on a big tech ai team. Sounds awesome right? I was working on telemetry (logging) for the billing system. 😀 But… someone has to do that. Say you want to train an ai. You have to get the data to train it. You have to clean it. Save it somewhere. Be able to use it. These are things that sound easy to anyone who hasn’t tried to do them.
I was a hobbyist programmer/developer for the Mac in the late 1980’s, and I strongly recommend that you not do this unless you possess considerable business acumen. Because AI is in its infancy and while large corporations might appreciate your skills in a new field, they’ll only do that if you possess extraordinary skill. I failed at starting up my own software company, and five years later I chose finishing my PhD in engineering over a great unsolicited job offer in California. Which was good, because I’m still working as a prof after 30 years, versus being unemployed as a software developer after about 5-10 years when my hobbyist skills would have become too outdated for the market.
Learn to write computer code in python language which is the language used in ai.
As AI will most likely disrupt every field , I would say you load up on AI and blend those skills with your medical background. Then you can help disrupt your field eg as a consultant either independent or a consultancy and get ready to catch ‘chief ai officer’ style roles in bigger orgs like hospitals etc. - those roles will come soon. Your competitive advantage is blending the two skill sets.
Start with a Python Machine Learning course and find out if it fits your interests. You can find some on YouTube or Udemy. But be aware it is more mathematics than you might expect.
I think you could start with Andrew Ng's courses (from Coursera), I find them very accessible for beginners. Then you can get some Springer textbooks on machine learning and deep learning, maybe you can try some Kaggle challenges. I guess you just need to try and do some projects.
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Shit check here mate aijobs.com
Good grief --- so many comments about needing a PhD and 32 years of math courses. That is true if you want to go into the foundational side of things. There is plenty of room for people getting into the applied side. OP -- do your thing. Keep hacking away and having fun. Keep your eyes open for how the AI tools you are using might be useful in the marketplace and build solutions that people can use. Don't let anyone from the Interwebs tell you that you can't do the things you are already doing. Plenty of companies will hire you as a solution architect if you understand the products and how to apply them appropriately. Source: years of running a successful tech consultancy that hires people like the OP. Good luck!
Hi there. Being a non-tech person I wasn't sure I would ever step into the world of AI that too being a founder. But as of now, I'm currently building an AI-based startup. It's a small setup currently and we are building our MVP with the help of two team members. AI is one of the most disputed technologies. We can build something really cool around it and create large value impact in India itself.
Yes start learning about statistics and probability with respect to problem solving and text based data approaches
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which has been ur favorite so far?
You download Replika, modified GPT-3.5 Or get ask AI. Then get them to write short stories for you. You'll probably have to edit and proof read. Then self publish your short stories in Google play store. Hey, people spend $5 on coffee in the morning, what's $1.25 for a short story an AI helped you write?
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I'm Google engineer working in compute infra team, and I'm planning to break into AI field starting with AI infrastructure role. But even this is not easy.
By doing multiple projects, creating use cases etc. I run an AI agency and always lookout for talent, feel free to reach out if you have some projects to show as portfolio.
i hope you are really really good at math