6 answers
Qinglin
Student
Pittsburgh, Pennsylvania
4
Questions
Asked
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How would the release of GPT4.0 affect the job market in machine learning/natural language processing?
Given the latest advancements in GPT4.0, is the field of ML/NLP still a promising field to enter after graduation? How effects would those large language models have on the current jobs in the field ML/NLP?
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6 answers
Jared Chung
CareerVillage.org TeamExecutive Director at CareerVillage.org
284
Answers
Palo Alto, California
Updated
Jared’s Answer, CareerVillage.org Team
Hard to say right now, and things are moving fast, but my best guess at the moment is: "Yes."
Specifically: Although there is a huge market right now for companies to hire data scientists to build ML/NLP models from scratch, those same companies may or may not continue to use their own home-grown models in the future. If they shift some of their data science work from "homegrown" models over to using models that already come largely pre-trained (like the OpenAI models you're referring to). Predicting this trend in business is hard because the whole sector is moving so fast. However, I still think that my best guess is "Yes, getting training in ML/NLP is still probably marketable for a long time" if for no other reasons than: (1) there are likely to be a ton of ML use cases that "general" models like OpenAI's GPTs won't be able to do as well as custom-trained homegrown models for at least some number of years, and (2) having a deep understanding of how ML/NLP works seems to me like a skill that would only be more valuable in an AI-strong world, not less.
Stepping back for a moment though: I think it's fair to acknowledge that this is a highly uncertain time, and data science is a career area with additional uncertainty layered on top. You should take any predictions you get here (including mine) with a grain of salt, and continue to get new perspectives over time and keep an eye on the latest AI developments.
Source: I hire data scientists, employ engineers, and use both ML models and cloud-based AI services like GPT-4. But I'm not a professional ML / NLP researcher or educator.
Make a repeating calendar entry to read https://hckrnews.com/ at least once a week and read the latest articles announcing major AI / ML / NLP developments.
Specifically: Although there is a huge market right now for companies to hire data scientists to build ML/NLP models from scratch, those same companies may or may not continue to use their own home-grown models in the future. If they shift some of their data science work from "homegrown" models over to using models that already come largely pre-trained (like the OpenAI models you're referring to). Predicting this trend in business is hard because the whole sector is moving so fast. However, I still think that my best guess is "Yes, getting training in ML/NLP is still probably marketable for a long time" if for no other reasons than: (1) there are likely to be a ton of ML use cases that "general" models like OpenAI's GPTs won't be able to do as well as custom-trained homegrown models for at least some number of years, and (2) having a deep understanding of how ML/NLP works seems to me like a skill that would only be more valuable in an AI-strong world, not less.
Stepping back for a moment though: I think it's fair to acknowledge that this is a highly uncertain time, and data science is a career area with additional uncertainty layered on top. You should take any predictions you get here (including mine) with a grain of salt, and continue to get new perspectives over time and keep an eye on the latest AI developments.
Source: I hire data scientists, employ engineers, and use both ML models and cloud-based AI services like GPT-4. But I'm not a professional ML / NLP researcher or educator.
Jared, CareerVillage.org Team recommends the following next steps:
Hi Jared, thank you so much for the insightful reply! I think what you wrote makes a lot of sense, especially, despite all the latest advances in the field of ML/AI, it is beneficial to have a deep understanding of how those models work. Also, thank you for sharing the new resource, to-do item saved!
Qinglin
yoonji KIM
CareerVillage.org TeamDirector of Operations at CareerVillage.org
36
Answers
Los Angeles, California
Updated
yoonji’s Answer, CareerVillage.org Team
Hi Qinglin! Great question. I have little ML/NLP expertise but have been playing around with Chat-GPT3.5 for the last couple of months and now GPT-4. I thought I'd just ask your question to GPT-4. Here's what it said:
The release of GPT-4.0 would have several effects on the job market in machine learning (ML) and natural language processing (NLP). As with any technological advancement, there would be positive and negative implications. Here are some of the potential effects:
Increased demand for ML/NLP experts: The release of GPT-4.0 and other advanced ML models would likely increase the demand for skilled professionals in the field. Companies and organizations would be more inclined to adopt and utilize these models, requiring experts to deploy, maintain, and improve them.
Job transformation and specialization: As large language models become more sophisticated, there will likely be a shift in the types of jobs available in the field. For example, there may be an increased demand for experts who can fine-tune these models for specific applications, develop new algorithms to make them more efficient, or ensure that they are used ethically and responsibly.
Emergence of new job opportunities: The advancements in GPT-4.0 could lead to the creation of new industries and job opportunities. These might include developing novel applications for the technology, such as virtual assistants, content generation, or automated analysis of large volumes of text data.
Automation of certain tasks: Some jobs in the ML/NLP field might become automated or partially automated due to the advancements in GPT-4.0. For instance, certain aspects of data annotation or preprocessing might be performed more efficiently by the models themselves.
Need for interdisciplinary skills: As ML and NLP become increasingly integrated into various industries, professionals in the field might need to acquire additional skills and knowledge outside of their core area of expertise. This could include domain-specific knowledge, ethical considerations, or user experience design, for example.
Overall, the field of ML/NLP is still a promising one to enter after graduation, as the demand for expertise in these areas is likely to grow. However, it's essential to stay up-to-date with the latest advancements, adapt to new job opportunities, and develop a diverse skill set to remain competitive in the job market.
(I'm sure it's missing a thing or two. Curious what actual ML/NLP experts on CareerVillage think. I'm also curious about your thoughts if you're willing to drop a comment below here.)
Hop this helps!
The release of GPT-4.0 would have several effects on the job market in machine learning (ML) and natural language processing (NLP). As with any technological advancement, there would be positive and negative implications. Here are some of the potential effects:
Increased demand for ML/NLP experts: The release of GPT-4.0 and other advanced ML models would likely increase the demand for skilled professionals in the field. Companies and organizations would be more inclined to adopt and utilize these models, requiring experts to deploy, maintain, and improve them.
Job transformation and specialization: As large language models become more sophisticated, there will likely be a shift in the types of jobs available in the field. For example, there may be an increased demand for experts who can fine-tune these models for specific applications, develop new algorithms to make them more efficient, or ensure that they are used ethically and responsibly.
Emergence of new job opportunities: The advancements in GPT-4.0 could lead to the creation of new industries and job opportunities. These might include developing novel applications for the technology, such as virtual assistants, content generation, or automated analysis of large volumes of text data.
Automation of certain tasks: Some jobs in the ML/NLP field might become automated or partially automated due to the advancements in GPT-4.0. For instance, certain aspects of data annotation or preprocessing might be performed more efficiently by the models themselves.
Need for interdisciplinary skills: As ML and NLP become increasingly integrated into various industries, professionals in the field might need to acquire additional skills and knowledge outside of their core area of expertise. This could include domain-specific knowledge, ethical considerations, or user experience design, for example.
Overall, the field of ML/NLP is still a promising one to enter after graduation, as the demand for expertise in these areas is likely to grow. However, it's essential to stay up-to-date with the latest advancements, adapt to new job opportunities, and develop a diverse skill set to remain competitive in the job market.
(I'm sure it's missing a thing or two. Curious what actual ML/NLP experts on CareerVillage think. I'm also curious about your thoughts if you're willing to drop a comment below here.)
Hop this helps!
Hi Yoonji, thank you for the answer! It is a genius idea to ask ChatGPT to answer this question. I feel like one of the concerns for LLMs is the risk of hallucination: ChatGPT generates contents that are well formatted and reasoned, but in fact, was wrong. But I have very limited knowledge on ML so would like to hear what others think on this topic :D
Qinglin
Never heard the term "hallucination" in this context before! I learned something new today thanks to you, Qinglin!
yoonji KIM, Admin
Mustaq K M
13
Answers
Bengaluru, Karnataka, India
Updated
Mustaq’s Answer
The release of GPT-4.0, a more advanced version of the current state-of-the-art language model, is likely to have a significant impact on the job market in machine learning and natural language processing.
Firstly, the development of GPT-4.0 is likely to spur innovation and research in the field of natural language processing, leading to new breakthroughs and opportunities. This may lead to increased demand for skilled professionals in the areas of machine learning, data science, and natural language processing.
Secondly, with the release of GPT-4.0, there may be a shift towards using more advanced models in various industries, such as healthcare, finance, and marketing. This may require companies to hire more professionals with expertise in natural language processing to help integrate these models into their products and services.
Thirdly, the release of GPT-4.0 may also lead to increased competition in the job market, as more individuals may seek to acquire the skills needed to work with advanced language models. This may result in higher salaries and more opportunities for those with the necessary expertise.
Overall, the release of GPT-4.0 is likely to have a significant impact on the job market in machine learning and natural language processing, creating new opportunities and increasing demand for skilled professionals in these areas.
Thanks
Regards
Mustaq.K
Firstly, the development of GPT-4.0 is likely to spur innovation and research in the field of natural language processing, leading to new breakthroughs and opportunities. This may lead to increased demand for skilled professionals in the areas of machine learning, data science, and natural language processing.
Secondly, with the release of GPT-4.0, there may be a shift towards using more advanced models in various industries, such as healthcare, finance, and marketing. This may require companies to hire more professionals with expertise in natural language processing to help integrate these models into their products and services.
Thirdly, the release of GPT-4.0 may also lead to increased competition in the job market, as more individuals may seek to acquire the skills needed to work with advanced language models. This may result in higher salaries and more opportunities for those with the necessary expertise.
Overall, the release of GPT-4.0 is likely to have a significant impact on the job market in machine learning and natural language processing, creating new opportunities and increasing demand for skilled professionals in these areas.
Thanks
Regards
Mustaq.K
Thank you so much for the answer, Mustaq. : D
Qinglin
Peter Huang
Security consultant
79
Answers
Cupertino, California
Updated
Peter’s Answer
You're asking whether we can predict GPT-4.0 do to the job market in the area of ML/I. Unfortunately, I don't think we know enough to answer that. Does it affect nature language processing, I think it will since it likely will bridge the gap of understanding by providing different compositions/contexts, make it more understandable. However, for independent thinking and new modeling, I have not seen enough so far. Hope that help.
Thank you for the answer, Peter!
Qinglin
Hassan Al
Product Management Professional
376
Answers
Austin, Texas
Updated
Hassan’s Answer
Transformers like GPT4 will aid programmers as well as data scientists. It will help automate mundane tasks and speed up development. It will also allow novices to build simple models and become productive.
I expect that there will continue to be a strong need for AI/ML experts that can develop new and complex models. There should be plenty of jobs, but expect that there will be consolidation of many of the newer, smaller companies that have sprung up to get into the LLM market. So it maybe challenging to figure out if you're joining the next OpenAI or next Netscape.
I expect that there will continue to be a strong need for AI/ML experts that can develop new and complex models. There should be plenty of jobs, but expect that there will be consolidation of many of the newer, smaller companies that have sprung up to get into the LLM market. So it maybe challenging to figure out if you're joining the next OpenAI or next Netscape.
Ricardo Vivas
CareerVillage.org TeamWeb developer
2
Answers
Bogotá
Updated
Ricardo’s Answer, CareerVillage.org Team
As a complement to yoonji KIM's excellent answer, and focusing more on the AI/NLP engineering itself:
One of the biggest challenges the AI/NLP industry is facing is the re-reaching of "AI democracy"; as the control of state of the art, large language models is currently in the hands of big corporations. We all miss the days when state of the art NLP models were released on Huggingface and you were able to fine-tune them on your own GPU/affordable cloud machine.
Although important personalities in the area such as Andrew NG or talented research teams such as Eleuther AI have made efforts to democratize AI and switch the focus to smaller, more accessible applications; today's reality is that OpenAI is miles away of everyone else as they are the first corporation to have in their hands a powerful, properly censored large language model that can be sold as a product.
However, there is so much data in the internet, and so many GPUs in the world, and until a new industry-changing result (such as attention mechanisms were for current transformers) is discovered and presents a paradigm-shift in model architecture/training, we can expect smaller jumps in performance between large language model versions (such as the one between GPT3.5 and GPT4, which is definitely not as big as the one between GTP2 and GPT3 was).
Hopefully, in the meantime, collective/open-source efforts such as Cerebras-GPT will allow us mortals to train "homegrown" state of the art models again. This is crucial because models such as ChatGPT are highly fine-tuned (although more like highly lobotomized) to align with or avoid certain political/ethical opinions.
One of the biggest challenges the AI/NLP industry is facing is the re-reaching of "AI democracy"; as the control of state of the art, large language models is currently in the hands of big corporations. We all miss the days when state of the art NLP models were released on Huggingface and you were able to fine-tune them on your own GPU/affordable cloud machine.
Although important personalities in the area such as Andrew NG or talented research teams such as Eleuther AI have made efforts to democratize AI and switch the focus to smaller, more accessible applications; today's reality is that OpenAI is miles away of everyone else as they are the first corporation to have in their hands a powerful, properly censored large language model that can be sold as a product.
However, there is so much data in the internet, and so many GPUs in the world, and until a new industry-changing result (such as attention mechanisms were for current transformers) is discovered and presents a paradigm-shift in model architecture/training, we can expect smaller jumps in performance between large language model versions (such as the one between GPT3.5 and GPT4, which is definitely not as big as the one between GTP2 and GPT3 was).
Hopefully, in the meantime, collective/open-source efforts such as Cerebras-GPT will allow us mortals to train "homegrown" state of the art models again. This is crucial because models such as ChatGPT are highly fine-tuned (although more like highly lobotomized) to align with or avoid certain political/ethical opinions.
Thank you so much for the insightful answer, Ricardo! I have been utilizing huggingface to build a question generation and answering system in my nlp course and I endorsed it. Tech monopoly is truly disappointing. Also, I am concerned about my the insufficiency of AI ethics research and regulation despite the rapid development of LLMs. I guess I have a follow up question of what do you think I as an individual who is wishing to step into the data science industry could do to increase my competitiveness in the job market?
Qinglin