You’re kind of (or a lot) into tech. You get your news from Twitter, Reddit, Medium, #random in Slack, etc.
For the past two months, your feed is getting increasingly full of GPT-3 related posts. You start to get curious, and go ahead and research to see what all the fuzz about the new OpenAI autoregressive language model APIis all about.
In the meanwhile, you find out some projects that are using GPT-3 to understand requests written in plain English and to generate some output that makes a lot of sense.
This by all means is hugely impressive and *really* cool, if you ask me.
The ability of the GPT-3 to generate layouts, Python code, or creative content is shocking to most people. And it should be. It’s really strange to see a machine learning model that can comprehend and act upon requests in a reasonably correct fashion.
So with that in mind, let’s get to the main topic.
The GPT-3 won’t get you laid off
Well, at least for then near future. I won’t dare to give it a timeline, as I’m a firm believer in the following:
“It’s tough to make predictions, especially about the future” — Danish Proverb
And, of course, I’m not referring to the folks that are working 9 to 5 as an autoregressive language model API. Feel sorry for you.
When innovation comes to disrupt tasks performed by people, the discussion of the effects of the technology regarding society always gets heated. When such innovation is seemingly disrupting the output of a workforce that is known to produce things that are similar to magic, like software engineers in general, things are definitely getting more heated than previously.
We, as tech people, are having some mixed feelings that are affecting our judgment.
I’m afraid that the notion that the GPT-3 is a truly groundbreaking achievement and, at the same time, it won’t hurt us, is not being brought up as frequently as it should.
- Yes, it can generate code. Just because of that, I wouldn’t advise you to switch careers or fire your engineering team.
- Yes, maybe the code that is generated is not as fancy as the code you write with 5,10 or 20+ years of experience, tricking the compiler or the framework to achieve maximum performance. Just because of that, I wouldn’t advise you to ignore it completely, like a super-hyped technology that will be forgotten on a dusty shelf.
“Deep Learning is a superpower” — Andrew Ng
We need to learn how to use it to potentialize our craft, before anything else.
The tools that can be created with the use of GPT-3 and other ML models to help us build, keep, and run better technology are in a league of their own. And they could help us, as professionals, to reach a new level of productivity, quality, and overall expertise.
In our little tech bubble, we can think of the new possibilities that are brought to the table with the GPT-3.
We can reimagine and build, from the ground up, the tools that we use daily — for coding, designing, managing work, etc — in order to become better professionals.
For example, we can use it to build better IDEs. Smart IDEs. Some companies have already started the work in the field and have developed great products. However, I feel there’s a lot more to evolve, and even to reimagine what an IDE can look like.
We should work on those tools so that we can be better at our craft, not to replace us altogether.
A vast portion of professionals of all areas have had to reinvent themselves through the years due to the code that we’ve written and all of a sudden we ourselves are unable to do the very thing we’re advocating for decades?
It’s up to us to learn how to use our new superpower.