Fearmongers would have you believe that AI will replace us, but I truly believe there has never been a better time in history to be a developer.

With the advance of artificial intelligence into generative AI (GenAI) and enhanced computing power, we stand on the brink of a new era of development, whether it’s software, apps or models we’re developing.

More importantly, this is an era where we get to unleash what I consider to be our number one skill. I’m not talking about coding, debugging or writing documentation. ​

I am talking about our creativity.

Developers are naturally some of the most creative people in the world. Now, with artificial intelligence as an ally, you can experiment faster and be more productive.

It used to be that productivity was about having the best Vi Improved (VIM) commands or Editing MACroS (EMACS), but we’ve come a long way since the late ‘90s.

Now, we do our computing in the cloud and our editing in a browser, and poof, our terminals are gone. And yes, that hurt, but look where we’ve gotten.

With multimodal AI now on the scene, productivity accelerates data and AI life cycles to put models into production so we can make better decisions. We write the code that accelerates that life cycle and we build the models that support those better decisions.

And for anyone who didn’t know by now, when developers are more productive, our organizations are more productive.

What if there was a technology that could help you become both more productive and more creative?

Generative AI, anyone?

I know you’re already hearing about GenAI everywhere and skeptics would have you believe it’s overhyped or potentially even a creativity killer, but I’m here to convince you otherwise.

Here are four ways I’m seeing GenAI improve the developer experience today:

  1. Data exploration
  2. Modeling suggestions
  3. Brainstorming
  4. Data generation

Data exploration with GenAI

What if you had an AI assistant for developers feeding an endless stream of ideas to you?

Here’s an example: Let’s assume I have air quality data from which I want to gain insights. I ask my AI assistant to show me all the different air quality data sets and briefly describe the data in each one.

My AI assistant says I can see air quality data on a daily and monthly basis, so I decided to play with the monthly data. The assistant gives me suggestions that fit the data and automatically generates buttons to execute different types of analyses.

I don’t have to think about and code data preprocessing approaches. It’s done for me, so I can have more time for more important matters.

Now that I see my options, I start with a geographical analysis. The AI assistant executes it, plots the average air quality index across different areas and explains what I’m looking at on the map. I decide to analyze air quality trends and patterns over time, so I ask for a trend analysis. Right away, it generates insights grouping the data into regular cycles, seasonal variations and unexpected changes.

Some kind of developer dream, you might think? These kinds of AI assistants are on the way from SAS.

Building models with GenAI

You know how time-consuming building models can be. But what if you were working with someone who gave you model ideas you might never have considered? Your AI assistant can do that too. Just push the button for the model that looks most promising – time series, machine learning, optimization, etc. – and your assistant can train it with your data and give you the results.

Once you choose and execute your model, you might as well show off your work. With a little help from the SAS business intelligence tool Visual Analytics, you can build a C-suite-ready dashboard.

Want to look behind the scenes at the code being generated? Your AI assistant will be fully transparent: human in the loop, no black boxes. You can have your assistant send your coding interface to SAS Studio, where you’ll see the code and have the chance to accelerate different tasks with it. From there, you can add comments, fix bugs, convert Python code into SAS code or vice versa, a world of possibilities.

Brainstorming with GenAI

My favorite button is brainstorm. If I run out of ideas or strategies, I push the brainstorm button, and my AI assistant recommends even more data possibilities.

Whether you’re a developer, data scientist or business analyst – whether you’re in banking, health care, insurance or any other industry – you get to build your own AI assistant to be more productive and solve real-world problems. Just give it a name, a description, and a few starters and upload your data. Your creativity is the only limit.

Not only will your AI assistant be fast, precise and flexible, but it will also be large language model (LLM) agnostic and secure because it’s running on your Viya server. It also speaks and works in many languages, including English, Italian, Chinese, German, etc.

Generating data with GenAI

There is no good AI without good data. And sometimes real-world data isn’t good enough.

No matter how much you may wish it weren’t so, sometimes data can show bias. Or it may have sensitive information in it. Or maybe you simply don’t have enough data.

Let’s say a financial institution wants to detect fraud. The number of fraudulent cases is extremely small, so traditional modeling approaches struggle to effectively train models from what’s available.

Synthetic data may be the answer for all of these examples. That’s why I'm excited about a new SAS product being tested: SAS Data Maker.

Upload your existing data and Data Maker generates high-quality synthetic data in a low-code, no-code way that’s completely transparent. Data quality and privacy are automatically audited and you can compare relevant variables between the original data and the newly generated data.

No more manual data collection or having to buy costly third-party data sets, so you save time and money. No more showing potentially sensitive information, so you can safeguard privacy.

I don’t know about you, but I am ALL IN on creativity and productivity. I don’t see GenAI as a threat or a danger, but as a tool or partner to make my job even more fun and productive.

Generative AI: What it is and why it matters

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About Author

Marinela Profi

Global AI & GenAI Marketing Strategy Lead, SAS

Marinela Profi is the Global AI & GenAI Lead at SAS. Leveraging her extensive background in data science, Marinela brings a unique perspective that bridges the realms of technology and marketing. She drives AI implementation within Banking, Manufacturing, Insurance, Government and Energy sectors. Marinela has a Bachelor’s in Econometrics, a Master of Science in Statistics and Machine Learning and Master’s in Business Administration (MBA). She enjoys sharing her journey on LinkedIn, and on the main stage, to help those interested in a career in data and tech.

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