Data Science WorkFlows with ChatGPT

Useful, in KDNuggets.

Automate the Boring Stuff with GPT-4 and Python   KNuggets

Speed up your daily workflows by getting AI to write Python code in seconds.

By Natassha Selvaraj, KDnuggets on March 28, 2023 in Python

Automate the Boring Stuff with ChatGPT and Python

On March 14, 2023, OpenAI launched GPT-4, the newest and most powerful version of their language model. 

Within just hours of its launch, GPT-4 stunned people by turning a hand-drawn sketch into a functional website, passing the bar exam, and generating accurate summaries of Wikipedia articles. 

It also outperforms its predecessor, GPT-3.5, in solving math problems and answering questions based on logic and reasoning.

ChatGPT, the chatbot which was built on top of GPT-3.5 and released to the public, was notorious for “hallucinating.” It would generate responses that were seemingly correct and would defend its answers with “facts”, although they were laden with errors.

One user took to Twitter after the model insisted that elephant eggs were the largest of all land animals:

Automate the Boring Stuff with ChatGPT and Python

And it didn’t stop there. The algorithm went on to corroborate its response with made-up facts that almost had me convinced for a moment.

GPT-4  on the other hand, was trained to “hallucinate” less often. OpenAI’s latest model is harder to trick and does not confidently generate falsehoods as frequently.

Why Automate Workflows with GPT-4?

As a data scientist, my job requires me to find relevant data sources, preprocess large datasets, and build highly accurate machine learning models that drive business value. 

I spend a huge portion of my day extracting data from different file formats and consolidating it in one place. 

After ChatGPT was first launched in November 2022, I looked to the chatbot for some guidance with my daily workflows. I used the tool to save the amount of time spent on menial work - so that I could focus on coming up with new ideas and creating better models instead.

Once GPT-4 was released, I was curious about whether it would make a difference in the work I was doing. Were there any significant benefits to using GPT-4 over its predecessors? Would it help me save more time than I already was with GPT-3.5?

In this article, I will show you how I use ChatGPT to automate data science workflows. 

I will create the same prompts and feed them into both GPT-4 and GPT-3.5, to see if the former indeed does perform better and result in more time savings.  ....  '

Robotic Process Automation

Well put intro piece in Venturebeat  by Peter Wayner

Robotic Process Automation in 2022

In 2021, enterprise teams turned to robotic process automation (RPA) to simplify workflows and bring some order to office tasks. The next year promises to bring more of the same sophisticated artificial intelligence and task optimization so more offices can liberate their staff from repetitive chores.

The product area remains one of the poorly named buzzwords in enterprise computing. There are no robots in sight. The tools are generally deployed to fix what was once known as paperwork, but they rarely touch much paper. They do their work gluing together legacy systems by pushing virtual buttons and juggling the multiple data formats so that the various teams can keep track of the work moving through their offices.

Here are the 10 ways that RPA marketplace will shift and adapt in 2022:

Better Integration

The main job for RPA is to knit together some hundreds of legacy systems that now make up the backbone of many companies. The main challenge for each RPA company will be strengthening the connections between systems. That means more modules or bots in the marketplaces and better versions of the existing ones.

Lower Code

One of the major selling points for many RPA vendors is that their tools can come close to programming themselves through what some call “process discovery.” While this may never be as magic as anyone wants, the tools will continue to simplify this job. It may even approach “no-code” level automation for some simple tasks.

Higher Code

It seems contradictory to imagine that RPA platforms will simultaneously get easier to program and harder, but these changes will be seen in different levels of tasks. While the interns and managers will be able to automate more simple tasks, the developers will be called to customize the RPAs for more complex integrations. In many cases, RPA tools make good frameworks that sophisticated programmers can revise and extend. The RPA handles 95% of the work and the development team handles the last 5%. This is why some companies are reporting that RPAs are more complicated and expensive to maintain than they thought. Companies are asking them to do more and more sophisticated jobs, and that means bringing in better programming talent.

More AI

Craig Le Clair at Forrester Research predicts that every RPA company will either embrace AI or “become a dinosaur”. While this may never become strictly true, there’s no doubt that RPA is one of the simpler vectors for inserting AI into corporate DNA. The standard modules tackle tasks like optical character recognition, machine learning, and machine vision. RPA firms that ship better, smarter AI modules will be able to win more contracts. The accuracy and depth of the AI algorithms will rise in importance.

Divergence

Some firms need all the cleverness that AI scientists can deliver. Some firms, though, do not. Many of the AI options are aimed at dealing with older, paper interfaces or other tasks that require adaptability. One popular job for AI is to convert paper documents into digital form and then search for relevant data like the invoice number or the expiration date for a driver’s license. Some workflows, though, are pretty mature and don’t need this extra dose of smarts. Companies that process little paper or don’t need the extra intelligence may find they’re not as interested in AI-based innovations.   ... ' 

Google Cloud Workflow

 Brought to my attention and review, follow link for free trial:

Google Cloud Workflows

Orchestrate and automate Google Cloud and HTTP-based API services with serverless workflows.

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Orchestrate Google Cloud and HTTP-based API services into serverless workflows

Automate complex processes,  Fully managed service requires no infrastructure or capacity planning.  Fast scalability supports scaling down to zero and pay-per-use pricing model ....