I need assistance establishing Python code to detect similarities among two lists of names and generate a relatedness ranking. Hence, I asked ChatGPT: “What would be the best way to write Python code which locates nearly matching elements across two collections of names and calculates a similarity ranking?
The FuzzyWuzzy library from Python can compute similarity rankings and find close matches between stamps, allowing you to gauge how similar two names are.
ChatGPT displayed code that enabled users to interface with FuzzyWuzzy, complete with helpful examples to guide them.
ChatGPT provided users with a code that enabled them to access FuzzyWuzzy and included sample use cases for their reference.
Generative AI is quickly becoming important in marketing, journalism, the arts, and software development – raising debate about ChatGPT’s intelligence, code safety, and source acknowledgment. Yet, it is undeniable that the benefits of this technology are giving people something to think about.
Quali, a company dedicated to making contextual cyber automation easier, tasked their Vice President of Research and Development – David Ben Shabat – with expressing this commitment worldwide.
David Ben Shabat says:
“Generative AI, such as ChatGPT and AlphaCode, are sure to have an immense impact on how organizations develop applications—from enabling faster and more efficient development cycles to optimizing customer experiences—over the next three years.”
“As AI continues to develop, businesses will be able to use these models to optimize customer experiences, increase customer engagement, reduce customer service costs, as well as overall cost reduction.”
Arjun Chandar, CEO at IndustrialML, adds:
“Generative AI tools will make it at least marginally more feasible to use machine learning for a broader array of applications across a larger number of domains.”
ChatGPT, with its user base of over 100 million, has been embedded in MS Office products and Bing by Microsoft. Meanwhile, Google’s Bard is another AI for searching. Developers can access code-generating AIs such as AlphaCode and GitHub Copilot for testing.
Integrating an array of Software has facilitated ChatGPT as a Service product, tech platform, and service provider. To illustrate, Gigster has incorporated ChatGPT integration, and Equally, AI launched Flowy, an application driven by programmed intelligence that enables web accessibility.
Don’t Fear AI; Leverage Its Capabilities
Software developers and DevOps engineers will likely start experimenting with generative AI tools, wondering how it will impact their profession and work. Policymakers may find it necessary to address the potential implications of these developments.
Marko Anastasov, the cofounder of Semaphore CI/CD, says:
“Generative AI tools such as ChatGPT have caused a stir among the developer community.”
“Some fear it will take their jobs, while others prefer to ignore it. Both attitudes are mistaken because, as we’ve seen with GitHub Copilot, a developer who integrates AI into their workflow can experience an incredible productivity boost.”
Utilizing my CRM example, I cut the time required to identify a useful Python library and find coding examples, accelerating the process immensely. However, I ultimately had to evaluate that information and integrate it into my application – a task I had yet to embark on.
Generative AI Lacks Context
It was remembering when you first got your Amazon Alexa or Google Assistant in your domicile, trying to make it act as cleverly as Star Trek’s computer did, expecting a similar result.
Aided by voice activation, you can use Alexa to perform basic activities such as setting alarms, compiling shopping lists, and providing current weather updates. However, this virtual assistant may not be sufficiently equipped to respond precisely to more complex queries.
Developer advocate at Sonatype, Dan Conn, thinks grasping the contexts from which AI algorithms are created and trained is essential.
Dan Conn says:
“Since the technology is based on data and not human intelligence, sometimes the program can sound coherent, but it does not provide any critically informed responses.”
The experience of using ChatGPT and other AI-powered Software can provide valuable insights into the challenges and best practices of software development. As we have seen, even the most advanced and well-designed Software can encounter unexpected errors and limitations and require ongoing maintenance and improvement.
To address these challenges, software developers can benefit from adopting a systematic and agile approach to software development that emphasizes testing, feedback, and collaboration. By involving users and stakeholders in the development process and by using tools and techniques to detect and fix bugs and vulnerabilities early on, developers can enhance the reliability, usability, and security of their Software.
Moreover, software developers can also learn from the ethical and social implications of their Software and take responsibility for its impact on users and society. This includes designing Software that respects user privacy, autonomy, and dignity and does not reinforce harmful biases or stereotypes.