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'Tech Connects' Podcast: Eric Wang on AI Impacting Education, Training
“Tech Connects,” Dice’s podcast, digs into the tech hiring, recruiting, and career topics that matter to you. Subscribe on ACast, Spotify, Apple Podcasts, iHeartRadio, Amazon Podcasts, and YouTube! Our next guest on 'Tech Connects' is Eric Wang, VP of AI at Turnitin, which provides tools to academic institutions for everything from course assessment to academic integrity. For example, they have a platform that detects the use of AI in students' papers. Artificial intelligence (AI) and machine learning are having a huge impact right now on how students learn and educators teach, and I wanted to talk with Eric about how the education industry is navigating these changes. At the same time, I also wanted to dig a bit into how AI is changing the very nature of education, training, and ultimately work itself. Let's listen in! Here are some quick takeaways from this discussion for any tech professionals interested in how AI will impact training, education, and work both in the near- and long-

May Tech Unemployment Dipped Despite Economic Turmoil
The tech unemployment rate dipped from 3.5 percent in April to 3.4 percent in May, according to the latest CompTIA analysis of data from the U.S. Bureau of Labor Statistics (BLS). Meanwhile, the nationwide unemployment rate held steady at 4.2 percent. Tariffs, mass layoffs within the tech industry, and other macroeconomic trends have been weighing on tech hiring activity. Within the tech sector, companies only added 1,571 net new employees in May, and tech occupation employment across the broader economy dipped by an estimated 131,000 jobs. Meanwhile, hiring for dedicated AI jobs held steady in the nation’s largest tech hubs. In San Jose and San Francisco, for example, AI and machine learning positions constituted 17 percent and 13 percent of all job postings, respectively; meanwhile, AI jobs were the focus of 9 percent of New York City’s tech job postings. Seattle (7 percent) and Washington DC (5 percent) are also notable for their AI hiring activity. Employers also continue to lean o

How to Build a Sentiment Analysis App in Python
We’ve all seen the rating systems on e-commerce sites such as Amazon. Whether based on stars or a point scale, such systems are an easy way for users to gauge the sentiment around a product. Many tech professionals are tasked with coding something similar for their own organizations, along with surveys and feedback platforms—and sometimes they run into issues around building out an accurate sentiment analysis. Using Python and a few libraries, it’s surprisingly easy to build a sentiment analysis tool. You can use this to process internal reviews, survey answers, product feedback, and so on. Let’s walk through how you can create such an app. What is Sentiment Analysis? At its core, sentiment analysis involves using AI to determine the emotional tone of feedback, ideally bringing out nuances. On a trivial level, it might seem easy, especially in the context of product feedback and reviews. For example: I love this feature! This is obviously positive. It’s okay. Nothing great, but it work

How Leaders Can Integrate AI into Their Teams Workflow
If you’re a team lead or manager or product owner, you’ve probably wondered how you can effectively integrate AI into your developer team’s workflow. You recognize that AI can’t (yet) replace developers. And you also recognize that developers are probably resistant to bringing AI into their workflows. What can you do? Resistant Senior Developers Let’s tackle the latter issue: Developers who are resistant to integrate AI into their workflow. If you have such developers on your team, they’re probably mid-to-senior level, very likely older, and very good at what they do. They haven’t really embraced AI themselves: for example, instead of asking ChatGPT for help on a problem, they might still go to StackOverflow. They might not trust AI. They know in their hearts that computers cannot code computers as well as people can. And that’s still true, even with AI strengthening its code-generation abilities. But they might be surprised how AI can help them code faster and more efficiently—despite

Build a Voice Command App with Speech Recognition and AI (Like Alexa, but Simpler)
By now, most of us use the voice recognition on our devices regularly. We shout at Alexa to play a different song; we ask Siri on our phones to give us driving directions. The technology has evolved exponentially since Siri and Alexa arrived more than a decade ago—and that was before generative AI. Thanks to generative AI, you can actually create a Siri-like app yourself… or integrate Siri-like features into your existing apps. Let’s look at what it takes to build a standalone voice recognition app. We’ll keep it simple: this app should: Listen to what you say and convert the speech to text Interpret what you want And either: Come up with some sort of command, as with a device that performs some task in response to spoken language (such as a request to play a song) OR Uses AI to build a human-sounding response and speaks that human-sounding response back in a natural-sounding voice Coding Libraries You’ll Need We recommend building this app using Python, as it has the largest AI infras