Meeting this moment: AI-driven automations

When I was a software engineer, I saw many waves of transformation. Social-first, mobile-first, analytics-first, and cloud-first, together better known as SMAC, were chief among many of these firsts I witnessed in the over two decades I spent in that field. Having witnessed these shifts, my biggest takeaway: change is constant. Now, change is faster than ever. Today, over 15 years after my full-time software engineering days ended, I am the president and owner of Divergence Academy, a 3x Inc. 5000-recognized vocational educational school for emerging tech. Despite the rapid speed of technological change, I see many learners we serve are still coming around to the idea of learning IT, let alone SMAC. AI-driven automation will be crucial in bridging this gap. Divergence Academy is committed to helping us get there.?

?

For those of us closely following the tech landscape, it can be crazy to note that ChatGPT was only just announced 18 months ago. It already feels ingrained in the fabric of so much of what we do technologically. Yet, AI-driven automation is so new, no one has 2-5 years of experience in this field. Anyone working in, or moving into, this field must be reskilled or upskilled. In this way, this new wave of AI truly creates a level playing field for us all to work and learn in.?

?

Automation has existed for a while. Software engineers and other IT professionals have been using automation to provision resources. Test automation suites have been used to develop software applications. But today, this new type of automation enabled by natural language is available not just for technical professionals but for the common man across all generations. The other day, my mother-in-law, who’s in her mid-eighties, experienced difficulties chatting with a bot to get an issue resolved with Amazon. She had to request the “artificially-intelligent” bot to transfer the case to a “human-intelligent” customer support agent. These were her words. In this way, our vocabulary is changing — fast. Natural language is defining the new wave of automations. Every automation — from Robotic Process Automation (RPA) to Digital Process Automation — is being natural language-enabled. We ain’t seen nothing yet.?

?

There is a consensus in the tech community: the more we automate, the more jobs will be lost. I disagree with this consensus. The Jevons Paradox demonstrates that greater technological efficiency leads to greater usage. In this case, it suggests that the need for AI-enabled workers will only increase with its greater usage around the world.?

?To prepare for this, we are already seeing newer hardware being envisioned by Intel: Neural Processing Unit (NPU) based laptops. The idea is to move some AI-driven automation processing to laptops. The big players will continue their one-upmanship on Large Language Models (LLMs), but there is a gradual shift to focused domain-based Small Language Models (SLMs). These SLMs will run locally on mobile devices – laptops, phones, and next-gen devices with new interfaces. They have another huge advantage, too: they will lead to greater energy efficiency and help the world more quickly reach carbon neutrality.?

?

We are at an inflection point. Gen-Z has just entered the workforce, and Gen Alpha will be right behind them in less than a decade. AI-driven automation will become native to these generations joining the workforce. It is like a few countries in Africa who moved directly to mobile devices and satellite communications — they never had to dig for landlines. Marc Presnky’s article, ‘Digital Natives, Digital Immigrants’ addresses the fact that students in 2001 were no longer the same people the educational system was designed to teach. He went on to explain that the differences between millennials and Gen-Zs weren’t just incremental or simply down to a change in style or trends. He described ‘the arrival and rapid dissemination of digital technology in the last decades of the 20th century’ as an ‘event which [changed] things so fundamentally that there [was] absolutely no going back.’ In fact, he argues that Gen Z individuals think and process information differently from their predecessors; they are ‘native speakers’ in all things digital, compared to digital immigrants who were not born into the digital world but rather thrown into it and forced to adapt.?

?

More resource hungry means we need bigger and better data centers powering the need for more energy. One example, helping to kick this off, is that Microsoft recently invested in nuclear power. Another example came from one of our Data Science Immersive learners at Divergence, who asked me if learning Rust was a better idea than learning Python. The reason the student gave is that he learned Rust was more efficient. Our subsequent back and forth led us to discuss computational costs, and how an efficient language would be better at reducing those costs. Per AWS’ blog, the broad adoption of C and Rust could reduce energy consumption of computation by 50% – even with a conservative estimate.?

?

Mastery of the English language to prompt the bots to generate the desired output is becoming the need of the day. Last year, I was at Pegasus Park in Dallas listening to a panel who shared that now that the BioLabs are available in the city, they would love to see talent with problem-solving skills generate new ideas, or take existing ideas and turn them into solutions, fail fast, and try again. The need of the day was not tech, but the ability to use their general education (the 30 hours in an associate degree), and the use of the AI-driven automation tools, to move the biotech business forward. I continue to hear the same need from multiple executives. Technology can be taught if the person joining the workforce is motivated to apply their general education skills.?

?

The conundrum: the need to balance the slow job displacement happening today with increased support for tomorrow’s workforce, which is on top of most executives’ minds. Technology shifts are happening at tectonic speed today. Taking an idea from incubation to the masses takes less time than ever. The semi-conductor industry must scale quickly to support the demand.??

?

We are at an exciting point in time in the IT industry. The demand for the workforce that understands AI-driven automations, able to use the English language to seek new knowledge about the problems and solutions for any given industry (ex. biotech), and adopts these new tools and practices them, is real. The upskilling and reskilling needs of the industry are high.???

??

Divergence Academy is embracing these shifts. We have embraced AI across all our six immersive programs, including our new Automation Process Analyst Immersive launching on June 3, where we will be covering the some of the best of how you can use the English language through LLMs and SLMs to increase your everyday productivity.?

??

We have a ton of new problems to solve. Few things excite me more than new solutions through new technologies. I’m always hungry for more. Let’s get started.