Dr. Lance B. Eliot is a world-renowned expert on artificial intelligence with over 8.1+ million amassed views of his AI columns and been featured on CBS 60 Minutes. As a CIO/CTO seasoned executive and high-tech entrepreneur, he combines practical industry experience with deep academic research.
Generative AI Shading The Truth When Answering That Viral Question Of Whether There Are More Wheels Or Doors In The WorldIn today’s column, I discuss an increasingly angry question being heatedly debated about whether software developers who are aiding the data training of generative AI and large language models or LLMs are acting in a traitorous manner when doing so to improve AI-based code generation capabilities.
The idea behind this is relatively simple. You could say that advancing AI toward generating programs and code will ultimately put all software developers out of a job.This analysis of an innovative proposition is part of my ongoing Forbes.com column coverage on the latest in AI including identifying and explaining various impactful AI complexities and then sets the valve accordingly .The programmer has divined what the line of code is intending to accomplish. The next step would be to inform generative AI about the gleaned insights.The code labeler adds comments to the code, trying to annotate what is going on so that the AI can more deeply analyze the code.. The code tutor explains to generative AI what the code is doing, and from that interactive explanation, the AI is able to more deeply analyze the code. In some situations, code labeling is the preferred route, while in other settings the interactive code explanation is undertaken. It all depends on the complexity of the code, the capabilities of the code tutor or labeler, and how the generative AI has been set up to try and figure out coding and programming machinations. All day long, that’s basically what the job consists of. The tasks would extend to doing likewise about various infrastructure that supports the code, including assorted programming utilities, tools, operating system facets, API or application programming interfaces, and so on. Please know that the job can be very demanding and requires a great deal of coding expertise. You normally don’t hire a newbie coder to do this kind of work. The reason you don’t is that they are less likely to know the coding tricks of the trade and are bound to miss out on what is actually going on in the code. I’m not saying you don’t hire newbies, only that if you do, they typically work under the tutelage of a more senior coding tutor or labeler. This aids in avoiding errors and the like.You might be given a bundle of code that you’ve never seen before. There might not be any documentation already existing for the code. From nothing other than the code, you must make all kinds of clever guesses about what the code is doing. In a sense, you are reverse engineering the code. In addition, the more advanced AI-based code generation is best aided by the code tutor or labeler going beyond just the presented code itself. For example, imagine that the valve value for “r” is later on in the code given the value of 4. The code tutor or labeler might have identified that the permissible values for the valve are only 2 or 3. Thus, the place in the code where the valve is set to 4 is a problem and the code contains a bug or error. By telling the AI about the bug, the AI might eventually in-the-large identify patterns of how to detect bugs in code. Notice that this is well beyond merely examining a particular line of code. The AI is somewhat getting data trained on how to interpret code and spot portions of code that might be buggy.You might be aware that one of the reasons that modern-day generative AI doesn’t spew out profanity and generally seems to carry on civil discourse is that a technique known as RLHF or reinforcement learning with human feedback is customarily used these days. That is how ChatGPT took the world by storm. The AI maker OpenAI had opted to use RLHF extensively on their budding generative AI before releasing it publicly they might decide to go to truck driving school as a backup to not being allowed to fly. This brings up two provocative or perhaps smarmy questions that I overhear among seasoned software engineers: Should software developers acknowledge the writing on the wall that AI is going to meet and likely surpass human programming skills?Well, first of all, truck driving is also facing the writing on the wall. The advent of autonomous vehicles such as self-driving cars and self-driving trucks is predicted to wean down the need for human drivers. No sense in switching from the frying pan to the fire. Second, we are still some distance from AI getting so good at programming that we would want to across-the-board have exclusively autonomously generated software. It can be done here or there. We are still in need of human software developers. Whether they are going to be coding from scratch is less likely and will instead be working side-by-side, shall we say hand-in-hand with generative AI. Doing so at this time can be exasperating for human software engineers. The AI is still clunky at times. The AI needs to get better at coding. Those code tutors and code labelers are doing their part. This could democratize coding, vastly expand the applications we might all enjoy, lower the costs of making use of applications, and change the world accordingly. Will this eliminate all those software developer jobs or aid them? Will this spur the need for more human programmers? Will AI only be proficient as a bottom-feeder in coding? Alas, haven’t we heard time and again that programmers would soon be outdated and out of work? This has been a clamor that existed when so-called 4GL or fourth-generation languages came along, as did even earlier when coding languages such as RPG were all the splash. Maybe generative AI is yet another in a long line of assertions that the sky is falling.Traitors or devisers of the future, it’s a conundrum and worthy of discussion, but do so civilly, please, and with suitable decorum, thanks.Our community is about connecting people through open and thoughtful conversations. We want our readers to share their views and exchange ideas and facts in a safe space.Insults, profanity, incoherent, obscene or inflammatory language or threats of any kindContinuous attempts to re-post comments that have been previously moderated/rejectedAttempts or tactics that put the site security at riskProtect your community.
Generative AI Large Language Models LLM Code Generation Software Developers Development Software Engineers Programmers Coders Data Training Labelers RLHF Reinforcement Learning With Human Feedback Labor Jobs Displacement Replacement
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