Earlier this year, two partners at prominent venture-capital firm Andreessen Horowitz published an interesting blog post about artificial intelligence (A.I.). Specifically, is A.I. (and by extension, machine learning) capable of powering a sustainable business? Or is the tech industry infatuated with a technology thats just a lot of empty hype?

Its a worthy question as we close out 2020, considering how much money and resources companies are pouring into all things A.I.-related (often despite budget cutbacks related to the COVID-19 pandemic). Martin Casado and Matt Bornstein, the partners in question, conclude that A.I. is indeed viablebut that A.I.-centric businesses cant operate like traditional software firms.

Specifically, A.I. companies have lower gross margins (dueto the need for lots of expensive and talented humans, as well asinfrastructure expenses), scaling challenges (due to edge cases), and weakerdefensive moats (because of more A.I. tools and apps becoming commoditized,among other issues).

Traininga single A.I. model can cost hundreds of thousands of dollars(ormore) incomputeresources, they wrote. Whileits tempting to treat this as a one-time cost, retraining is increasinglyrecognized as an ongoing cost, since the data that feeds AI models tends tochange over time (a phenomenon known as data drift).

If the A.I. model is training on something storage-intensive like video, things get even worse. Add on top of that the cost of humans to design and wrangle the models, and you can see how any hoped-for profits from an A.I. project could quickly evaporate.

The entire Andreessen Horowitz posting is worth reading, especially if youre debating whether to jump aboard an artificial intelligence startup. Amidst all the discussions of cloud-infrastructure costs and model complexity, though, one thing stands out: the overwhelming presence of human beings within A.I. systems that are supposedly becoming more and more automated.

Its not just a question of employing people who can build and continually maintain models. For many tasks, especially those requiring greater cognitive reasoning, humans are often plugged into A.I. systems in real time, the posting added. Social media companies, for example, employ thousands of human reviewers to augment A.I.-based moderation systems. Many autonomous vehicle systems include remote human operators, and most A.I.-based medical devices interface with physicians as joint decision makers.

And theres no end in sight to intervention: Many problemslike self-driving carsare too complex to be fully automated with current-generation A.I. techniques. Issues of safety, fairness, and trust also demand meaningful human oversighta fact likely to be enshrined in A.I. regulations currently under development in theUS,EU, and elsewhere.

Weve seen these sorts of issues cropping up already among companies with artificial intelligence products. A few years ago, for example, Google rolled out Duplex, its automated voice assistant, which it predicted would revolutionize the process of making reservations and dealing with customer service. However, journalists quickly demonstrated there were relatively straightforward ways to stump Duplex. As of mid-2019, 25 percent of Google Duplex calls were supposedly made by human operators as opposed to an A.I.

Now consider all the A.I.-centric (or A.I. hopeful, for those still trying to develop an application) businesses that dont have Googles talent or resources. The dream of building an artificial intelligence model thats fully capable of performing its assigned task without any sort of human interventionwell, thats likely years away.

Andreessen Horowitz isnt the first firm to warn about thisissue. In 2019, ArvindKrishna, IBMs senior vice president of cloud and cognitive software, warnedthat A.I. initiatives could implode once companies realize how much effort istruly necessary to prep the related data. You run out of patience along theway, because you spend your first year just collecting and cleansing thedata,he told the audience at The Wall Street Journals Future ofEverything Festival,according to the newspaper.

Ina 2018 blog posting,A.I. researcher Filip Piekniewski listed all the ways in which theartificial intelligencehype wasnt matching withreality, includinga lack of progress in Googles DeepMind. Two years later, its clear thatA.I. is still grinding forward as a discipline, consuming lots of cash andtalent as companies hope for incremental advances.

But at least artificial intelligence researchers are still making lots of cash. And, despite these challenges, keep in mind that automation is still a long-term risk to many professions.

Ultimately, A.I. and machine learning technologies that help companies handle customer personalization and communication, data analytics and processing, and a host of other applications will continue to grow, even if it takes longer than expected to achieve seamless automation. An IDC report found three-quarters of commercial enterprise applications could lean on A.I. by next year alone, while an Analytics Insight report projects more than 20 million available jobs inartificial intelligenceby 2023.

Whether youre a manager or a software developer, in other words, prepare for A.I. (even weaker A.I.) to change how you work. Make sure to review the 10 jobs that could be radically impacted by these technologies sooner than you think.

Want more great insights?Create a Dice profile today to receive the weekly Dice Advisor newsletter, packed with everything you need to boost your career in tech. Register now

Visit link:

Artificial Intelligence (AI): Is It All Just Costly Hype? - Dice Insights