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AI Is Not Only a Thing of the Future, It’s Also a Thing of the Present

Artificial intelligence (AI)-based platforms have taken the world by storm. Perhaps the best known of these is ChatGPT. OpenAI, the company that developed the innovative chatbot, released the tool widely to the public in November 2022. Analysts have said ChatGPT crossed the million-user mark five days after launch. Less than three months later, it had more than 100 million active users, making it the fastest-growing consumer app in history. Other similar platforms, including Google Gemini, Microsoft Bing Bard, AI21 Studio, Mesa, and Cohere, have also experienced rapid growth.

“We are on the verge of the most profound industrial revolution in human history,” Zack Kass, a self-proclaimed AI futurist and the former head of Go-to-Market at OpenAI, said during a presentation given at DISTRIBUTECH in Orlando, Florida, in February. “It is very clear that what is about to happen is probably more important—more seminal—than the invention of fire, the wheel, aqueducts, the electrical grid, the internet. It’s almost certain that AI will move the human experience forward in ways that those experiences did not.”

Further Along Than Most People Realize, but Much More to Come

Kass noted that the technology people are using today on their computers and phones was proven in scientific papers 18 to 24 months ago. He said there are reasons for the lag, but what’s important to understand is that the technology is much further along than most people realize. And, yet, we are also much earlier in the evolution of AI than most people can contemplate.

“Today, people are already studying 3D, olfactory, major, major movements in robotics that are coming out in published papers,” Kass said. “There are early, early signs that suggest the transformer is going to get us in much further than we previously expected, and ultimately, the argument here is that we are—humans—beginning an exponential journey together, which is really exciting.”

The transformer model Kass mentioned can translate text and speech in near-real-time. IBM explains that text-based generative AI tools such as ChatGPT benefit from transformer models because they can more readily predict the next word in a sequence of text, based on large, complex datasets. Transformers process input sequences in parallel, making them highly efficient for training and inference, and requiring less training time than previous recurrent neural network architectures.

Kass also said artificial general intelligence (AGI) could radically change the way the world’s problems are solved. AGI theory suggests that, at some point, perhaps sooner than we think, AI will become smart enough to help itself make novel scientific discoveries. With that in mind, Kass said he would argue that AI was the last technology that humans will ever invent on our own.

“We are about to have a wave of scientific breakthroughs,” Kass predicted. “I think it is basically certain that we will cure cancer and neurodegenerative diseases, probably within the decade. We will almost certainly solve fusion within the decade—nanotechnology, quantum computing, diabetes—this is going to happen.”

How the Power Industry Is Using AI

Yet, ChatGPT and other generative platforms are not the only AI use cases. Companies serving the power industry are using AI and machine learning (ML) models today in real-world applications to solve a variety of problems.

For example, Locana, a TRC company, is working with a number of utilities on AI/ML–based pilot projects that address power industry challenges. “The combination of AI/ML and location intelligence will give utilities the ability to solve complex problems that are at the heart of grid modernization, decarbonization, graying of the workforce, and accelerating risks related to climate change,” Jeff Haight, CEO of Locana, told POWER during an exclusive interview at the DISTRIBUTECH event.

“This combination of technologies will drive problem-solving and foster efficiencies that solve many of the strategic and operational challenges that utilities face, but companies need to have the right strategy and be focused,” said Haight. “In every meeting we are having with utility leaders, we are advising something different—use case-driven projects that harness the power of AI/ML and location intelligence to address specific pain points.”

Haight shared some examples of work Locana has done. “We’re partnering with several utilities to do implementations that are showing immediate results,” he said. “An example of that is a pilot project that allows higher-precision vegetation management and wildfire risk mitigation, using a combination of AI/ML technology, geospatial data, and mobile devices.”

Another example he cited involves using a ChatGPT interface to give non-expert users across an organization access to geospatially driven insights that turn infrastructure projects that would typically take months or years into projects that take only days or hours. The last example Haight mentioned leveraged reality capture technology at substations. He said it provides much-needed detail about the as-built assets that are often a blind spot for utilities’ infrastructure models. Haight noted, “With the right partner and the right focus, these use case-driven projects will enable utilities to quickly turn the potential of AI and ML into reality in areas of great need.”

Anything Is Possible

According to Kass, the most exciting thing about the future is that each new discovery or invention that AI makes will represent a “Wright brothers moment,” that is, an eye-opening breakthrough that causes people to start looking toward previously unimaginable ideas. “In the same way that the Wright brothers flew a plane and then we went to the moon 60 years later, there’s a non-zero chance that these inventions give way to all sorts of new ideas and things that we weren’t even considering today—problems that we haven’t even considered solving,” Kass said.

“With any AI, it’s truly, the sky’s the limit,” said Haight.

—Aaron Larson is POWER’s executive editor.

Originally Appeared Here

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