AI Revolution Won’t Happen Overnight, but It’s Happening

• 2 min read

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AI is coming – but like cell phones, it could take years to transform the world.

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Innovation has a history of shaping economic growth, and, in 2023, artificial intelligence (AI) captured the attention of investors worldwide.

OpenAI arrived with its ChatGPT programs that could research topics and write essays of any length in seconds. Microsoft quickly incorporated new AI capabilities into its search functions, followed by others seeking to do the same. Nvidia became a trillion-dollar company based on its semiconductor technology, designed specifically for the processing power needs of AI.

Capital has quickly followed suit, with venture investors seeking new business models that leverage the advantages of AI. In the first three quarters of 2023, more than $68 billion has been invested globally across AI and machine learning. This includes $4 billion invested in one company, Anthropic, which is building foundational AI models.

But don’t expect AI to change the world overnight. It’s more likely the technology’s impact will come in stages just like other waves of innovation. After all, it took mobile telephones decades to evolve into handheld computers.

AI has been in development for years, though the ChatGPT launch in November 2022 marked an important inflection point. While AI’s current applications include content generation and editing, like ChatGPT, it also shows great promise in software development, specifically writing computer code. As AI activity accelerates beyond the initial core applications, increased infrastructure will be required due to the power-processing demands.

As processing requirements are solved, specific user applications will develop, particularly those that enhance productivity and efficiency. For example, healthcare companies are innovating with AI to assist in diagnostics and radiology, leveraging massive datasets from prior cases to improve the outcomes for future patients. Better understanding prior treatment models for specific diseases, paired with a particular genetic makeup of a patient, would allow physicians to better tailor treatments.

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