The United States of AI
In 1956, American assistant professor of mathematics, John McCarthy, met with his colleagues to discuss and later coin the term “artificial intelligence.” Soon scientists worldwide were teaching computers to play chess and robotically speak languages. It was just the beginning.
In 1965, Herbert Simon, a contemporary of McCarthy, boldly proclaimed, “Machines will be capable, within 20 years, of doing any work a man can do.” Though this prediction was a bit ambitious, artificial intelligence (AI) has advanced exponentially. The most straightforward way to illustrate this might be in looking at computing usage for AI from the 1960s until 2020, shown in petaflops, a measure of high processing speed.
Until 2012, AI computing power followed Moore’s Law and doubled about every two years. After 2012, computational power made an even more significant leap, with AI computing power doubling every 3.4 months ever since. This creates an unprecedented high requirement of computing power for AI, which the industry is eagerly adopting.
Besides the great anticipation of computer scientists, technologists, investors, and futurists, this advancement of the intelligent machine has been met with trepidation from those who fear AI may take jobs. However, an article in Stanford Business claims that demographic shifts, not AI, create the most significant workplace challenges.
What used to be considered possible only by human intelligence is being realized through machine learning by AI. For instance, AI senses its environment and continuously makes adjustments to achieve specified goals. Computer algorithms now may improve automatically through experience using machine learning.
The World Economic Forum (WEF) published a report on the global impact of robotics and automation. The chart below shows their impact on wages to be surprisingly positive overall, with increased use in robotics/automation correlating to higher salaries.
Higher-value technology leads to higher-value jobs while increasing productivity, leading to economic growth in countries adopting robotics/automation.
The WEF report concludes countries that don’t adopt policies on robotics/automation with training programs for the workforce fall behind those that do. Amazon has invested in extensive training programs in AI and machine learning, some free of charge.
Today AI is used in the military, healthcare, security, e-commerce, advertising, agriculture, education, finance, transportation, climate, and other fields. Let’s take a look at just a few applications.
In August 2020, an AI won a dogfight with a human F-16 fighter pilot in the US Air Force. 4 billion simulations trained the AI to adapt under almost any circumstances. The US Air Force recently revealed its Skyborg program of autonomous unmanned drones that fly alongside fighter jets, controlled by AI.
These Skyborgs are fully autonomous and do not require a human to guide them. One of their proposed uses is to deflect attention from other crewed operations. The Air Force expects to have these AI drones in 2021 for testing and operational by 2023.
While AI developments like the Skyborg affect the military, they will also enable advancements in the transportation industry, and even space exploration as the technology is applied across related industries. Perhaps the most well-known AI application is its use in autonomous driving technology, helping cars become safe self-drivers, saving millions of lives every year, and preventing car crashes (90% caused by human error).
AI will even assist weather forecasting. The National Oceanic and Atmospheric Administration (NOAA) teamed with the Google AI team to add over a decade of weather data onto Google Cloud so Google may use its AI on its data sets. NOAA has used supercomputers to predict weather patterns for years, yet this model was still often unreliable. The addition of AI to this model will increase its accuracy exponentially.
Google’s AI may even develop microclimate models for more localized predictions. With these new models, we might see when to expect rain on one side of town but not the other.
AI could also help model global climate change and show how agriculture, temperatures, and sea levels are impacted. These models could give us advanced notice for hurricanes and typhoons.
The uses for AI in health and wellness are vast. Analysis of complex human vital data is just one area. AI may now help us treat diseases by analyzing billions of compounds, expediting the discovery of new drugs and therapies for millions.
Market research shows that the adoption of AI technology is increasing up as well. International Data Corporation, a market analysis firm, reports $50 billion will be spent developing AI in 2021. Spending is expected to grow to 110.7 billion in 2024.
Soon, there will be almost no industry untouched by AI. We at Beyond Enterprizes will continue to watch its advances and report our findings in this fascinating field.
