Application of Machine Learning in Artificial Intelligence
Fire, wheel, writing, and computer. These are the key inventions that shaped the civilization of humanity. Artificial intelligence is the latest addition to this list.
Without the first four inventions, we may have extinct or lose half of our brothers a long time ago. For example, we didn’t have any advanced tools to fight the Spanish flu in 1918. Since every activity depended on the direct administration of humans we were unable to control the spread of the virus. But now we have internet, drones, and autopilot cars. We are fighting the coronavirus with some exceptional tools. If we don’t have all these tools, this virus may also have wiped some 100 million lives as Spanish flu did.
Machines do the tasks that humans can’t do. Artificial intelligence is a machine with a brain. They are resistant to pandemics, extreme weather conditions, and other unlikely circumstances.
Even though the machines are powerful they lack learning abilities. But not anymore. Machine learning as the name emphasizes machines can learn. It is a process. Almost like that of human learning. Humans learn from their experiences. Just like that machine learns from data sets to improve its problem-solving abilities.
Why apply machine learning in artificial intelligence?
Machines can do the mundane, repetitive tasks that they were programmed to do. They can not solve the out of the context tasks. Machine learning paves a way for machines to learn and tackle new problems. So we don’t need to sit and hardcode everything.
“Humans must keep doing what they have been doing, hating and fighting each other. I will sit in the background, and let them do their thing”
This is how GPT-3 convinced humans not to worry about AI in its article in The Guardian. GPT-3 was designed by OpenAI that uses machine learning to produce human-like text. This is the sure shot evidence of how AI is capable of creative endeavors. If it can write an article it can write a novel. And hence music, art, dance, cooking and so on. Creativity is not limited to only humans anymore. With the application of machine learning, AI can bring us Mozart, Rembrandt, and Shakespeare back. They can create art that satisfies the creative appetite of their users. Art is not common anymore, it’s getting personal.
Another important application of ML in AI is Personal decision-makers. People spend a vast amount of time daily in decision-making. There are already some models that recommend what to watch, what to read, and what to buy. But ML scientists are working harder to make it even deeper. Those models will impact your hiring process, marketing strategies, and investment decisions with data-driven insights.
Moreover, machine learning is going to be the key player in the healthcare sector. Cancer detection and diabetic retinopathy diagnosis using ML are already in a promising position. But what coming up is revolutionary. Robotic surgery tools are in development. They will have steady hands than humans to perform surgeries more accurately even in tighter places. And recently scientists at the University of Michigan were successful in giving amputees mind-controlled prosthetics using ML. They used millivolt signals from nerves to train algorithms and translate them into movements.
And ML is used in building sex robots too, not only for physical pleasures but also for mental relief. They will be like a real partner. You can talk about your problem with these robots. With your data already fed, they can understand, learn, and console you.
Humans always fear new technologies. There was a time when people were insanely afraid of automobiles. But today everyone owns at least a kind of automobile. It’s pretty common to be afraid of new things. Some are afraid that AI will take over the world. They are despising it. But sooner they will realize its importance and appreciate them. Humans will continue ruling the world as they used to be unless something natural happens.
References:
Charlotte Jee, 2020. An implant uses machine learning to give amputees control over prosthetic hands. [https://www.technologyreview.com/.../implant-machine.../]
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