Artificial Intelligence
The intent here is to briefly explain artificial intelligence (AI) for the common folk like me.
Before we start, let’s understand that AI is also something called machine learning (ML).
AI is a computer algorithm. It may surprise us that AI is used by most of us in some way or another on a regular basis.
AI systems work by combining massive amounts of data with algorithms that repetitively process and learn from the data analyzed. AI never needs a break, so it can do hundreds, thousands, or even millions of tasks very quickly. It can learn a lot in a short amount of time and become very good at whatever it’s being trained to do.
For example, when you ask your smartphone assistant a question or when you get recommendations for products to buy on Amazon, you’re using an AI system.
Another example. We all know about facial recognition. It’s used extensively by law enforcement. Faces are fed into a computer along with other data about the individuals to create a database. Subsequently a face can be fed into that computer and very quickly it determines whether that face is in the database.
AI systems are also being used for more complex tasks like driverless cars and diagnosing cancer.
And it’s a growing field of study and application.
There are two main types of AI/machine learning:
Supervised learning is when the inputs are known, and the outputs are defined. For example, we might put horses and kangaroos into the computer forming the database and we want the algorithm to learn to label horse or kangaroo in the output.
Unsupervised learning is when we input horses, kangaroos, alligators, snakes and trees and we ask the computer to give us some structure or pattern to the data without any defined output. We want the algorithm to learn what that structure or pattern might be without defining it.
Machine learning is a key part of AI, and it’s what allows AI systems to get better and better at whatever they’re being trained to do.
Natural language processing is a way AI can communicate with humans. Verbalize any language and an algorithm can verbally translate it into a foreign language or even write the foreign language out for us. You likely already know students are using it to write papers for a class.
Cognitive computing is a way for AI to reason, make decisions, and solve problems like humans.
The applications of AI to healthcare are already extensive in the areas of diagnosis, treatment, and research – and communicating with the patient.
It all sounds pretty understandable to this point, right? But I cite a quote from an IBM website on AI:
“As AI becomes more advanced, humans are challenged to comprehend and retrace how the algorithm came to a result. The whole calculation process is turned into what is commonly referred to as a “black box” that is impossible to interpret. These black box models are created directly from the data. And, not even the engineers or data scientists who create the algorithm can understand or explain what exactly is happening inside them or how the AI algorithm arrived at a specific result.”
Now, if IBM scientists don’t know exactly how or why some AI algorithms work, it’s going to be beyond me in this piece. Furthermore, it’s not far-fetched to think that soon AI will be able to write its own algorithms.
This may not be a good analogy, but what comes to mind is the 1818 Mary Shelly novel Frankenstein, considered to be the first science fiction novel ever written. In it, Dr. Frankenstein creates a creature in an unorthodox scientific experiment in which he tries to cheat death. During and after piecing together the creature he really doesn’t know what it will do once it comes to life. In that vein apparently nobody really knows what AI can and will do as that scientific experiment advances in applications. Will AI be smarter than its human creators? Will machine learning eventually replace the role of humans as the smartest creatures on earth?
Recently a group of prominent computer scientists and other tech industry notables such as Elon Musk and Apple co-founder Steve Wozniak called for a 6-month pause to consider the risks.
That admonition was triggered by a San Francisco startup called OpenAI. It released an AI program called GPT-4. That program, ChatGPT, is a more advanced version of AI which in turn triggered companies like Microsoft and Google to unveil similar applications.
In other words, the race is on – which prompted the latest warning and call for a pause. The group referred to warns that AI systems with “human-competitive intelligence can pose profound risks to society and humanity” — from flooding the internet with disinformation and automating away jobs, to more catastrophic future risks out of the realms of science fiction.
AI may change everything. In some areas of knowledge, it’s already smarter than humans.
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Have a great and prosperous week.
Hug somebody.
References:
https://abcnews.go.com/Business/wireStory/musk-scientists-call-halt-ai-race-sparked-chatgpt-98208068
SPIDER Bites
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Even if the House passes the sweeping immigration bill introduced last week, its chances in the Senate are nil. A record 3.3 million illegals have entered the country since the Biden administration took over a little over 2 years ago.
CA’s ban on gas appliances was overturned by the Ninth US Court of Appeals last week. There’s at least some sanity left in that state.
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President Biden has promised to veto the bill passed in the House last week blocking transgender girls from competing in women’s sports.
Former acting CIA Director Mike Morell told the House Judiciary Committee that Antony Blinken, now the secretary of state, was the Biden campaign official who asked him to organize the 50 signatures to say the allegations against Hunter Biden’s laptop were Russian misinformation.