What is AI?
Artificial Intelligence (AI) is no longer just a concept from science-fiction movies. It’s becoming more and more common in our daily lives. AI tools are being used to improve healthcare, solve traffic problems, and much more.
In this guide, we’ll explain what AI is and how it’s being used today. We’ll also share some of the most innovative and interesting use cases that you can find today.
A.I. is the ability of computers and machines to perform tasks that would normally require human intelligence. This includes using cognition, learning, and behavior that is comparable to that of humans. AI is a branch of science that combines computer science and substantial datasets to help us solve common problems across a broad spectrum of our lives.
How A.I. Works.
Artificial intelligence (AI) uses machine learning and other logic-based techniques to analyze events, automate activities, and carry out actions with little to no human involvement. AI systems combine large data sets with intelligent processing algorithms and process many jobs exceptionally quickly. With the help of key tools like “machine learning” and “deep learning,” artificial intelligence (AI) can do tasks almost as well as the human brain.
Machine learning uses algorithms to interpret data, learn from that data, and make informed decisions based on what it has learned. While Deep learning organizes algorithms into layers to produce an “artificial neural network” capable of independent learning and deductive reasoning. Deep learning is a subset of machine learning
Examples of how A.I. Works Today.
Everyone knows that A.I. is used in ChatGPT, but there are many other services using it as well, such as those below.
- Phones with FaceID: AI is used to recognize your face and unlock your phone.
- Google’s search engine’s formula: Google uses AI to improve its search engine. For example, it uses “neural matching” to better understand the meaning of words and phrases..
- The Netflix recommendation engine: Netflix uses AI to recommend movies and TV shows based on what you’ve watched before.
- Ride-hailing services like Uber and digital Assistants like Alexa and Siri: AI is used to match drivers with riders and to understand voice commands. And Alexa and Siri can also handle voice commands.
- Smart home technologies: AI is used to control smart home devices like thermostats, lights, and security systems.
- Banking: AI is used to detect fraud and to make personalized recommendations for financial products.
- Social media like Facebook etc.: AI is used for content moderation, image recognition, and personalized advertising.
- Sending messages or emails: AI is used for predictive text and auto-correct.
The History of A.I.
In the 1700s and afterwards, philosophers, mathematicians, and logicians started thinking about how machines could think like humans. They wondered if machines could be built to think and learn like people. These ideas eventually led to the invention of the programmable digital computer, the Atanasoff Berry Computer (ABC) in the 1940s.
Nearly a decade later Alan Turing, a mathematician among other things, proposed a test that measured a machine’s ability to replicate human actions to a degree that was indistinguishable from human behavior. This led to John McCarthy, a cognitive and computer scientist from the United States developing the computer programming language LISP in 1958. Arguably the first speech replication computer tool. He was also the first person who used the term artificial intelligence in 1955.
Early Developments of A.I.
AI research started in the mid-20th century by Alan Mathison Turing. In 1943, Warren McCulloch and Walter Pitts proposed a model of artificial neurons which is now recognized as AI. And In 1949, Donald Hebb demonstrated an updating rule for modifying the connection strength between neurons. His rule is now called Hebbian learning. These are recognized as early developments of A.I.
If you wish to find out more about “early developments of A.I” please look up Britannica.com or….. Harvard University.
Key Milestones of A.I.
- 1637: Philosopher and scientist Rene Descartes proposed that one-day machines could think and make decisions like human beings.
- 1956: The Dartmouth Conference was held, which is considered to be the birthplace of AI as a field of study.
- 1966: ELIZA was created, which was one of the first programs to use natural language processing.
- 1980: XCON was developed, which was one of the first AI systems to be used in real-world applications.
- 1997: Deep Blue defeated world chess champion Garry Kasparov.
- 2011: IBM’s Watson won Jeopardy.
- 2012: AI learned to recognize cats.
- 2015: Google’s DeepMind developed an AI system that could recognize images better than humans. The system was able to identify objects in photos and videos with a higher degree of accuracy than humans. This was a significant milestone in the development of AI and demonstrated the potential for AI to surpass human capabilities in certain areas.
I have copied and pasted this directly from ChatGPT and find it somewhat funny and scary at the same time. Especially at the end when “Chat” writes “…and demonstrated the potential for A.I. to surpass human capabilities in certain areas. I am not a huge fan of Elon Musk, However, I do believe that we have to keep a very tight rein on this technology.
The Different Types of A.I.
According to Forbes, there are four types of AI or AI-based systems:
Reactive machines;
These are the oldest types of AI systems that are very limited in what they can do. They copy how the human brain responds to different things. However, these machines can’t remember things they have learned before, so they can’t use experiences to help them with what they’re doing now.
Limited memory machines;
In addition to possessing the characteristics of fully reactive machines, limited memory machines also have the ability to learn from past data and make judgments. Nearly all existing applications that we know of come under this category of AI.
Theory of mind;
The previous two types of AI are reactive machines and limited memory machines. The next two types of AI are still in the concept or work-in-progress stage. Theory of mind AI is the next level of AI systems that researchers are currently working on. A theory of mind-level AI will be able to better understand the entities it is interacting with by discerning their needs, emotions, beliefs, and thought processes.
Self-aware;
Self-aware AI is the final stage of AI development which currently exists only hypothetically. It is an AI that has evolved to be so similar to the human brain that it has developed self-awareness.
Recent Advances in A.I.
Here is possibly an easy way to show the rapid advancement of A.I over the last 8 years without going into every aspect of A.I. itself.
Below you will see pictures starting with a fairly primitive picture of a woman with a pixelated face in black and white. Only 3 years later computers were able to create pictures that looked so real, it was difficult to tell if they were photographs or not.
The capacity of AI systems has increased dramatically in recent years. These more recent models have expanded their ability to text-to-image synthesis based on virtually any prompt, whereas earlier systems were mostly focused on producing images of faces.
The illustration in the lower right corner demonstrates that even the trickiest suggestions, such as “A Pomeranian is seated on the King’s throne wearing a crown with two tiger soldiers standing next to the throne” are transformed into photorealistic pictures In a matter of seconds,
This shows the rapid advancement of A.I over a short period of time. Also, one of the “newer” tools is the use of A.I. in holograms.Tensor holography, a novel technique that may be used on a smartphone, may make it possible to create holograms for use in virtual reality, 3D printing, medical imaging, and other applications.
You can also read about the latest news and launches in the A.I field at Tech Radar, a website that provides up-to-date news about the latest things in Technology.
Check it out here at “Tech Radar, what is A.I., Latest news and launches”
The Benefits of A.I.
The advantages of artificial intelligence are numerous. Increased production, profits, efficiency, precision, and speed are a few of the common advantages. Data analysis, automation, forecasting, and planning can all benefit from AI. AI has the potential to improve people’s life, education, and employment prospects. AI can improve precision while reducing human error.
AI can lessen the tedium associated with numerous job-related duties. In every employment, repetitive, boring duties are the scourge of many human workers. Even while repetition can make humans more perfect in their job, computer automation is still the finest and most affordable solution for repetitive activities.
Real-Life Scenarios.
In practical applications, AI can aid physicians in making more accurate diagnoses and better treatment strategies. Compared to human doctors, AI can properly detect diseases in 87% of cases as opposed to 86%. Deep learning systems had a 93% specificity compared to humans’ 91%. Radiologists can also benefit from AI medical diagnosis systems by having access to multiple points of view, lowering the likelihood of misunderstandings, and improving overall diagnostic accuracy.
New Opportunities.
Rather than the doom and gloom espoused by so many, there are many more opportunities for the creation of new jobs, prompt engineers being just one. Or so it is reported.
AI can help create new opportunities in various fields. AI-powered assistants like Alexa, Siri, and Google Assistant are good examples. Autonomous checkouts are another possible future for retail. No-Code AI Platforms and Generative Adversarial Networks are other examples of new opportunities presented by AI. AI can also create 58 million new jobs by 2022. The growth of artificial intelligence could create 58 million net new jobs in the next few years.( 58 million new jobs, Forbes)
In some supermarkets, such as Amazon Go stores operated by Amazon, there is no point of sale at all. Customers are tracked in the supermarket. Thanks to networking with the shelves, an algorithm calculates which items are in the customer’s shopping basket, and the shelves report their fill level automatically so that supplies can be replenished in a timely manner.
The payment process is completed via the customer’s Amazon account. In this way, queues are completely avoided with the help of artificial intelligence.
New Job Opportunities.
It is difficult to ‘crystal ball” what specific jobs will appear. But from the research I have done, overall the percentage of work carried out by A.I. and humans may adversely affect the numbers of people employed. Thus, it is important to be prepared for any possible changes.
Here are the type of new jobs that have been predicted. The World Economic Forum identified the top emerging roles as experts in AI and machine learning, data scientists and analysts, and experts in digital transformation. Artificial intelligence (AI) engineers, machine learning engineers, data engineers, robotics engineers, software engineers, data scientists, user experience designers, researchers, business intelligence developers, and prosthetists are just a few of the occupations that produce AI. Additionally, there are new professions in business and technology that are influenced by AI, such as trainers, explainers, and sustainers. And you might just be on a retainer!
The Limitations of A.I.
Lack of Creativity and Intuition.
AI can only do what it has been programmed to do. For example, an AI model that has been trained to recognize cats will not be able to recognize dogs unless it has been specifically programmed to do so. Similarly, an AI model that has been trained to play chess will not be able to play checkers unless it has been specifically programmed to do so.
Dependence on Prior Data.
AI models are only as good as the data used to train them. For example, if an AI model is trained on biased data, it will be biased as well. This can lead to problems such as discrimination against certain groups of people. One example of this is facial recognition technology, which has been shown to be less accurate for people with darker skin tones.
Ethical Concerns.
There are many ethical concerns surrounding AI. One example is the potential for AI to be used for malicious purposes. For example, AI could be used to create deepfakes or to automate cyberattacks. Another concern is the potential for AI to perpetuate existing biases. For example, if an AI model is trained on data that is biased against women or people of color, it will be biased against them as well.
Final Thoughts.
I believe we are at the start of another “Business Revolution”, we started with the industrial revolution, And we are coming up to the “Fourth Industrial Revolution”. Over the next decade, we will be undergoing a paradigm shift in the way we do business. And if you don’t, won’t, or can’t adapt you will be left behind.
Love it or loathe it, if you don’t “change your script” or the way you do business you will be left behind. Much like what has happened through every technological surge forward. In the 1960s and even the 1970s and 1980’s how many people could say they were comfortable with computers? Now we have to learn how to use the new tools provided by A.I.
Forbes: The Fourth Industrial Revolution.
Stephen Hey
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