Light & Energy, whenever you switch on the lights at home, does it involve you to help the bulb enlighten? Once the switch has been turned on by “you” it automatically starts to enlighten itself via the “physical” processes that have been “programmed” into the bulb. This is an example of a semi-automated activity. What if it is the case that movement sensors turn on the lights at home instead of “you”? Then we can call it an automated activity. This is what semi-automation and automation are like.
Now we can start explaining AI. The term AI means Artificial Intelligence, artificial because it is programmed/made by humans and intelligence because it is at least capable to make an analysis and decisions without the involvement of humans. Humans haven’t called it like this, but it wouldn’t have been strange if we called it Automated Intelligence instead of Artificial Intelligence, because the AI entity automatically uses programmed intellectual capacities to perform certain tasks without involving human interaction.
Let us alter our last example in a way that AI is implemented. We didn’t have to turn on the lights anymore ourselves when something is automated, but what if you arrive at home at night and there is a camera placed in your door that is capable of face recognition and ensures that when you come home a voice is welcoming you and asks you what light settings you prefer.
- The first algorithm programmed by developers in this example is face recognition which enables the AI to recognize your face with a camera, thereby it knows what person to welcome, and also to gain access to the data of the individual in question about favourite light settings, etc.
- The second algorithm that has been programmed is speech recognition, allowing a user to have conversations with the AI and is able to ask it to execute specific tasks like dimming the light. You might recognize this when you have a luxury car like the latest released Mercedes’.
The establishment of shared theoretical frameworks, combined with the availability of data and processing power, has yielded remarkable successes in various component tasks such as speech recognition, image classification, autonomous vehicles, machine translation, legged locomotion, and question-answering systems.
As capabilities in these areas and others cross the threshold from laboratory research to economically valuable technologies, a virtuous cycle takes hold whereby even small improvements in performance are worth large sums of money, prompting greater investments in research. There is now a broad consensus that AI research is progressing steadily, and that its impact on society is likely to increase…. Because of the great potential of AI, it is important to research how to reap its benefits while avoiding potential pitfalls.
~ Stephen Hawking~
Try now to see if you can have a clear overview of the evolution of technologies (“physical” programming > “physical” programming + computer programming > Artificial Intelligence) that resulted in the establishment of AI.
If you succeed in having ……….. you might see like me that this is a piece of very effective and innovative technology that has so many possible use cases.
Disappointingly there are many obstructions nowadays that make it difficult for most companies and individuals to successfully program AI algorithms in order to implement this technology in products and/or services.
Mainly because sharing and/or selling AI algorithms and research is very uncommon nowadays, plus the fact that developing it from scratch consumes large amounts of time and money; therefore it is not lucrative enough for many businesses and individuals to start developing AI.
Most of the leading companies in AI technology like Tesla and Google, specifically develop AI for their products and keep all of their research and algorithms for themselves, preventing others to leverage their innovations.
This is going to change significantly with a business entity like Effect.ai, a company that offers an innovative easy (UI) to use AI algorithm training, trading, and computational power platform. Striving to solve most of the big obstructions in the AI industry of which it is expected to be worth 15.7 trillion dollars by 2030.