What is Artificial Intelligence
We humans have been getting smarter for millennia. How has this happened? Instead of asking this question, we can find some answers using the term Artificial Intelligence.
AI comes from the Latin word Artificiality which means “play”. It really is so used today as a generic term for a whole range of things including pattern recognition, natural language processing, image recognition, mechanical operation, and many more, but primarily time-based (via computer systems).
Before we look at ways in which AI can help us, let’s look at how we define AI, so that we can also judge the quality of AI systems currently using this term and the new ways of using AI that are coming.
We need to make sure we are not too bogged down in definitions as we are starting to see a trend of AI built on a real name.
Science ancient times artificial intelligence has been an important buzzword. Microsoft Artificial Intelligence Lab answers “It’s all about money”, a trend shown by companies using AI-lab architectures for their main applications that include chatbots, chatbots, virtual assistants, computer systems, driverless cars, etc.
AI is just an abbreviation of Artificial Intelligence which means systems that can be given instructions and perform well. As with many emerging technologies, it is a continuous development process. Examples are IBM’s Watson, Apple’s Siri, computer systems that are able to identify anomalies in images to identify train fashions and alarm signals.
IBM Applied Artificial Intelligence
There is an interesting trend of AI implemented on big data. An AI code that can have hundreds of thousands or even millions of parameters, contains many machines that are needed to perform their set tasks.
Amazon’s Alexa for example recognizes all the commands of a user and understands what they are trying to say. As in Microsoft’s chatbot, which asks users what day of the week they were on last week. An AI system that has lots of parameters can really help you learn how to get a better idea of what works best for its’ context and better/more accurate results with a limited amount of data. This kind of (human language) understanding will allow for later steps into more advanced AI.
AI systems today provide slightly better performance when they are trained with much data than when trained on just the right data. The more data we train them on, the more accurate they become.
One of the most common ways of building a neural network is with mathematical equations. These equations are very similar to ones in human neurons which helps us understand the way neurons work. We don’t have enough neurons in our brain that will perform all the functions, a network trains itself on the inputs (training data) of each neuron and “attributes” (output data) for a neural network based on all the connections.
These connections help to make it decision-making process more accurate.
There are many other ways to build an AI system with better performance, one way is to use computer code with algorithms that look like the human brain and can provide you with very interesting new ways of combining them together to arrive at a more accurate output.
We believe AI can have a huge impact on some other aspects of our lives. We know that things can’t happen or happen faster if we don’t want them to happen, that’s why we sometimes put on investment protection. Algorithms in the natural world can be very intuitively (and in a short-term way) communicated. For example, you can decide to put a sensor in a tree (point) and click a button to inform someone.
You can talk about which sensor should be put in a tree (trigger) and click another button to activate it to see that sensor just detects that sensor that was placed closer to where the sensor from the tree was placed. This sensor is someone else’s sensor, which receives the signal from the tree and tells their agents.
So in the short term, we’re giving the tree different detectors that help to develop a bigger system. The tree’s agent tells its agents, the agent tells its agents, and so on and so on.
Because of this, we believe we could create the AI equivalent of Hedge Funds that help manage investments on your behalf, providing us with better performance and human-like intelligence.
The above is just a future scenario. This is where we would like to see an advanced AI system being developed.
IBM Applied Artificial Intelligence (AI) Professional Certificate
This program is sponsored by Pacific Lutheran University in collaboration with SkillUp Online.