In 2017, Andrew Ng, one of the world’s most renowned computer scientists, stated that artificial intelligence is the electricity of the 21st century. Although some absent-minded may believe that it is a slightly exaggerated statement, the truth is that this discipline has great potential to transform all kinds of industries: health, education, entertainment, manufacturing, transportation, and the list goes on.
What is artificial intelligence?
Artificial Intelligence is the scientific field of computer science that focuses on developing systems that can mimic human intelligence. In other words, AI performs tasks that have some intellectual challenge, and that can iteratively improve based on the information they collect.
In general, an AI program is capable of analyzing large amounts of data (Big Data), identifying patterns and trends and, therefore, making predictions automatically. AI manifests itself in several forms. Some examples are:
- Chatbots: Through natural language processing, chatbots are applications that simulate and process conversations enabling humans to interact with digital devices. The main objective of its use is to make interaction with users more scalable and offer more efficient responses at any time of the day.
- Virtual assistants: This kind of applications respond to instructions and questions to help people complete tasks, whether it’s an Internet search or turning on an appliance.
- Recommendation engines: Thanks to AI, many services can provide on-the-spot recommendations based on previous searches or other user habits. The section «Our selection for you» of Netflix, for example, is based on this technology.
Regardless of its particular uses, when we address AI is much more about the development, the math’s, the processing power, and the data analysis behind it. Although AI seems to replace human work, its primary objective is to enhance it.
How does artificial intelligence work?
Artificial intelligence works from algorithms, which are mathematical learning capabilities, combined with large amounts of data to train those algorithms.
Machine learning automates the building of analytical models. Employs neural network, statistical, operations research, and physical methods to find hidden insights in data without being explicitly programmed so it knows where to look or what conclusions to draw.
Artificial intelligence types
AI can be categorized into three large groups. The narrow or weak AI, the robust or general AI and the Artificial Super Intelligence.
- Narrow AI
Artificial Narrow Intelligence (ANI), sometimes referred to as “weak artificial intelligence,” is a type of AI that is trained and focused on performing specific tasks.
Narrow artificial intelligence is behind most of the AI around us, including self-driving vehicles and personal digital assistants like Alexa or Siri. This is because, although it appears to be thinking for itself in real time, artificial intelligence is actually coordinating different narrow processes and making decisions within a limited range of previously defined options.
- General AI
General AI, also called robust AI, or «human-grade artificial intelligence,» refers to the ability of a computer system to have intelligence equivalent to or greater than that of humans. It’s the kind of artificial intelligence we often see in science fiction movies, where people interact with robots or programs that have conscious thoughts and act based on their own motives.
In theory, a computer system that has achieved artificial general intelligence could solve highly complex problems, be self-aware, and have the ability to make judgments in uncertain situations and plan for the future. It could even have creativity and imagination, with processing power infinitely greater than that of narrow artificial intelligence.
- Artificial super intelligence
The term artificial superintelligence, or ASI, refers to the point at which digital intelligence surpasses human intelligence in certain ways. It goes a step further than the previous two types by envisioning a world where the cognitive ability of a computer exceeds that of a human being.
Super intelligent machines can think in abstractions that are simply impossible for humans. This is due to the fact that the thinking capacity of the human brain is limited to billions of neurons.
In addition to replicating multifaceted human behavioral intelligence, this type of artificial intelligence focuses on the ability not only to interpret human emotions and experiences, but also to gain emotional understanding, beliefs, and desires of one’s own, as a result of their learning.
Although these last two types are still an aspiration and there are no practical examples of use, researchers are exploring alternatives and testing possible developments. Meanwhile, the future technological evolution brings numerous ethical dilemmas of various kinds: Who will determine the ethics that will guide an AI? Who will be held accountable for their decisions? How will the world of work change? Will AIs still be considered machines?
Can AI help businesses?
Leaving aside the problems that the future poses, the artificial intelligence that actually surrounds us today offers great opportunities for innovation in all industries.
In fact, companies around the world already use it in a wide variety of applications. Powered by various forms of machine learning, AI recognizes patterns in data to make predictions, identify trends, automate actions, and achieve significant business benefits. Some of its usages are:
- Customer experience: Customer expectations are higher than ever, expecting faster, easier-to-use, and personalized services from brands. AI has multiple utilities in this regard. For example, recommendation systems based on historical user data to offer more significant proposals, chatbots and other utilities aimed at forecasting purchasing trends, applications to improve customer segmentation, and identify browsing patterns in a Shopping environment.
- Image analysis: AI makes it possible to obtain meaningful information from digital images, videos and other visual inputs. This application can help companies to know the presence of their brand or prevent theft of intellectual property in the digital environment. It is also useful in photo tagging and classification, identity verification, or sentiment analysis of a face-based shopping experience.
- Automated stock trading: in order to optimize stock portfolios, AI-powered high-frequency trading platforms make thousands or even millions of trades per day without human intervention.
- Banks: in financial institutions, artificial intelligence techniques can be employed to identify which transactions are likely to be fraudulent, perform credit assessments, and automate data-intensive management tasks.
In short, artificial intelligence can transform all industries, but we must understand that it must be formed from large volumes of data. That means that any company that wants to design and train AI algorithms will need to have a strong and accurate data in the first place.
For this phase, companies today have solutions such as Conciliac’s, which allows centralizing, automating and standardizing all processes that involve data treating, such as integrations, reconciliations, validations, consolidations, extraction and transformation, among others.
If you want to know more, don’t hesitate to contact us.