Narrow AI is created to solve one given problem, for example, a chatbot. Artificial general intelligence (AGI) is a theoretical application of generalized artificial intelligence into any domain, solving any problem that requires AI.
What is Narrow AI?
Artificial Narrow Intelligence (ANI), sometimes known as "weak AI", refers to any AI that can outperform a human in a narrowly defined and structured task. It is designed to perform a single function like an internet search, face recognition, or speech detection under various constraints and limitations. It is the constraints that lead people to refer to these functions as ‘narrow’ or ‘weak’.Applications of ANI are not thinking for themselves but simulating human behavior based on a set of rules, parameters, and contexts that they are trained with. Some of the most common narrow AI techniques are machine learning, natural language processing, and computer vision.
Examples of Narrow AI
Here are a few Narrow AI examples that perfectly illustrate how it's leveraged today’s tech.
The benefits of Narrow AI
Every minor success in narrow AI is typically a stepping stone towards Artificial General Intelligence (AGI). We will break narrow AI into three core benefits.
1. Productivity and efficiency
The news often cites AI as being a catalyst to large-scale redundancies for low-skilled workers. However, although there could be some short-term job losses, the objective of AI is to augment the roles of people rather than cutting them out completely. For example, chatbots are not being developed to replace traditional human customer service. They handle basic queries to allow skilled humans to deal with the more complex or sensitive issues and not waste their time with mundane work.
2. Smarter decision making
AI can analyze trends to help companies make better strategic decisions. Algorithms are unbiased (as long as trained correctly) and devoid of the emotions that can often inhibit humans from making the correct decision.
3. Better customer experiences
Narrow AI solutions such as chatbots, recommender systems, and intelligent searches can significantly enhance the customer experience. Everything is fully personalized to the user, making brands, products, and services more relevant than ever.
Although the solutions and applications of narrow AI are exciting and transforming lives, machines cannot yet think strategically and make independent decisions. This is where AGI comes onto the scene.
What is General AI (AGI)?
In simple terms, Narrow AI is where we have been, and General AI is where we want to head towards. Artificial General Intelligence is known as "strong AI" and allows machines to apply knowledge and skills in different contexts.
Where ANI applications can run single, automated, and repetitive tasks, the objective of AGI is to create machines that can reason and think just like a human is capable of doing. General AI is where we are heading but still in its very nascent stages.
The human brain is incredibly complex, and it's not yet possible to create models that replicate that biological network's interconnections. However, more advanced fields such as natural language processing and computer vision are closing the gap between ANI and AGI.
AGI solves many of the problems associated with ANI. For example, where ANI focuses on a single task, the performance of algorithms can degrade with slight changes as it is only programmed to achieve its goal without unintended actions. If you ask ANI to find a cure for kidney failure but then offer photos of the lungs, it won't adapt. Here are a few examples of AGI in use.
Where we're headed – artificial superintelligence
Artificial Superintelligence (ASI) would be capable of outperforming humans. As we discussed early, there are both optimists that focus on the opportunities of the technology and those who fear it could result in disaster for humanity.
If we look at the predictions of AI entrepreneurs as to when we will reach a singularity, the majority are between 20 and 30 years away:
Louis Rosenberg – computer scientist and entrepreneur – 2030
Ray Kurzweil – computer scientist – 2045
Jurgen Schmidhuber – co-founder of NNAISENSE – 2050
While they could be correct, you should remember that in 1965, AI pioneer Herbert A. Simon predicted singularity within 20 years, and in 1980 Japan's Fifth Generation Computer had a ten-year timeline to carry out goals associated with AGI. Although there is greater knowledge today than 50 or 60 years ago, nobody can truly predict when we will have artificial superintelligence.