Two Types of A.I.: “Weak” Vs. “Strong”

PSMJ Resources, Inc.
Posted on: 05/01/24
Written by: PSMJ Resources, Inc.

A.I. comes in two major categories, narrow or weak A.I. and general or strong A.I. The latter currently exists largely in theory. 

Narrow or Weak A.I. is designed and trained for a specific task or set of tasks. It operates within a limited context and cannot perform tasks beyond its predefined capabilities. Virtual assistant programs like the iPhone’s Siri are examples of Weak A.I. Other models include image recognition software, and recommendation algorithms for social media and streaming networks. 

General or Strong A.I. refers to machines with the ability to apply intelligence to any problem, rather than being limited to a specific task. It is a more advanced form of A.I. that can understand, learn, and apply knowledge across diverse domains, similar to human intelligence. Most commonly called “artificial general intelligence” or AGI, it exists as more of a theoretical concept and has not been fully realized yet. 

Shane Legg, Google DeepMind’s co-founder and chief AGI scientist, told Time that he expects AGI to be developed by 2028. Other A.I. experts predict that AGI will become a reality within 5 to 20 years. 

Perhaps as a way to temper expectations, Time also noted that Herbert Simon, who won a Nobel Prize for economics and the Turing Award for computer science, predicted that “machines will be capable, within 20 years, of doing any work that a man can do.” That was in 1960. 

Clearly, nothing is guaranteed. As advanced as the recent (and continuing) chatbot and other machine-learning-based technologies have become, the consensus among experts is that they still fall short of AGI. 

In 2024, AGI exists only in works of fiction. Arnold Schwarzenegger’s character in The Terminator is an example of AGI. Though it had a single focus – kill Sarah Connors – it was able to “understand, learn and apply knowledge across diverse domains.” The Terminator is a character of fiction – for now. As A.I.-contributing technologies advance, we grow closer than ever to true AGI. 

Below is a graphic from technology information and advice website Lifewire (lifewire.com) that explains the differences between the weak/narrow and strong/general A.I. 

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A third category is sometimes included in this group – Artificial Superintelligence (ASI). This refers to a hypothetical form of A.I. that surpasses human intelligence in every aspect (presumably represented by Arnold Schwarzenegger’s “emotional” character in Terminator 2). Discussions of ASI revolve around the obvious ethical, safety and existential questions of building such a machine. And for the purposes of this book, that’s enough about that.

SO WHAT IS & ISN’T A.I.? 

In a 2020 article, ancient by technology standards but still pertinent, Mike Kaput of the Marketing Artificial Intelligence Institute wrote, “Artificial intelligence is a broad term. It encompasses a lot of different technologies. Some of these technologies are called machine learning, natural language processing (NLP), natural language generation (NLG), deep learning, and neural networks.” 

He continues, “Some commentators treat these concepts as interchangeable. They’re not. They refer to specific, but related, technologies. The term ‘artificial intelligence’ or ‘A.I.’ is an umbrella term to describe this suite of tools. Kind of like how the term ‘analytics’ or ‘business intelligence’ encompasses many technologies. Understanding this helps a lot of people start to wrap their heads around A.I. You pull back the curtain and see individual tools with real capabilities, not some singular magic technology that can do everything.” 

And there it is. A.I. as it exists today encompasses a range of technologies that simulate or replicate human intelligence to perform specific tasks. While it has made substantial strides in recent years, with 2023 being the pinnacle thus far, it is critical to understand A.I.’s limitations and to differentiate between the narrow degree of capabilities it currently offers and the theoretical concepts of general or “strong” A.I.

SIDE NOTES: “ A.I. IS NOT A TECHNOLOGY” 

A 2018 article in Forbes argues that, “Artificial intelligence is not a technology.” Author Kathleen Walch writes, “Asking the question whether or not some particular technology is or isn’t A.I. is missing the point. Artificial intelligence is the journey. It’s the quest for the intelligent machine. All the technologies we’ve developed on the route to that quest are things that are individually useful, but all together, have not yet gotten us to the goal. This is why it’s important to understand that artificial intelligence is not a technology, in much the same way that the Space Race is not a technology.” 

Walch adds, “The term artificial intelligence was coined in 1956 at a Dartmouth University summer conference. John McCarthy, celebrated A.I. researcher who pulled together the conference himself, said that A.I. doesn’t have a technology-specific meaning. In his words, ‘A.I. is the science and engineering of making intelligent machines.’ The creator himself saw A.I. as not the ends, but the means. A.I. is not a technology any more so than physics or civil engineering. The challenge is, like all sciences, there must be application to bring concept to reality.” 

Walch, Managing Partner & Principal Analyst at A.I. Focused Research and Advisory firm Cognilytica, continues, “It might be more helpful to think of A.I. as a goal. If A.I. is considered to be a collection of technologies, then you can argue all day about what is and what isn’t A.I. Are software robots A.I.? Are self-driving cars A.I.? Is computer vision A.I.? Is character recognition A.I.? If you think about it as technology then it’s always subject to disagreement and interpretation. However, if you think about it as a goal, or a quest, then it’s something we’re always striving to achieve, even if we aren’t quite there yet.” 

She concludes. “Forward thinking organizations and individuals understand that A.I. is not a technology. They don’t ask whether something they implemented is or isn’t A.I. Instead they ask what transformative effect that technology has. They ask what benefit they can realize from machines that can think and act as humans do. They ask how A.I. will represent opportunities to dramatically increase efficiency, reduce expenses, increase customer satisfaction, improve existing products and services, and create new business opportunities. Because at the end of the day, an organization itself is not about its technology, but its overall mission and objective. And just like those organizations, A.I. is not defined by technology, but by the overall objective.” 

Source: Forbes, “Artificial Intelligence is Not a Technology,” by Kathleen Walch, May 1, 2018, https://www.forbes.com/sites/cognitiveworld/2018/11/01/artificial-intelligence-is-not-a-technology/?sh=7c24bbf55dcb 

Steve Bennett, Director of Design Technology for 110-person architecture, strategic planning and data analytics firm Taylor Design, says, “In the early 2000s in Silicon Valley, everything had to have an “i” in front of it. Now it’s an “ A.I.” The companies have had the last year to put a marketing spin on A.I. and put it on everything. Some people are going to fall for it, but we have to take a step back and ask, ‘is this really A.I.?’ It matters and there are ramifications whether something is or isn’t A.I.” 

Chatbots are a good example. In its paper, “What is a Chatbot,” IBM says, “The terms chatbot, A.I. chatbot and virtual agent are often used interchangeably, which can cause confusion. While the technologies these terms refer to are closely related, subtle distinctions yield important differences in their respective capabilities.” 

The paper continues, “Chatbot is the most inclusive, catch-all term. Any software simulating human conversation, whether powered by traditional, rigid decision tree-style menu navigation or cutting edge conversational A.I., is a chatbot. Chatbots can be found across nearly any communication channel, from phone trees to social media to specific apps and websites.” 

Bennett says, “When I think of A.I., I think of a purpose-built A.I. system like Midjourney, which helps you create imaginary imagery. Or ChatGPT, which helps you create text-based imaginary things. Adobe Photoshop has an A.I. plug-in you can use to embed images with text-based prompts. Some people call their automated chat systems ‘A.I.’ when it’s not. You can actually chat with an A.I. chatbot, but a non-A.I. chatbot is usually the one that you don’t get an answer from, so you go around it and talk with a human.”

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