Artificial Intelligence

Here's How Narrow AI is Paving a Path Towards Artificial General Intelligence (AGI)

Narrow (weak) AI is designed to perform a narrow task
Here's How Narrow AI is Paving a Path Towards Artificial General Intelligence (AGI)
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Managing Partner, EVC Ventures
4 min read
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From Siri to self-driving cars, artificial intelligence (AI) is advancing swiftly, moving into different landscapes and industries which has the vision to get things done faster. While science fiction usually depicts AI as robots with human-like qualities, it actually denotes a much bigger idea towards technology than what we can fathom. It can encompass anything from Google's search algorithms to IBM's Watson to autonomous weapons.

The Chronicle of Narrow AI

We all are aware that artificial intelligence is commonly known for narrow (weak)AI, in which it is designed to perform a narrow task, for instance, facial recognition, internet searches or just driving a car. However, the long-term goal of numerous researchers is to create something more concrete such as Artificial general intelligence (AGI or solid AI). While narrow AI may outpace us at whatever its specific task is, like playing chess or explaining equations, AGI would outperform people at every cognitive task.

Source: Gartner

Looking at these patterns raise a wide range of questions. What will happen to AI when it achieves the peak of productivity? What does that mean for you and me as entrepreneurs, marketers, engineers, and designers?

With more than 1,000 startups jumping on the bandwagon, preparing to pivot themselves as AI organizations, it is a big risk to place a bet on the current year leading to the rundown of mega-trends, in every one of its flavors and forms. Yet, before you expel this as hypothetical, consider that the rise of AI, specifically weak or narrow AI, is additionally inseparably linked with the development of big data.

Where Is Narrow AI?

Doubting that all AI is about frameworks designed to autonomously learn new tasks, adjust to changing conditions and outmaneuver their makers at last, skims over the numerous critical contrasts between the classic AI (the one motion pictures are made of) and its more than one dozen sub-disciplines.

Narrow AI Can Be Witnessed In:

• Self-driving cars that learn how to drive like Google and Uber cars, which as of now exist

• Recognizing your face at your nearby bank office to help you with a more personal experience

• Filling in your tax form for you, in view of all your financial information

• A bot that will book your flights and hotels for you, in view of your previous preferences

• Being your virtual planning right hand to manage your logbook and gatherings

• Making a personal music playlist for you that fits your exercises routine for the day etc.

These AI subsets, which may run on voice recognition and understanding of common dialects, such as individual helpers like Siri and Cortana, can also help with machine learning and deep learning and has the fundamental quality to grasp huge analytics and structural information intended where the action and opportunity exists.

The Bottom Line Is

It’s the volatile rate of data evolution that creates the prerequisite for narrow AI. Adding to it is the recent avalanche of user-generated content - the nearly 300,000 tweets, 220,000 Instagram posts, 72 hours of YouTube video content and the 2.5 million pieces of content shared by Facebook users every single minute that businesses must monitor and acknowledge — and it’s clear that no organization (or human) can cope without the aid of narrow AI.

Are you as fascinated as I am about AI and other emerging technologies, here’s are few books, about AI, that inspired me - The Inevitable by Kevin Kelly, The Emotion Machine by Marvin Minsky, Superintelligence by Nick Bostrom, Machine Learning: A Probabilistic Perspective by Kevin Murphy, Artificial Intelligence - A Modern Approach by Stuart Russel and Peter Norvig.

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