Why AI is has become so popular?
- AI requires increased data volumes – tremendous data have been generated in the form of text, images, and videos
- Advanced Algorithms – developments in deep learning and machine learning algorithms
- Improvements in computing power and storage
- AI needs a lot of processing capacity due to the great amounts of "mathematics" needed to be handled. And the cost of processing have steadily gone down as a result of Moore´s law
- In addition to processing power, AI normally needs a lot of data, leading to e.g. big storage capacity of data needed. Due to Moore´s law, the storage cost has steadily gone down, too.·
History of AI:
Types of AI:
Artificial Intelligence is broadly categorized into three types based on the nature of work:
I. Narrow AI (ANI) / Weak AI:
Weak or Narrow AI refers to machines or software that is focused on one narrow and specific task, which is trained and programmed to perform to provide intelligent answers. Most of the development and achievements in AI that we are familiar with are in Narrow AI.
As per Arend Hintze - the Assistant Professor at Michigan State University, AI is categorized into four types:
1. Reactive Machines (RM):
RM does not have the ability to form memories, neither do they use past experiences to inform current decisions. Machines designed with a Reactive system and intelligence perceive the world directly and act on what they encounter or see. They do not have memory.
Ex. Google’s AlphaGo, IBM’s supercomputer Deep Blue. If interested, I recommend watching the documentary:
Garry Kasparov versus Deep Thought Documentary
AlphaGo - The Movie | Full Documentary
2. Limited Memory (LM):
LM systems have the ability to look into past experiences to inform future decisions.
Ex. Self Driving Car, image classification, machine translation, etc.. Currently, LM systems are widely used in business for automation, improving productivity and gaining predictive insights.
II. General AI (AGI) / Strong AI:
Strong AI or Artificial General Intelligence (AGI) has the ability to learn, solve, and perform any task that it is presented, without any human intervention. Applications and computers powered by Strong AI have the same accuracy level as humans, human-like cognitive abilities such as adaptability, thinking, learning, creating, deciding, etc.
3. Theory of Minds:
Future AI - Machines that understand emotions, infer intentions, and predict behavior. Researchers are deeply investing in turning it into reality though it is far from being achievable.
Researchers hope that machines developed with the concept of theory of mind will be able to relate to humans and perceive human intelligence and emotions, while understanding how it is affected by events and the environment.
III. Superhuman Intelligence (ASI):
Superhuman intelligence refers to the cognitive ability of machines that can do everything that humans can do or even more. Researchers are in dilemma, whether building ASI is harmful to society or beneficial one.
As said by Stephen Hawking “The development of full artificial intelligence (ASI) could spell the end of the human race."
Another great mind Elon Msk says, Artificial Intelligence Poses 'Existential Risk'
4. Self-Awareness:
Theory of Mind is limited to sci-fi and is yet to be a reality. However, self-awareness is an idea of AI that has the ability to understand its surroundings and will have a sense of self or ‘consciousness’ and use that information to further understand what other humans/ machines are feeling.
AI potential for business across the globe:
AI that describes a variety of technologies referring to the creation of intelligent machines that will have the ability to learn and solve problems. These include machine learning, computer vision, and natural language processing (NLP), voice processing, among others. The global survey report says the global AI software market is expected to grow approximately 154 percent year-on-year, reaching a forecast size of 22.6 billion U.S. dollars in 2020. Moreover, PwC’s Global Artificial Intelligence Study says $15.7tr potential contribution to the global economy by 2030 from AI. Industries across countries have invested huge and expecting 45% of total economic gains by 2030 that will come from product enhancements, stimulating consumer demand. This is because AI will drive greater product variety, with increased personalization, attractiveness, and affordability over time.
To map countries' success and leadership in the context of AI, let’s consider “AI maturity and digital activity in country” and “AI talent “ as parameters. Based on the global survey, top five countries in the race are:
1. China (China’s State Council’s promise to become a $150 billion AI Global leader by 2030)
2. United States (DARPA and IARPA are helping the country achieve success in the field of artificial intelligence.)
3. Japan (Like China, Japan has also created a council to focus on the development and commercialization of AI)
4. United Kingdom (Leader in AI and ranked fourth)
5. European Union (EU too holds a high ambition for AI and rank fifth)
