Difference between ANI and AGI, or why we should not fear AI taking over the world (yet)

18

October

2019

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As AI makes a lot of technological advances possible, it leaves some people in fears of clever robots coming to overtake humanity anytime soon. However, this misconception is a result of misinformation about the AI terms and their corresponding technological progress. 

AI is divided into three areas: Artificial Narrow Intelligence (ANI), Artificial General Intelligence (AGI), and Artificial Super Intelligence (ASI). 

  • ANI – ability to mimic human intelligence to a narrow set of parameters
  • AGI – ability to mimic human intelligence indistinguishable from a human
  • ASI – ability to surpass human intelligence

Despite the multitude of AI innovations and technological breakthroughs, most of the progress in AI is attributed to ANI (Bhatia, 2018). Examples of ANI include voice recognition systems, self-driving vehicles, spam filter, recommendation systems of Google, Amazon or Netflix, etc. And thus, ANI is often called “one-trick ponies”, since they only work within a limited set of parameters. 

AGI, on the other hand, represents a machine’s capacity to learn and understand any tasks a human can, and thus, is often called “human-like AI”. For decades researches have been claiming that AGI development is right around the corner but with every passing decade, they were proven wrong (Dickson, 2017). One of the popular approaches for AGI development is brain emulation, which is a process of building an analogue of the entire human brain into a computer system that will be able to simulate its activities similar to a human (Wikipedia.org, n.d.). However, the brain is a very complex system and we have insufficient understanding of higher cognitive processes in order to successfully build a model of it. 

Overall, slow development in AGI can be attributed to many reasons. First of all, there are many views on how AGI is supposed to mimic human intelligence, and how to test it. Secondly, we still do not entirely understand how AI works. Also, researchers face conceptual limitations as AI requires understanding of multitude of areas. Furthermore, investments required for AGI development are substantial, and companies prefer to invest in ANI as its outcomes are more predictable and generally profitable. 

So, at the moment, ANI is the ultimate AI and AGI and ASI are only existing as part of Sci-Fi. Overall, the predictions of the progress of AGI vary. Some researchers claim it will take 30 years, some of them tell it will take about 100 years, while some claim that it might never come true (Dickson, 2017). 

 

References 

Bhatia, R. (2018). AGI vs ANI & Understanding The Path Towards Machine Intelligence. [online] Analytics India Magazine. Available at: https://analyticsindiamag.com/agi-vs-ani-understanding-the-path-towards-machine-intelligence/ [Accessed 18 Oct. 2019].

Dickson, B. (2017). What is Narrow, General and Super Artificial Intelligence. [online] TechTalks. Available at: https://bdtechtalks.com/2017/05/12/what-is-narrow-general-and-super-artificial-intelligence/ [Accessed 18 Oct. 2019].

Wikipedia.org. (n.d.). Artificial general intelligence. [online] Available at: https://en.wikipedia.org/wiki/Artificial_general_intelligence [Accessed 18 Oct. 2019].

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NIke’s SNKRS App: Driving Sales via Digital Community

18

October

2019

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After the recent decline in sales of Nike, the company decided to change its strategy by focussing its distribution on direct-to-consumer channels (Karwatka, 2018). This has proven to be a successful strategy as digital commerce sales went up 35% for 2019 fiscal year (Nike News, 2019). By establishing a direct relationship with the customers, and building emotional consumer experiences, Nike creates a loyal customer base that drives up the sales.  

At the moment, Nike owns several distribution channels: physical stores, its website, and apps – Nike+ and SNKRS. SNKRS app represents a digital platform centered around sneakers community. It is not just another digital store, but a platform that offers insider access and content about the latest sneakers. According to Ron Faris, CEO of s23nyc, the studio behind the SNKRS app, the digital community consists of 20% of Hyperbeasts, people that are extremely knowledgeable and fanatical about the community, and 80% of Styleseekers who are interested to learn more (The Next Web, 2018). And the key to driving a digital community and creating a powerful social network is to make those that have the most knowledge to share with those who have the least. 

In the case of SNKRS,  it offers consumers a platform to share their enthusiasm for Nike shoes, and creates immersive experiences for a chance to access limited edition styles. It creates a digital community of people that are crazy about sneakers, and uses this community to share and drive sales and engagement better than any advertising campaign as it allows to scale up without much investment. 

In order to energize such a community and create virality, the app is based upon three components: product, story and experience (The Next Web, 2018). By providing its key product, high-end shoes that are surrounded by a folklore story through a special and unique experience, it can make customers very emotional, enticing them to share and grow the community by means of which the product sells through. 

For sneaker community, the experience of buying sneakers as is important as sneakers themselves (The Next Web, 2018). Thus, another component of SNKRS’ strategy is gamification of the purchasing process. The company uses technology, in particular augmented reality, to revolutionize the buying experience by creating a sense of competitiveness fuelled by the adrenaline. For example, SNKRS Stash is campaign that allows users to purchase limited edition sneakers only from a certain location in their city (Karwatka, 2019). With this feature, online shopping can reach another level as virtually everyone and everything can become a Nike store: a poster in a metro, a menu in a restaurant or a concert of a celebrity. 

Thus, Nike is redefining online shopping by engaging with customers directly and creating emotional experiences through the use of technology. 

 

References:

Karwatka, T. (2018). Nike just shaped the future of retail with mobile-first commerce. [online] Divante.com. Available at: https://divante.com/blog/nike-just-shaped-future-retail-mobile-first-commerce/ [Accessed 17 Oct. 2019].

Nike News. (2019). NIKE, Inc. Reports Fiscal 2019 Fourth Quarter and Full Year Results. [online] Available at: https://news.nike.com/news/nike-inc-reports-fiscal-2019-fourth-quarter-and-full-year-results [Accessed 17 Oct. 2019].

The Next Web. (2018). Ron Faris (Nike) on The future of retail and digital community | TNW Conference 2018. [online] Available at: https://www.youtube.com/watch?v=JXLwzm2292U [Accessed 17 Oct. 2019]

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