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Who Will Make Money from AI: The Gold Rush


By Ankit Dhandhania

 

Welcome to the Artificial Intelligence gold rush!

Today we are experiencing another gold rush in Artificial Intelligence. In

today’s world billions of dollars are spend on start-ups across every imaginable

business. Amazon, Google and Microsoft are some companies who is in

heavyweight fight investing over 25 billion dollars in artificial intelligence.

AI is everywhere. From billions of searches on Google to the new iPhone in the

market which uses face recognition to get an answer from Alexa. Media stories

on how AI is helping doctor to diagnose the diseases, farmers are able to

predict crop yields and market target and to retain customers are coming up

daily on there channels and newspapers. Artificial intelligence and machine

learning will be woven into fabric of the society. But as the question who will

find gold in gold rush? And who will hit pay dirt?

As I started thinking that Who is going to win the gold in gold rush, I ended up

with 4 questions Artificial intelligence in facets. AI in Industries, AI in business

and in chip making


1) Artificial intelligence in its many forms and facets, nowadays very large

number of companies are somehow involved in Artificial intelligence in

their application or services. But AI is a broad term which describes

applications when a machine performs cognitive functions and helping

in problem solving. When speaking about AI it has only two main

approaches Machine Learning and Deep Learning.


Machine learning includes classical algorithm for various kind of task such as

clustering, classification or regression. Whereas Deep learning is a young field

which includes neural networks which are produced to solve classical as well as

advanced tasks such as language generation and image recognition. If the

company wants to incorporate AI in their services or product deep learning will

be helpful.


2) Artificial Intelligence in Industries: - The total annual value of AI

potential across 23 industries and 10 business function in global

economy is 3.5 trillion dollars and 5.8 trillion dollars. This constitutes 40

percent of total annual value of the AI field. There is a wealth to new AI

powered start-ups providing solutions to cooperate uses in financial,

automotive, agriculture, legal and industrial sectors.


Many start-ups are providing valuable points and solutions and they can be

successful in their objective if they have access to 4 things. 1) They should have large data training sets. 2) they should have domain knowledge that gives them deep insights into opportunity. 3) they should have deep pool of talent around Artificial Intelligence. 4) there should be enough capital to fund the growth.


Start-ups that are doing well in their business generally speaks about ROI,

Business Efficiency and corporate language. In the form well developed

market plans.

3) Business Function: - It shows the value of potential of AI in comparison

to value potential of classification analytics across nine different

business functions.


When speaking about business functions there are mainly 3 opportunities in

the field AI field 1) Marketing, 2) Supply Chain management and

manufacturing.


a) Marketing in AI can help business in making better marketing decisions

and lead customer to your brand. Technology has developed so much

that it can transform are job as marketers. By doing this, they are giving

themselves a multi- year head start on their peers who are still afraid of

exploring AI. Whatever the reason, brands that don’t find smarter ways

to do their marketing will be left in the dust by their competitors that

do.


b) Supply chain: - AI in supply chain is involving about leveraging artificial

intelligence as process of supply chain. AI is operational processes by

interpreting large number of historical data, such as a supply shortage or

surplus. Supply chain improvements have direct impacts on our day to

day life. Operational efficiencies in supply chain are responsible for

reduction in cost to serve us all. It helps maintain current prices for the

product we love to buy.


c) Manufacturing: - Manufactures face lots of problem while reducing the

costs while continuing to deliver the products with high quality services.

Manufactures are taking an active approach to streamline operations.

Companies that are using AI are enjoying benefits of improved efficiency

and decrease downtime while maintaining customer satisfaction.


4) Chip makers: - Even there is falling in price of chips the demand is rising

faster. AI and machine learning with massive with datasets and its

trillions of vector calculations has a ferocious and insatiable appetite.


It is clear that the cost of designing and manufacturing chips the sustaining

a position as a chip leader is very high. It requires a deep pocket and a

team of silicon and software engineers. This means that there will be very

few new winners. Just like gold rush days those who provide the cheapest

and most widely used will make a money.

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