AI, the key frontier of Digital Transformation
What is AI? While the word AI is used for Artificial intelligence; there is nothing artificial about it. In my book, the best definition of AI, is Augmented intelligence, Added Intelligence, and Advanced intelligence, when added to normal human intelligence. Most of this added intelligence comes from data. That is why it is also called Machine Learning (ML) and sometimes AI and ML are used interchangeably.
We live in a data-driven economy:
- It is all about data, data..data
- Data is the new Oil of Economy
- Data is flooding the C suite; but dulling the intelligence
- Data is trapped in various Silos
- If you can figure out how to connect these Silos and extract the most desirable and useful information, you may be able to make more intelligent decisions
Let us describe the data: (It can be described by 5Vs):
- Volume: Petabytes of data is being generated; need for storage continues to increase
- Velocity: The rate of data generation continues to accelerate, 50% of the world has mobile devices –Mobile banking, WhatsApp
- Variety: Data is no longer Binary data; it is made up of Telecom, Sound, Video, Graphics, Social and Sensor data
- Veracity: It is critical to pay attention to Facts and Accuracy of the data; What is Real
- Value: Ultimately, our challenge is to extract the Value hidden in this vast amount of data; Data Analytics
Data science vs. Computer Science:
- Data Science is not Computer Science
- Data is not just the Binary data
- It is Graphics, Imaging, Voice, Telecom and of course, also binary data
- Tremendous amount of Information/knowledge is hidden in the data
- Data science is the next generation of Mathematical modelling, Statistics, Graphing, Visualization and Information extraction out of the Data lakes or Data Silos. This is where machine learning comes in
Extracting this knowledge (intelligence) is what AI and ML are all about
Who has the most data? Based upon your market segment and its field of specialization, a company may have the best relevant data. However, you don’t have to have gigabytes and petabytes of data anymore, as long as you can come up with the right mathematical model and algorithm to expand that data.
Now let us turn around and look at Computers vs. AI
- AI is the science of computers, completing tasks that would require intelligence when performed by humans. Applying this definition, is why AI is synonymous with machine learning and predictive analytics
- Pundits may make you believe that computers will take over the world in the not-so-distant future; the reality is that replacing human cognitive intellect has resulted in only modest gains in the last five decades
- Nonetheless, AI can be useful as an overlay that works to extend the intelligence of humans
- AI has helped transform massive amounts of data into actionable items
- There are 2 types of AI or machine learning:
- Supervised learning refers to humans directing a computer to solve a given problem
- Unsupervised learning involves the use of computer algorithms to analyze data and present findings that a human can then use to solve problems
In summary:
- AI is the added intelligence hidden in the vast amount of data being generated and collected by computer systems in our daily lives
- This added Artificial intelligence can be used as science of training systems to emulate human tasks through learning and automation
- A computer’s strength comes from its ability to reliably, efficiently and accurately analyze large volumes of data without fatigue
- But the computers don’t understand strategy. They are limited to repetitive specific tasks, which they execute in a very intelligent manner
- Computers also can’t predict future; they rely only on the data from the past and the present
To conclude:
If we can harness the strengths of machines and artificial intelligence, while acknowledging their weaknesses, we can use current technologies to significantly accelerate the future success of human beings.
Naresh Batra
CEO sfivei
Email: n.batra@sfivei.com
