Scope of AI – Why are the Technology Giants busy with AI?

IT giants are busy with a revolutionary innovation- AI technology. Microsoft, Meta, OpenAI, IBM, and Anthropic are in open competition in technically designing their own LLM engine for public approval.Also, there are several start-ups and research labs that are mushrooming. The names include Midjourney AI (2022), Stability AI (2019), DALL-E (2021), Black Forest Labs (2024), etc.

In this article, we will explore the scope of AI. It will include what is AI when AI started, what we have achieved so far with AI, and the limitations of AI.

 

What is an AI Machine?

In AI we often use the word machine. Therefore,  it is important to understand what an AI machine is. AI machine is a program that can do human tasks that require cognitive intervention. 

Examples of AI machines:

• AI Algorithm
• Foundation Model
• LLM (Large Language Model)
• Interactive devices
• Hardware

 

When did AI start?

Artificial Intelligence started entering the commercial market with Machine Learning and Deep Learning at least 15 years back in 2010. Back then we mainly used machine learning for decision making.

Example: Dynamic price determination based on demand, traffic conditions, weather conditions, and other factors.

Machine learning and deep learning are closely related but have subtle differences. We can say that Deep Learning is more about exploring the unexplored. Deep Learning is all about determining a hidden pattern and unsupervised learning.

 

 

Where are we now with AI?

Artificial Intelligence is now standing at the door of ground-breaking achievements in all fields. While data scientists and top web development teams are busy training their Foundation Model, people worldwide are speculating about the impact on our regular lifestyle and livelihood. 

 

• NLP (Natural Language Processor)

NLP or Natural Language Processor is the foundation of all AI models. NLP helped human beings interact with machines without writing codes. Machines can understand simple English or voice commands using NLP.  It helps in analysis in automation. We call it deep learning.

A small example:

• A text can be converted automatically into a mathematical problem.
• The mathematical problem can be solved by machine.
• Convert output into plain text that human beings can understand. 
• This completes a hell lot of a complete interaction cycle between man and machine.

 

• Picture to Text

 

We can convert PDFs and images and provide a text output using OCR or Optical Character Recognition. Therefore, it opens a whole new world of automation in industries like healthcare, automation, legal firms, administration, and government organizations.

 

 

• Generative AI or GenAI

The most irresistible yet the most dangerous tool is Generative AI. The term explains itself. It means it can “generate”. 

When you ask what an AI can ‘generate,’ an AI engineer will ask you what you want. To elaborate, AI can generate a wide range of outputs, from images and documents to graphs and even composing songs. You will only need to give a simple text command. The machine does the rest! 

Dangerous, no?

 

 

• LLM

LLM or Large Language Model is a foundation model trained to provide contextually relevant texts. For example, ChatGPT -4 can respond to any inquiry. It has made man-machine interaction to a whole new level. In this generation of AI, man is no more required to code complex programming language to interact with the machine. We are using simple English using voice or text command to talk to a machine. This is what the magic of LLM is all about. LLM uses Machine Learning to achieve this. This is specifically done by Natural Language Processing (NLP) and by Deep Learning techniques.

 

Why people are using ChatGPT or Claude(Anthropic)?

• Translation: Language teachers are using ChatGPT as a translator.
• Debugging: Software engineers are using ChatGPT to generate/ debug a piece of code.
• Document Creation:HR executives can generate a policy document using Claude.
• Information Hub: Lawyers can find necessary legal information by interacting with an LLM.

LLM is an interactive and intelligent Wikipedia where you are getting the feeling of interacting with an AI Chatbot online.

 

• Voice Assistant

Not only does a machine understand human language in the form of voice commands or texts, but it can also respond back to human beings using a synthetic human voice.

Example: Amazon’s Alexa, Siri, Google Assistant, etc,

 

• Facial recognition

A special branch of AI that uses machine learning and artificial intelligence to detect faces. Facial recognition is used widely for security and surveillance, patient identification in healthcare, and mobile devices for authentication.

 

 

• AI in Healthcare

AI is vividly used in the healthcare industry both for analysis as well as for robotics. Artificial Intelligence Algorithms analyze medical images like CT Scans, MRIs, USG Scans, ECG, etc. AI-powered robots for performing minimally invasive surgeries.

This is because Foundation Models have analyzed billions of data to become intelligent, interactive, and precise. We will probably need a zillion words to define the scope of AI in the emerging world. However, there is or will be some limitations of AI. 

 

 

Limitations of AI:

Not many I can think of, but here are a few:

1. Firstly, Artificial Intelligence engines don’t have the emotional quotient to address social issues
2. Secondly, AI cannot sense or screen anti-social activities or trigger alarms.
3. Thirdly, Generative AI can be easily misused beyond ethical boundaries.
4. Since generative AI is formed by studying pattern, there can be chance where a GenAI creation can give rise to Copyright Violation.
5. Finally,  AI can never match human creativity.

 

 

Conclusion: Standing in 2024, we are still evaluating the scope of AI. There is an ocean of opportunities in every field to utilize AI. At this nascent stage (10 years of hard work)we have only managed to train the AI Models. But now comes the most challenging task of regulating its use and licensing. While the tech giants are already in the tech bout to capture the market and create a monopoly, the administration is carefully watching. So are we!