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What's Possible After What's Possible
Harnessing the Power of GenAI at the Enterprise Level to Disrupt Your Industry

This is a GenAI Possibilities PoV:

Why the explicit declaration? As the proliferation of the term ‘AI’ continues, there is still confusion about the difference between traditional AI and GenAI. As an example, the function of speech-to-text conversion classifies as a traditional AI use case, but content creation and customization use cases are GenAI (making GenAI a subset).
Here’s a quick splainer by Marily Nika to help us set context and begin from square 1. 

The landscape of AI and its Use Cases

The landscape of AI and its Use Cases
Credit: Marily Nika
marily.substack.com

GenAI - The Blue-Eyed Boy of AI

A form of AI based on Large Language Models (LLM) (combined with other algorithms such as transformers) that can generate something new based on the provided context, GenAI is all the rage in the world today. Traditional AI was not very business user-friendly and needed deep knowledge of data science, quants and statistics combined with coding capabilities. GenAI holds much more power to demystify and ‘uber’-ise access to AI for a lot of business users across sectors and industries.

GenAI is at the apex of tech research momentum and has taken the world by storm through a series of application-level platforms like ChatGPT, Bard and Claude. With this PoV, we are making a sortie deep into AI territory and the potential it holds for you to disrupt the foundations of your industry. But first, it’s story time. While you read about DeepMind, it is important to remember that this all took place in 2016, way before AI captured the imagination of the world as it has today. 

‘If you’ve not watched the Google DeepMind AlphaGo documentary, you’re in for a mind-numbing AI story. When the AI researchers at DeepMind, led by Demis Hassabis, set out to create a professional virtual Go player, no other ‘AI’ had been made to defeat a professional Dan player without a handicap. Go is considered infinitely more complex than chess to ‘master’, as the traditional deep learning models, like alpha-beta pruning and heuristic search do not apply here. DeepMind researchers applied the Monte Carlo tree algorithm to create AlphaGo, beating some of the world’s highest-ranked professionals in the process.
The same team has come a long way since then. They recently uncovered more than 800.years worth of research using a new neural network tool which will change the use of future materials for key industries. ’

So, What’s Possible with GenAI? 
Simply put, a lot of possibilities. But they can be clubbed under three broad functional areas as: 
We have all experienced the power of GenAI through the GPT platforms mentioned earlier and they continue to improve with every prompt fed to them. A trained LLM will provide many possibilities across various industries. To understand foundation level capabilities, the following graph shows the rise in AI performance for fundamental learning benchmarks worldwide. With theoretical mastery underway, can practical al know-how be far behind?  
Source: Sparks of Artificial General Intelligence: Early experiments with GPT-4, Bubuck et al. 2023

We are already seeing the advent of AI-led transformation across industries. Some have already reached your home – intelligent recommendations by Netflix – and chances are, in the next 12 months, more than half the world’s population will have experienced the power of GenAI directly in their life.

Here’s a snapshot of industry-specific disruptions already afoot:

Healthcare

Customized treatment plans 

Banking and Finance

Personalized insights 

Insurance

Customer experience chatbots | Expedite claims settlements

Telecom

Customer support and experience 

Legal

Document analysis | Research and historical learning

Retail

Advanced customer engagement 

Ready to Cook with GenAI? 

Understanding AI and applying it is very different. Having the perfect setup to whip up a delicious meal can look simple but it is hard work. Any restaurant that aims to please must have a steady supply chain of what’s needed to plate good food. Similarly, here is how enterprises can get ‘GenAI ready’ with an example of how a well-oiled kitchen setup works. 

Every dish this kitchen setting delivers can be equated to an industry use case, be it automation or intelligence adding in nature. The impact on productivity, efficiency and repetitive tasks can be mind-boggling.

Here are some examples to help us understand real world applications better.  

Group 1000006243

We have already seen the learning capabilities of GenAI LLMs across various sectors. Training LLMs is a process that needs a lot of fine-tuning to perfect, not to mention the associated costs. Once the basic training is complete, the best case for training involves a man-machine interface. Take ‘labeling’ as a process, for example – which categorizes outcomes for the AI to understand human requests. The AI can create drafts for humans to evaluate and critique labels and their performance, which need concurrency and collaboration.

All this is needed to truly unlock the possibilities of GenAI we haven’t experienced yet. Thankfully the Head Chef or the GenAI Solutions Architect will be your best bet as chaperone through this journey 

Possible After What’s Possible:
I hope that reference has gotten you hungry for the future. With regards to LLMs, it will be possible for the Solutions Architect (head Chef) and their AI Bots (assistants or AI Agents (sous chefs) to create something special for each customer and their palette. Knowledge and tactical intelligence can be available each time a customer places an order because we have mastered the two pillars that prop up GenAI as the solutions technology of the future. 
Breaking the Knowledge Hegemony
Just like in cooking or any specialized industry, knowledge is the fiefdom of a few gatekeepers. GenAI breaks that by assimilating data and context into learning that can be applied to real world challenges. We know the models are getting smarter with each prompt and can breakdown challenges at the product, process or business landscape level. With democratization of knowledge, nuance and know-how, the business user is given unprecedented power to steer the business in the right direction. 
Tailor Made Industry Solutions
Imagine serving a dish suited to every taste, level of spice, presentation, crunch and even time of the day based on what the user desired. Micro-tiny models help organizations create an open smorgasbord of options to choose from which are tailored to business and technical challenges for sectors and industries looking to make the next evolution in how they serve their customers. Just like a GenAI buffet table with an all you can eat pass. Macro and micro use cases which can have quick impact on top lines and customer experience will usher in a new age of customer centricity and expectations.  
Conclusion: So Let GenAI Cook 
Understanding GenAI and its disruption potential for your industry and customer is now vital to every business leader. Just as the kitchen has evolved from serving the masses to even providing granular nutrient information for every dish and a plethora of options to cater to diverse demands, so must the modern progressive business. Starts with asking the right question – What can GenAI do for my business and how do we get to the far realms of possibilities.  

What's Possible After What's Possible Harnessing the Power of GenAI at the Enterprise Level to Disrupt Your Industry

What’s Possible with GenAI
Why the explicit declaration? As the proliferation of the term ‘AI’ continues, there is still confusion about the difference between traditional AI and GenAI. As an example, the function of speech-to-text conversion classifies as a traditional AI use case, but content creation and customization use cases are GenAI (making GenAI a subset).  
Here’s a quick splainer by Marily Nika to help us set context and begin from square 1. 
The landscape of AI and its Use Cases
Cinque Terre Cinque Terre
GenAI – The Blue-Eyed Boy of AI 

A form of AI based on Large Language Models (LLM) (combined with other algorithms such as transformers) that can generate something new based on the provided context, GenAI is all the rage in the world today. Traditional AI was not very business user-friendly and needed deep knowledge of data science, quants and statistics combined with coding capabilities. GenAI holds much more power to demystify and ‘uber’-ise access to AI for a lot of business users across sectors and industries.

GenAI is at the apex of tech research momentum and has taken the world by storm through a series of application-level platforms like ChatGPT, Bard and Claude. With this PoV, we are making a sortie deep into AI territory and the potential it holds for you to disrupt the foundations of your industry. But first, it’s story time. While you read about DeepMind, it is important to remember that this all took place in 2016, way before AI captured the imagination of the world as it has today. 

‘If you’ve not watched the Google DeepMind AlphaGo documentary, you’re in for a mind-numbing AI story. When the AI researchers at DeepMind, led by Demis Hassabis, set out to create a professional virtual Go player, no other ‘AI’ had been made to defeat a professional Dan player without a handicap. Go is considered infinitely more complex than chess to ‘master’, as the traditional deep learning models, like alpha-beta pruning and heuristic search do not apply here. DeepMind researchers applied the Monte Carlo tree algorithm to create AlphaGo, beating some of the world’s highest-ranked professionals in the process.
The same team has come a long way since then. They recently uncovered more than 800.years worth of research using a new neural network tool which will change the use of future materials for key industries. ’

So, What’s Possible with GenAI? 
Simply put, a lot of possibilities. But they can be clubbed under three broad functional areas as: 
  • Extraction – understand contextual reference and present data as desired
  • Summarization – Create meaning from data that can be consumed and actioned upon.
  • Generation – Create new content (image, text, videos) for many use cases.
We have all experienced the power of GenAI through the GPT platforms mentioned earlier and they continue to improve with every prompt fed to them. A trained LLM will provide many possibilities across various industries. To understand foundation level capabilities, the following graph shows the rise in AI performance for fundamental learning benchmarks worldwide. With theoretical mastery underway, can practical al know-how be far behind?  
Cinque Terre Cinque Terre
Source: Sparks of Artificial General Intelligence: Early experiments with GPT-4, Bubuck et al. 2023

We are already seeing the advent of AI-led transformation across industries. Some have already reached your home – intelligent recommendations by Netflix – and chances are, in the next 12 months, more than half the world’s population will have experienced the power of GenAI directly in their life.

Here’s a snapshot of industry-specific disruptions already afoot: 

Healthcare

Customized treatment plans 

Banking and Finance

Personalized insights 

Retail

Advanced customer engagement 

Telecom

Customer support and experience 

Legal

Document analysis | Research and historical learning

Insurance

Customer experience chatbots | Expedite claims settlements

Ready to Cook with GenAI? 
Understanding AI and applying it is very different. Having the perfect setup to whip up a delicious meal can look simple but it is hard work. Any restaurant that aims to please must have a steady supply chain of what’s needed to plate good food. Similarly, here is how enterprises can get ‘GenAI ready’ with an example of how a well-oiled kitchen setup works. 
Serving GenAIon a platter

Every dish this kitchen setting delivers can be equated to an industry use case, be it automation or intelligence adding in nature. The impact on productivity, efficiency and repetitive tasks can be mind-boggling.

Here are some examples to help us understand real world applications better.  

We have already seen the learning capabilities of GenAI LLMs across various sectors. Training LLMs is a process that needs a lot of fine-tuning to perfect, not to mention the associated costs. Once the basic training is complete, the best case for training involves a man-machine interface. Take ‘labeling’ as a process, for example – which categorizes outcomes for the AI to understand human requests. The AI can create drafts for humans to evaluate and critique labels and their performance, which need concurrency and collaboration.

All this is needed to truly unlock the possibilities of GenAI we haven’t experienced yet. Thankfully the Head Chef or the GenAI Solutions Architect will be your best bet as chaperone through this journey 

Possible AfterWhat’s Possibe :
I hope that reference has gotten you hungry for the future. With regards to LLMs, it will be possible for the Solutions Architect (head Chef) and their AI Bots (assistants or AI Agents (sous chefs) to create something special for each customer and their palette. Knowledge and tactical intelligence can be available each time a customer places an order because we have mastered the two pillars that prop up GenAI as the solutions technology of the future. 
Breaking the Knowledge Hegemony
Just like in cooking or any specialized industry, knowledge is the fiefdom of a few gatekeepers. GenAI breaks that by assimilating data and context into learning that can be applied to real world challenges. We know the models are getting smarter with each prompt and can breakdown challenges at the product, process or business landscape level. With democratization of knowledge, nuance and know-how, the business user is given unprecedented power to steer the business in the right direction. 
Tailor Made Industry Solutions
Imagine serving a dish suited to every taste, level of spice, presentation, crunch and even time of the day based on what the user desired. Micro-tiny models help organizations create an open smorgasbord of options to choose from which are tailored to business and technical challenges for sectors and industries looking to make the next evolution in how they serve their customers. Just like a GenAI buffet table with an all you can eat pass. Macro and micro use cases which can have quick impact on top lines and customer experience will usher in a new age of customer centricity and expectations.  
Conclusion: So Let GenAI Cook 

Understanding GenAI and its disruption potential for your industry and customer is now vital to every business leader. Just as the kitchen has evolved from serving the masses to even providing granular nutrient information for every dish and a plethora of options to cater to diverse demands, so must the modern progressive business. Starts with asking the right question – What can GenAI do for my business and how do we get to the far realms of possibilities.