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Are we at the ‘Gutenberg’ moment of AI ?
Are we at the ‘Gutenberg’ moment of AI ?

August 1, 2024

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Paper was invented by the Chinese in the 2nd century AD. It was such a closely guarded secret that it took 9 more centuries for paper to reach Europe. Between 11th and 15th century AD Europe had produced a grand total of 30,000 books. But by 1500 AD, there were 9 million books, enough to stir up an intellectual revolution across the continent- The Renaissance.  What happened in 15th Century ? -- A German craftsman named Johannes Gutenberg invented the Printing Press, an invention that is the cradle for a whole new modern industry- the Print & Media industry.

So what is the relevance of this to AI?

Renowned theoretical physicist Michio Kaku explains that all mass technologies go through four basic stages.

  • Stage 1 – products of technology are so precious that it is a closely guarded secret much like paper between 2nd and 11th century.
  • Stage 2 – Technology becomes personal . The Gutenberg invention allowed for books to be produced at scale and they were no longer cocooned to patrician edifices but became prized possession of plebian folk too. 
  • Stage 3 - Technology gets commoditized. By 1930s, the cost of a sheet of paper fell to pennies and individuals could now afford to own a library of books at home.
  • Stage 4 -Technology becomes a fashion statement. Today we decorate our world with paper of all shapes, colours and sizes, so much so that it is the largest source of urban waste.

AI as a concept dawned in the middle of the 20th century and continued to be an arena restricted to geeks and nerds in research labs and academia.  A text based NLP application called ELIZA developed by MIT Computer scientist Joseph Weizenbaum back in 1964, is recognized as the first known Generative AI system. Baring a few widely publicized events like Deep Blue vs Garry Kasparov, AI remained an esoteric field indulged only by the scientific community. The invention of the transformer models, towards the end of the last decade changed all that. This invention became the enabler for what is the cornerstone of Generative AI - the Foundational models.

Today high school drop outs in the hinterlands of India leverage Gen AI tools and develop digital avatars and deep fakes of yesteryear stars and famous personalities for as low as $150.

Generative AI is well and clearly out of the realm of geeks and nerds and is not a closely guarded secret anymore.

Generative AI today summarize conversations, classifies data, performs sentiment analysis, generates content for specific purpose like marketing campaigns and job descriptions, analyzes and extracts information from unstructured data and answers queries on specific content. A Scale Zeitgeist Report in 2023 observed that over 80% of enterprises are working with or planning to leverage and adopt generative AI. Bulk of the development in these use cases have happened right in our own backyard in the Global Capability Centers in India.

IBM Research states that organizations have realized 40% improvement in HR productivity, have seen over 90% of customer inquiries being handled by AI Assistants and over 60% of software development content automatically generated by AI. IBM’s own internal AI Assistant for HR called AskHR has automated 84% of tasks and manages over 9 Mn employee interactions annually.

However over 80% of business leaders worldwide see at least one of four ethical issues as a major concern.

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Clearly AI is yet to cross the realm of ‘Emotional’ and ‘Social’ intelligence.ie. it is still not ‘sentient’ and does not have a ‘conscience’. That part of AI is still the playground of geeks and nerds. While the geeks are at it, Enterprises should embrace new tenets for operating with AI for the near future:

  • Open – Generative AI must be based on best open technologies available. Over two-thirds of 150+ enterprises surveyed by IBM Research report pursuing a multi-model strategy for Generative AI with both commercial and open source models.
  • Trusted - Generative AI platforms need to be trusted, offering security, and data and model protection. They also need to be architected with governance in mind from the start, not an afterthought and provide transparency, and explainability for their models to support increasing regulatory compliance demands. Data quality and provenance are paramount and ‘hallucinations’ are simply too expensive to be accommodated in Enterprise AI.
  • Targeted – Enterprises do not always need an expensive LLM trained on billions of parameters and one which requires extensive fine tuning to solve specific business problems. They need targeted models (or domain-specific models) for business use cases that can be quickly, effectively, and economically tuned with a small set of proprietary data from the business.
  • Scale for Value – Generative AI is not only about its Foundation models. The platform must also provide governance to ensure proper, responsible usage of the AI models. Moreover it needs to be able to support running wherever the business wants to at a desired scale. Most enterprises will deploy generative AI across hybrid / multicloud environments.

 

Do you believe Generative AI is Stage 2 of AI ?  Are we at the ‘Gutenberg’ moment of AI?

Whatever be the case, it is fair to say GenAI is still an ‘Infant’ and has a long way to go. We have seen elephants dance, but this baby has already set the stage on fire. One can only wonder what the world will be when the ‘Big Mammoth’ arrives.

 

About the Author:

Jayaram Sivaramakrishnan is a seasoned Technology Services Leader who has been with the industry since the dawn of the ‘dot com’ age. Jayaram is currently an Associate Partner with IBM India Pvt Ltd and he works closely with Financial Services Captives in India and helps them meet their strategic objectives.


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Jayaram Sivaramakrishnan
Associate Partner

Jayaram Sivaramakrishnan is a seasoned Technology Services Leader who has been with the industry since the dawn of the ‘dot com’ age. Jayaram is currently an Associate Partner with IBM India Pvt Ltd and he works closely with Financial Services Captives in India and helps them meet their strategic objectives.

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