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Industry Solutions, AI and Machine Learning

Make "Gen AI Work": Landscape, SLMs vs. LLMs, Cost & More...

By Bruno Aziza | April 23, 2024

Are you fascinated by the ever-evolving world of Machine Learning (ML), Data Analytics (DA), and Artificial Intelligence (AI)? If so, then buckle up for a ride through the "Mad landscape" with this engaging carcast!

In this week's edition, we discuss the fast growing Machine Learning, AI & Data Landscape with my friend FirstMark's Matt Turck. His MAD Landscape documents 2,000 companies from Infrastructure, Analytics to Applications.  10 years ago, there were just 139 companies in the landscape. So, in 10 years, the space has grown by 14X!

We delve into the mind-boggling growth of the Mad landscape while Matt argues that the focus is shifting from structured data to the vast, uncharted territory of unstructured data, demanding a whole new set of technological tools.

The conversation doesn't stop there. We dive deep into the world of Generative AI and unpack the key differences between small language models (SLMs) and large language models (LLMs). Think of SLMs as the focused athletes excelling in specific tasks, while LLMs are the all-around champions with a broader range of capabilities. The future of enterprise AI is likely to be shaped by a powerful hybrid architecture that leverages the strengths of both SLMs and LLMs.

I hope you'll find this week's session helpful.  Among others, we tackled questions like:

  • Where are we in the AI hype cycle?
  • Is Traditional AI dead?
  • Will 2024 be the year of AI in the Enterprise?
  • How much does AI actually cost?
  • What explains the emergence of Small Language Models (SLMs)...vs. LLMs. 



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