The 3 Catalysts Driving the Artificial Intelligence Renaissance

“Artificial Intelligence is the ultimate breakthrough technology”

—Satya Nadella


Five of the world’s ten most valuable companies – Alphabet (Google), Amazon, Apple, Facebook and Microsoft – are repositioning to become AI-first organizations.  Recently, Gartner boldly predicted that 80% of emerging tech will incorporate AI within the next two years.   

AI has reached an inflection point, driven by milestones in investment, capability, entrepreneurship and adoption. The implications for consumers, companies and society are profound.

“We will shift to a world that is AI-first.”

—Sundar Pichai

Why is AI Important?  

As discussed in depth in another Omega Venture Partners’ ‘Alpha Blog’ post, AI is a way for software to perform difficult tasks more effectively, by learning through practice instead of following rules.  AI is important because:

  • For the first time, traditionally human capabilities can be undertaken in software efficiently, inexpensively and at scale.
  • AI capability has reached an inflection point. After several false dawns since the 1950s, AI technology is coming of age.
  • AI is transforming entire industries and business models: New possibilities enabled by AI include autonomous vehicles; automated medical diagnosis; voice input; intelligent agents; automated data synthesis; and enhanced decision-making.


AI Has Reached an Inflection Point Because of 3 Key Reasons

(1) Proliferation of Data

There has been massive growth in the amount of unstructured data being created by the increasingly ubiquitous connected devices, machines, and systems globally. Artificial Intelligence systems become more effective the more data that they have, meaning that as the amount of data increases, the number of problems that AI can solve using that data increases.


90% of the World’s Data Was Created in the Last 2 Years

(2) Improved Price-Performance of Computing

The repurposing of Graphic Processing Units (GPUs) and the general availability of lower cost compute power through cloud services, have dramatically increased the speed and accuracy of the results AI-enabled solutions can produce.  The price per Gigaflop of computing (a standard unit of computing performance measurement) has declined from approximately $10 billion dollars in the 1960s to a few cents today.

Cost per GFLOPS (Log Scale, 2013 Dollars)

(3) Enhanced Algorithms Have Improved Results

Deep learning, a technique used to train AI systems on large amounts of data, is not new. Ideas for multilayer neural networks were published as far back as 1965.  In the last few years, however, improvements in the design of algorithms have transformed results, delivering breakthrough applications.


Not surprisingly, the World Bank has called AI the “the fourth industrial revolution” that is “poised to have a profound impact across markets and applications.”