The progress of generative AI

Generative AI for Business

Carl Rosseel

Head of Business Intelligence Curriculum at DataCamp

The key players

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Government Government_building

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Open-source communities Collection of open source generative AI tool and model logos

Generative AI for Business

Universities

  • Production center of research and theory
    • GANs were developed at University of Montreal
  • Training and inspiring researchers
  • Collaboration with industry and government

Generative AI for Business

Government and civic institutions

  • Governments regulate and fund the industry
    • DARPA funds research into making AI explainable
  • Civic institutions provide resources for independent projects
    • CIFAR-10 image dataset

Generative AI for Business

Companies (large and small)

  • Generative AI is rapidly adopted
    • to gain market advantage
    • to attract more funding

   

  • Big tech companies specifically
    • produce research
    • develop hardware and infrastructure
    • acquire startups

Generative AI for Business

Open-source community

  • Provide open access
  • Lower barrier to entry
  • Risks:
    • Projects cannot be maintained indefinitely
    • Malicious use

Collection of open source generative AI tool and model logos

Generative AI for Business

Companies and open-source

Wins

  • Developer support
  • Talent acquisition
  • Feedback from a wide community

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Challenges

  • Loss of competitive edge
  • Misuse of research/technology

 

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Generative AI for Business

Going forward

Accelerators:

  • Lower costs of hardware
  • Research and development
  • Market competition

Decelerators:

  • Technological limits
  • Regulation
  • Lack of funding or talent

Generative AI for Business

Let's practice!

Generative AI for Business

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