Insights from the last AI Cycle

Drawing from the AI cycle of 2016-2018, there are some insights that can be developed:

  1. Importance of Strategic Planning: Many startups fell into the trap of assuming that AI development would be a linear process, and that increased computing power and data would naturally lead to improved AI capabilities. Infrastructure takes time to build (and time to sell to enterprises).

  2. Need for Sustainable Business Models: The failure of the “Human-in-the-loop” approach underscores the need for sustainable business models. Relying on the future success of technology to make a currently unprofitable model profitable is a risky strategy. Chatbots and agents that relied on human intervention with the intention of replacing said human processes were not sustainable.

  3. Value of Simplicity: The success of simpler models and frameworks over more complex ones indicates the value of simplicity in AI. Users often prefer tools that are easy to use and understand, even if they are less sophisticated. The data stack (e.g., much more grounded analysis) saw more investment and success.

  4. Focus on Core AI Capabilities: The success of companies that focused on core AI capabilities, such as data labeling, suggests that there is value in focusing on fundamental aspects of AI.

Some notable winners from the AI cycle of 2016-2018 include:

  • OpenAI: OpenAI demonstrated remarkable adaptability during this period, transitioning from reinforcement learning on video games to developing large language models, which have been widely adopted.

  • Scale AI: By focusing on an essential part of the AI workflow - data labeling, Scale AI secured a strong position in the market.

  • PyTorch: This open-source machine learning library for Python, developed by Facebook’s AI Research lab, gained significant popularity due to its simplicity and ease of use.

  • Yolo (You Only Look Once): This real-time object detection system became widely adopted due to its speed and efficiency.

  • Cruise: Acquired by General Motors, Cruise benefited from strategic buying, highlighting the value of AI in the automotive industry.

  • Zoox: This autonomous vehicle company was another winner in the strategic buying category, being acquired by Amazon.

  • Otto: Bought by Uber, Otto’s focus on self-driving trucks made it a winner in this AI cycle.

  • Airbnb and Uber: Despite some challenges, these companies were early adopters of AI and machine learning, using these technologies to enhance their services and operations.

  • Jasper AI: This company successfully leveraged GPT-3, a proprietary model developed by OpenAI, to deliver real value to customers without the need for human intervention.