The Strategic CEO’s Guide to Navigating the AI Landscape - Part II
Part 2 of 3
For businesses, two major paths of development have emerged:
Investment in broad, multimodal foundation models. Large AI companies, driven by the resources at their disposal, are competing on this front.
Investment in millions of small, domain- or task-specific AI models. Here, companies compete on the basis of their domain-specific knowledge and expertise.
As AI continues to advance, it's becoming increasingly clear that it's not only the large-scale foundation models that carry value. Small Specialist Models (SSMs), which are efficient and domain-specific, hold immense potential. The open-source project OpenSSM, led by Aitomatic, is a major player in accelerating the global development and adoption of SSMs. For businesses, this presents two key opportunities. Firstly, the opportunity to create the best SSMs leveraging their domain-specific knowledge and expertise. Secondly, the opportunity to host and make effective use of these SSMs. (See the OpenSSM project.)
In the immediate future, the picks-and-shovels companies that provide essential services and technologies required for AI implementation will see significant growth. An example is the recent acquisition of MosaicML by Databricks. Both company CEOs are long-time friends, which gives me some insights into the dynamics of the acquisition. MosaicML’s journey offers a fascinating glimpse of what’s possible when riding the AI wave. MosaicML, specializing in making large-model training more efficient and reliable, saw a surge in demand following the release of ChatGPT. Their model training technologies helped them rapidly grow revenues. The subsequent acquisition by Databricks is a testament to their successful strategy. This acquisition not only benefits both parties but also signifies the value of these types of companies in the evolving AI landscape.
CEOs need to understand the significant shifts occurring in the AI landscape and align their strategic plans accordingly. With the rise of AI, it's crucial to integrate AI capabilities in your business model. This includes both investment in AI technologies and fostering AI expertise within your organization.
Acknowledge the Central Role of AI
AI is transforming industries and becoming an indispensable part of innovation strategies.
Understand the Geopolitical Landscape
Countries worldwide are investing in AI independently due to geopolitical factors. This creates demand distortions for AI infrastructure, such as Nvidia's chips, and opens up opportunities for regional collaborations.
Appreciate the Evolving Landscape
Major players like Google and Microsoft are restructuring and ramping up their AI efforts. Stay informed about these developments as they shape the future of AI.
Utilize Domain-Specific Models
Invest in Small Specialist Models (SSMs) that align with your specific operations to avoid directly competing with AI giants and benefit from the ongoing bifurcation in the AI landscape.
One effective strategy for implementing AI is to initially focus on Q&A AI to index corporate knowledge and make it accessible to employees. This approach provides immediate productivity gains. However, the ultimate goal should be the implementation of problem-solving AI, which will lead to significant increases in operational efficiency and effectiveness. While Q&A AI can provide near-term value, real enterprise value will be unlocked when Generative AI crosses from the IT domain to the OT domain. I'm optimistic about the future of problem-solving AI architectures like Aitomatic’s aiCALM, which will be based on these teams of domain-expert SSMs.
Part 2 of 3
For businesses, two major paths of development have emerged:
Investment in broad, multimodal foundation models. Large AI companies, driven by the resources at their disposal, are competing on this front.
Investment in millions of small, domain- or task-specific AI models. Here, companies compete on the basis of their domain-specific knowledge and expertise.
As AI continues to advance, it's becoming increasingly clear that it's not only the large-scale foundation models that carry value. Small Specialist Models (SSMs), which are efficient and domain-specific, hold immense potential. The open-source project OpenSSM, led by Aitomatic, is a major player in accelerating the global development and adoption of SSMs. For businesses, this presents two key opportunities. Firstly, the opportunity to create the best SSMs leveraging their domain-specific knowledge and expertise. Secondly, the opportunity to host and make effective use of these SSMs. (See the OpenSSM project.)
In the immediate future, the picks-and-shovels companies that provide essential services and technologies required for AI implementation will see significant growth. An example is the recent acquisition of MosaicML by Databricks. Both company CEOs are long-time friends, which gives me some insights into the dynamics of the acquisition. MosaicML’s journey offers a fascinating glimpse of what’s possible when riding the AI wave. MosaicML, specializing in making large-model training more efficient and reliable, saw a surge in demand following the release of ChatGPT. Their model training technologies helped them rapidly grow revenues. The subsequent acquisition by Databricks is a testament to their successful strategy. This acquisition not only benefits both parties but also signifies the value of these types of companies in the evolving AI landscape.
CEOs need to understand the significant shifts occurring in the AI landscape and align their strategic plans accordingly. With the rise of AI, it's crucial to integrate AI capabilities in your business model. This includes both investment in AI technologies and fostering AI expertise within your organization.
Acknowledge the Central Role of AI
AI is transforming industries and becoming an indispensable part of innovation strategies.
Understand the Geopolitical Landscape
Countries worldwide are investing in AI independently due to geopolitical factors. This creates demand distortions for AI infrastructure, such as Nvidia's chips, and opens up opportunities for regional collaborations.
Appreciate the Evolving Landscape
Major players like Google and Microsoft are restructuring and ramping up their AI efforts. Stay informed about these developments as they shape the future of AI.
Utilize Domain-Specific Models
Invest in Small Specialist Models (SSMs) that align with your specific operations to avoid directly competing with AI giants and benefit from the ongoing bifurcation in the AI landscape.
One effective strategy for implementing AI is to initially focus on Q&A AI to index corporate knowledge and make it accessible to employees. This approach provides immediate productivity gains. However, the ultimate goal should be the implementation of problem-solving AI, which will lead to significant increases in operational efficiency and effectiveness. While Q&A AI can provide near-term value, real enterprise value will be unlocked when Generative AI crosses from the IT domain to the OT domain. I'm optimistic about the future of problem-solving AI architectures like Aitomatic’s aiCALM, which will be based on these teams of domain-expert SSMs.
