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The notion that data is the lifeblood of artificial intelligence (AI) has been a prevailing theme in the industry. However, as AI continues to evolve and mature, it's becoming increasingly clear that knowledge – not data – will be the differentiator between truly innovative systems and those that merely process information.
Data alone can provide insights into patterns and trends, but it lacks context, depth, and nuance. Knowledge, on the other hand, represents a higher level of understanding, born from the integration of experience, expertise, and critical thinking. It's the ability to apply learned concepts to new situations, make informed decisions, and adapt to changing circumstances.
Knowledge compounding is the process by which organizations can harness their collective experiences, successes, and failures to create a rich tapestry of knowledge that informs future decision-making. AI enables this process by converting knowledge into questions, allowing us to identify gaps in understanding, prioritize important queries, and develop effective strategies.
A prime example of this concept in action is Korry's project-based approach. By leveraging insights from previous projects, they're able to distill a set of essential questions and apply those lessons learned to new challenges. This iterative process enables their AI systems to synthesize information, identify knowledge gaps, prioritize important queries, and develop effective strategies for tackling novel situations.
In contrast to traditional data-centric approaches, knowledge compounding:
1. Fosters contextual understanding: By integrating experiences from various projects, organizations can gain a deeper comprehension of the complexities involved in solving real-world problems. 2. Encourages critical thinking: Knowledge compounding promotes the development of essential questions that facilitate informed decision-making and adaptability. 3. Cultivates expertise: This approach recognizes that knowledge resides not only within individuals but also in the collective experience of an organization, allowing for a more comprehensive understanding of challenges.
Building a Sustainable Advantage with AI
As artificial intelligence (AI) continues to advance, it's crucial to recognize its true potential lies in building knowledge-based systems. I believe this is where AI firms can establish their competitive advantage.
While companies like Microsoft, OpenAI, and Google focus on collecting data, they inadvertently give away value when users access their models. The real value, however, lies elsewhere – in the accumulation of knowledge that enables continuous improvement and efficiency gains.
A Lesson from Aviation that can be Applied to the Financial Market
The aviation industry exemplifies this approach. By meticulously analyzing problems and implementing corrective measures, air travel has become significantly safer over time. Every innovation, every safety feature, is a testament to the power of cumulative knowledge.
We can apply similar principles to AI development. Each project generates new insights, which in turn enhance our understanding for future applications. This iterative process enables us to refine our systems and deliver better products or services with each iteration. By building on this accumulated knowledge, we unlock the true potential of AI.
This content is provided by an external author without editing by Finextra. It expresses the views and opinions of the author.
Prakash Bhudia HOD – Product & Growth at Deriv
13 March
James Strudwick Executive Director at Starknet Foundation
Foday Joof Risk Management Officer at Central Bank of The Gambia
Anoop Melethil Head of Marketing at Maveric Systems
12 March
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