The clock is ticking for effective GPT data management
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The power of generative AI, exemplified by large language models (LLMs) like GPT, lies in its ability to generate a variety of content types from large volumes of data. This evolution in data manipulation, analysis, and building makes these processes easier for everyone, not just data scientists and engineers. However, the real value is found not in data collection but in the ability to accurately utilize it with AI, machine learning, and secure infrastructure. With the transition to cloud environments and the advent of microservices and APIs, handling and managing data has become more complex, necessitating the involvement of more roles within an organization.
The focus in organizations and the media has been on data utilization and less on managing the data and infrastructure. This focus has resulted in more investment in startups building on top of LLMs like GPT and less in those building solutions for data management and infrastructure. However, without proper data management, AI systems, information security processes, and automated information flows could encounter bottlenecks. The next generation of Israeli startups is expected to focus on data management, including data quality and contracts, process automation, analytics explainability, and cost optimization for the modern data stack. As data becomes cleaner, more accurate, and easier to use, the tech running on it will yield more value in the long term.
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