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Well, never the less, these deal are all done with a set of vested interests that in many occasion don’t necessarily align with neither the customer’s (why companies should even exist) or that of their employees ( the motor of companies success) but more in the realm of financial spreadsheets, where, due diligence sways in the direction of those stakeholders in the deal… And I purposely look at it this way as no to take any given side without the details. Non the less, IMO, the only winners here are the stockholders, Splunk as a business, and many others with the same model of “schema selling” are in a high risks stake in the new erra of AI/LLMs. If you consider the accelerating world of AI we are living in, and the emergence/trend towards Domain Specific Large Language Models (DS-LLMs) and advancement like MEMgpt, they represent a transformative approach to data analytics. Instead of using a schema-specific model, as seen in tools like Splunk which extract and transform data into a predefined schema, DS-LLMs offer a flexible, continuously trained approach. They not only analyze data but also learn from it in real-time. The “actors”, or bots, leveraging tech like MEMgpt that not only collect but also learn from the vast streams of data are far more capable than those schema models. As these models self-train and trade knowledge, they are poised to provide insights more organically aligned with the data’s inherent structure, rather than a pre-defined schema. This means businesses could potentially gain deeper, more intuitive insights without the confines of structured data models. With the rapid pace of innovation in the AI sector, it’s worth questioning whether traditional, schema-based solutions will be able to keep up with the dynamic learning capabilities of DS-LLMs. I still wonder who got the better deal here. Wishing the best to all the Splunk employees moving forward. |