Understanding Support Patterns

Oct 1, 2024

Understanding Support Patterns #

Finding patterns in the support cases helps to find structural issues and bottlenecks in the data platform.

Just after BigQuery released the ML.GENERATE_TEXT functions (mid 2024) and made Gemini accessible though BigQuery, I was curios to to test this new feature. And what better use case then understanding Support Patterns and issues with the support on the fly.

Thus, I tried these features by analyzing a sample of our internal support tickets.

AI Summit 2024

Dec 11, 2024

Today, December 11, 2024, I had the honor of participating in a panel at the AI Summit New York, discussing LLMs Application Solution Lifecycle: Development, validation and implementation

The panel addressed the complexities involved in the development, validation, and deployment of LLM and RAG applications. One of the key topics was the importance of structuring data effectively before indexing, focusing on encoding, chunking, and embedding. We explored how aligning prompts with embedded document structures plays a critical role in enhancing model performance and ensuring more accurate and efficient retrieval.

AI Summit 2023

Dec 6, 2023

On December 6th 2023 I participated in a panel discussion on the AI Summit alongside Joel Beckerman and Josephine Hua Pan under the title “Dawn of AI: The End of Human in the Entertainment Industry”. We were discussing the impact of AI on the entertainment industry.

We discussed how that AI is a valuable tool for enhancing creative processes rather than replacing human creators. AI acts as a tool to generating new forms of content and streamlining workflows.

Economic Cooperative Systems

May 10, 2024

Economic Cooperative Systems #

I am reflecting on the potential of AI and what has to be build.

I am taking a procurement process as the baseline for a cooperative system. The perspective of the buying model:

1. Identifying Needs: The whole process starts with a need. This need can be identified by a model itself recognizing that it might not be the best to solve the problem itself.
2. Supplier Research and Selection: reach out to a marketplace / exchange and fin potential suppliers based on something like a request for Proposal/Quotation (RFP/RFQ). The offered prices in conjunction with a vendor self assessed confidence for a response are received as a bid in the exchange.
3. Approval / PO issuance: The buying model can now pick it’s supplier based on it’s configuration of price & quality. (There might be more than one quality metric.)
4. Assign the task to the model identified.
5. Receipt and Inspection: the buying model can now assess the quality of the response or might leave this assessment to the user.
6. Payment: a payment can be disputed if the response is of a objective quality below a certain measure. (There might be quality assurance / audit models within the system to ensure orderly conduct of business.) If the objective measures are ok, a payment has to be made. Feedback can be given, that yields future decisions, blacklisting of models etc.
7. Keeping and Audit: Given experience, there must be a record for each transaction with all it’s parameters. This allows for further
8. Performance Review and Relationship Management: The supplier’s performance is reviewed, and feedback is provided. This step also involves maintaining and managing the relationship with the supplier for future transactions.and auditing.

It is easy to derive the vendor perspective from the above.