Nicolay Gerold

For High Throughput data, Grab uses Apache Avro with a strategy called Merge on Read (MOR) .

Here's the main operations with Merge on Read:

• Write Operations - When data is written, it's appended to the end of a log file. This is much more efficient than merging it in the current data and reduces the latency of writes.


• Read Operations - When you need

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t on LLMs and SQL highlighting why they don’t consistently work :

• “LLMs can write SQL, but they are often prone to making up tables, making up field”


• “LLMs have some context window which limits the amount of text they can operate over”


• “The SQL it writes may be incorrect for whatever reason, or it could be correct but just return an unexpected

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Efficiency comes from doing one unit of work to answer each question, but scalability comes from doing the least amount of work and answering more questions.

This README is under construction as we work to build a new community driven high performance key-value store.

This project was forked from the open source Redis project right before the transition to their new source available licenses.

This README is just a fast quick start document. We are currently working on a more permanent documentation page.

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The brain leads to associate the taste, the likes and dislike, with the signals from the gut, which measures what you need (protein, sugar, fat) and causes craving.

Workflow+model startups will win by combining a fine-tuned model with deep customer insight to build an AI-native workflow. These startups will be particularly well-positioned to win in one of the following 3 scenarios:

1. Incumbent saas players do not have legacy workflow dominance in that vertical


2. An AI-native workflow solves the most critical

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Build an optimized, secure, and frontend-independent application for multi-platform deployment.

Langfuse is an open source observability & analytics solution for LLM-based applications. It is mostly geared towards production usage but some users also use it for local development of their LLM applications.

Langfuse is focused on applications built on top of LLMs. Many new abstractions and common best practices evolved recently, e.g. agents,... See more

In the open-source community, there are huge numbers of people leveraging AutoGen in creative ways, and solving surprising problems. One pattern that we see as fundamental is the "generator+critic" pattern, where one agent generates content (writing, code, etc.) and another agent critiques it (finds bugs, etc.) They can iterate until the solution... See more