james_chu

Given the current trend of companies developing increasingly large language models, with the goal of creating a single model that can do it all and surpass human-level performance, it is worth considering an alternative future scenario. In this scenario, models are micro-sized and highly specialized, capable of performing only a few specific tasks.

These micro-models are independent and can run on CPUs, with a high degree of automation that allows them to identify problems and dynamically combine with other micro-models to complete larger tasks.

This approach would allow for the creation of flexible model ensembles that can be easily disassembled into their constituent micro-models."

[ASE Rankings Update]

Exciting news for technology enthusiasts and market watchers! The ASEED (AI Search Engine Evaluation Dataset) has been publicly released, paving the way for transparent benchmarking in the burgeoning field of AI search engines, which are anticipated to revolutionize the market.

Explore ASEED: This open-source dataset not only sets the stage for identifying which AI search engines might become phenomenally successful products but also offers critical insights into their performance metrics. Stay updated with ASEED to discover who might emerge as the frontrunner in this dynamic sector.

Find more details on our GitHub page: sparticleinc/ASEED: Conversational Retrieval Evaluation Dataset.

<https://github.com/sparticleinc/ASEED>

As of now, Metaso holds a slight edge in the rankings over Perplexity, leading with innovative features and robust performance.

We Want Your Input: Which other AI search engines should we keep an eye on? Please share your thoughts in the comments below.