Databricks-trained AI agents match Claude and GPT-5.6 Luna's answer quality — in half the time

Databricks' Adaptive Instructed-Retriever lets AI agents decide how many times to search per question, matching frontier model quality in half the time.
SiliconANGLE

Databricks adds adaptive search model to speed agent retrieval

Databricks Inc. today expanded its Adaptive Instructed-Retriever search model to speed up response times for requests from artificial intelligence agents that require multiple rounds of retrieval. The ...
InfoWorld

Databricks unveils adaptive AI retrieval model to cut search costs and latency

Adaptive Instructed-Retriever dynamically decides when queries need additional search steps, aiming to improve answer quality without driving up enterprise AI costs. Databricks on Wednesday introduced ...
InfoWorld

Databricks’ TAO method to allow LLM training with unlabeled data

Test-time Adaptive Optimization can be used to increase the efficiency of inexpensive models, such as Llama, the company said. Data lakehouse provider Databricks has unveiled a new large language ...