IBM Granite has new experimental features for developers to test

IBM has open-sourced a pair of prototype tools for detecting hallucinations in RAG applications and estimating model uncertainty. If feedback is positive, these capabilities could be added to the next Granite release.

IBM has open-sourced a pair of prototype tools for detecting hallucinations in RAG applications and estimating model uncertainty. If feedback is positive, these capabilities could be added to the next Granite release.

The promise of large language models is offset by one notable issue: they can be unpredictable. It’s not always easy to tell when information an LLM just generated is accurate or grounded on trusted documents.

IBM Research has designed a pair of open-source low-rank adapters, or LoRAs, to give developers more control over AI content generation. These experimental adapters can be swapped in and out of IBM’s Granite 3.0 Instruct 8B model to provide an additional quality check. The LoRAs are available on Hugging Face, and if they prove to be useful, the data used to train them will be incorporated into Granite 3.1.

The LoRAs are part of a new IBM Research playground called Granite Experiments for testing ideas to see if AI developers see value in them. If the two experiments are successful, researchers plan to put out new open-source features for community testing.

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