Deep learning has yielded some fantastic results for basic natural language processing (NLP) functions such as named entity recognition (NER), document classification and sentiment analysis ...

Machine learning is concerned with one aspect of this: given some AI problem that can be described in discrete terms (e.g. out of a particular set of actions, which one is the right one), and ...

For a while, we were the only evaluation tool for unstructured AI, like deep learning models. Erstwhile before the LLM moment, people were fine tuning mostly Bert-style models for entity detection. We ...

The wide array of uses cases is fueling a global NLP market that Fortune Business Insights is forecasting will jump from $20.98 billion last year to $127.26 billion in 2028. More recently, the drive ...

MLOps attempts to streamline the process of building and managing machine learning models by ... “It’s often 10x faster to repeatedly build production-ready NLP and LLM services ...

LONDON, Oct. 12, 2023 — TitanML has secured $2.8 million in pre-seed funding led by Octopus Ventures alongside deep tech-focused angel investors. The round is timed as the team publicly launches Titan ...

The goal is to ensure all the NLP labeling can occur on a single platform instead of using spreadsheets for one type and open-source tools for another.” Evaluating quality of LLM responses ...

The Intel AI Lab has open-sourced a library for natural language processing to help researchers and developers give conversational agents like chatbots and virtual assistants the smarts necessary ...

"Datadog LLM Observability provides the deep visibility needed to help teams manage and understand performance, detect drifts or biases, and resolve issues before they have a significant impact on ...