The goal is to help build trust and transparency in business outcomes, the company said.
IBM has unveiled a slew of announcements designed to help businesses scale their use of AI. The company also announced the rollout of new capabilities for its Watson platform.
IBM researchers have built a hybrid question-answering system called Neuro-Symbolic-QA (NSQA) that for the first time uses neurosymbolic AI to allow an AI system to offer "and"/ "or" to its recommendations. This will ultimately position the system to perform better in real-world situations, IBM said.
"This enhanced reasoning capability comes as a result of an entirely new foundational AI method created by IBM researchers called Logical Neural Networks (LNN), IBM said.
LNNs are a modification of today's neural networks so that they become equivalent to a set of logic statements, but they also retain the original learning capability of a neural network, the company explained in a blog post.
QA is designed to meet the significant challenges in language-based AI, in particular the fact that the training of NLP models still requires massive amounts of data, it's expensive, and these models can't demonstrate true intelligence—they only share what they're already trained to know and ultimately fall apart in spontaneous, real-life situations, IBM said.
"To date, the QA system has achieved state-of-the-art results on two major industry NLP benchmarks, QALD and LC-QUAD, which is significant because it's the first time a non-deep learning based NLP method has achieved top performances on these tests," the company said.
Further, IBM said the system operates off significantly less data: A dataset of 400 questions versus the industry standard of around 10,000.
IBM said its hope is that the system will help it advance AI, including NLP models, beyond the narrow restraints of pattern-based deep learning, which offers only solutions they are trained to know. Instead, the goal is the system can demonstrate flexibility and offer solutions not included in training data as well as efficiency by using far less data, all while maintaining accuracy.
The new capabilities for Watson are designed to improve the automation of AI, provide a higher degree of precision in natural language processing, and foster greater trust in outcomes derived from AI predictions, the company said. They include:
Reading Comprehension is based on an innovative question-answering (QA) system from IBM Research. Currently in beta in IBM Watson Discovery, it is planned as a new feature that can help identify more precise answers in response to natural language queries from vast troves of complex enterprise documents. It also provides scores that indicate how confident the system is in each answer.
FAQ Extraction uses a novel NLP technique from IBM Research to automate the extraction of Q&A pairs from FAQ documents. Currently in beta in IBM Watson Assistant's search skill, it is planned as a new feature to help businesses keep virtual assistants up-to date with the latest answers and reduce the time-consuming process of manual updates.
A new intent classification model is now available in Watson Assistant. It is designed to improve a user's interactions with a virtual assistant and enables faster training times and more accurate results from less data. This can help businesses go live with virtual assistants in a few days with high accuracy.
Watson Discovery now includes support for 10 new languages including Bosnian, Croatian, Danish, Finnish, Hebrew, Hindi, Norwegian (Bokmål), Norwegian (Nynorsk), Serbian, and Swedish.
IBM also announced plans to commercialize IBM Research-developed "AI Factsheets" in Watson Studio in Cloud Pak for Data throughout 2021.
"Like nutrition labels for foods or information sheets for appliances, AI Factsheets are designed to provide information about a product's important characteristics,'' the company said. "Standardizing and publicizing this information will help build trust in AI services across the industry."
To complement this, IBM Services for AI at Scale, a new consulting offering, provides businesses with a framework, methodology, and underlying technology to guide organizations on their journey to trustworthy and ethical AI. IBM Cloud Pak for Data also has new capabilities to provide a complete foundation for AI that can run on any cloud.
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