How the Expert.ai Platform Impacts Your Approach to NL
Dive deep into the capabilities of the expert.ai Platform and the core areas it can impact for you when developing your own language model.
Search Results for Explainable
Why Financial Services Rely on NLU to Streamline Operations
With 40,000 listed stocks and more than 100,000 investment funds, how can financial services firms manually gain insight into investment data? They can’t, which leads to a great deal of investor time and manual effort being consumed by research, creating latency that can slow portfolio decision cycles, resulting in lost upside and higher risk exposure. … Continued
Expert.ai Wins “Digital Technology” Category in Ventana Research’s 14th Annual Digital Innovation Awards
Creator of artificial intelligence platform for natural language understanding recognized for exemplifying digital innovation Expert.ai (EXAI:IM), the premier artificial intelligence (AI) platform for language understanding, has won the “Digital Technology” category in Ventana Research’s 14th Annual Digital Innovation Awards. The prestigious honors recognize trailblazing vendors that contribute advancements in technology, drive change and increase value … Continued
Disambiguation: The Key to Contextualization
Machines need access to background information to cope with text ambiguities and meaning recognition. Disambiguation makes this possible.
What Knowledge Means to Your Artificial Intelligence Success
Reading is not understanding. This is a fundamental concept, but one that many choose to ignore. To read a word or phrase, you must only have a fundamental understanding of language and phonetics. To understand a word or phrase, you must not only know the language in which it is written (with all its grammatical … Continued
The Case for Symbolic AI in NLP Models
The promise of AI is, in some ways, already a reality. Thanks to natural language processing (NLP) we can successfully analyze language-based data and effectively communicate with virtual assistant machines. But these achievements often come at a high cost and require significant amounts of data, time and processing resources when driven by machine learning. Not … Continued
Anti-Money Laundering Procedures & AI: The Perfect Match
Money laundering is legally defined as transferring illegally obtained money through legitimate people or accounts so that its original source cannot be traced. The International Monetary Fund (IMF) estimated in December, 2018 the criminal proceeds laundered annually between 2 and 5 percent of global GDP, or $1.6 to $4 trillion a year. The profits of … Continued
How to Remove Pigeonholing from Your Classification Process
If there is a single task that best represents natural language processing (NLP) problems, it is document classification. Generations of NLP techniques were first tested on this problem, including simple algorithms (e.g., Bayes classifiers and K-Nearest Neighbor), machine learning, neural networks and recent advanced deep learning models. Today, it remains a test field for most … Continued
How We Built a Better Solution to the Misinformation Epidemic
This work was conducted in the context of project Co-inform, funded by the EU under grant 770302. Further information, including details on the architecture, implementation, and experimental results can be found in our paper Linked Credibility Reviews for Explainable Misinformation Detection, which was awarded Best Research Paper at the International Semantic Web Conference, held in November 2020. Both our ISWC 2020 talk and a … Continued
Do You Trust Your AI Algorithm?
The growth of artificial intelligence is incredible to watch. We have seen adoption in nearly every industry vertical to applications and systems we never thought possible. But while the AI possibilities grow by the day, our trust in them has stagnated. Given how pervasive AI has become, many consumers simply take it for granted. As … Continued
