A collection of articles and advice for organizations thinking of using artificial intelligence and machine learning to turn data into insight.
How to deploy an ML model and use it in your data pipeline as a web service. Operationalizing a model refers to the process of deploying a machine learning model (ML) to be used with a client application such as… Read More »Operationalizing an ML model in the cloud
A technical overview of our approach to overcoming the challenges of unsupervised text classification. Text Classification is a very popular and well explored research and application area in machine learning. There are more and more sophisticated ways to classify text… Read More »Categorizing multilingual open-ended survey responses and social media comments using Natural Language Processing
NovaceneAI collaborates with CMC Microsystems to bring the power of quantum computing to business users through an easy-to-use interface. Big Data Needs Big Computers For years now, the cloud made it possible for subject matter experts to take advantage of… Read More »Democratizing Quantum AI
How natural language processing can enable a broader understanding between governments and citizens. Digital technologies can help us collaborate… Social media, online consultations, discussion forums and online surveys provide researchers with a massive source of qualitative data. These technologies are… Read More »Harvesting Insights from Text
The user interface brings new technologies to the masses. It happened over and over throughout computer history. AI, machine learning, quantum and future technologies will be no exceptions. Every New Technology Starts as User-Unfriendly Maybe it is because it’s been… Read More »From ENIAC to Quantum
AI business applications are here to stay. Businesses are using AI to improve operations, increase value to customers and reduce cost. But it can be hard to get started implementing AI when opportunities aren’t clear. This post presents a few… Read More »Using AI in your Organization: 6 Practical Examples
The technical and scientific nature of artificial intelligence technologies make AI an intimidating topic for most people. And the hype around what AI can do blurs the lines between reality and science fiction. While you might think that AI is… Read More »Five AI Definitions Every Business Leader Should Know
Natural Language Processing helps subject matter experts reduce the amount of time they spend analyzing text. Some of the best tools however require engineers to set up and configure. This dependency on IT delays projects because of competing priorities. When… Read More »Text Analysis: Understand sentiment, topics and tone without coding
Training Machine Learning (ML) models can take a lot of time and consume a lot of computing power. This can be also true for testing the models if your datasets are large enough. These operations are resource-hungry and can paralyze… Read More »Training Machine Learning Models in the Cloud
Insight Automation Platforms have the work cut out for them: delivering on the promise to fully automate the process of going from data to insight requires a significant engineering effort and close collaboration across multidisciplinary teams that rarely work together.… Read More »Insight Automation: The Future of AI in the Enterprise
