Ready to Begin Your AI Journey? 3 Steps Financial Advisors Can Take Now
Wealth management is benefitting from recent advances in AI. Alerts can now be generated for when financial status’ change. In this Barron’s article, Jen Cole shares how deep learning is ideal for complex data analysis. Jen state’s that “Robo-advisors are good examples of deep learning at work. They analyze a customer’s risk tolerance and current financial trends to make investment recommendations.”
5 Things Your AI/ML Training Data Is Lacking
Erik Vogt shares his insights on ensuring the data that AI technology companies deploy contains inclusive data and runs efficiently. He identified five key areas that are often common weaknesses for AI teams and how to improve in these areas.
Why Data Remains the Greatest Challenge for Machine Learning Projects
Quality data is both a catalyst to successful AI deployment and the biggest challenge companies will face. VentureBeat looked to our 2022 State of AI Report for the insights behind why and how to overcome these challenges. Sujatha Sagiraju also shared advice and observations for ensuring appropriate steps are taken in obtaining high quality data.
Why the Biggest Obstacle to Machine Learning Initiatives is Data
CIO Applications Europe looked at our 2022 State of AI Report for insights into why successful AI is dependent on quality data. The identified areas of focus include organisational structure, corporate policy and leveraging synthetic data and human-in-the-loop evaluation.
Pre-Labeled Datasets Are Key to Building High-Quality ML Models
Jen Cole shares her thoughts on the importance of pre-labeled datasets (PLDs). By leveraging PLDs, data is free from personally identifiable information (PII) and ready to be used to train a machine learning module. Jen also shares our solution to making sure our PLDs are free from PII and ready to be used for various projects.
Big Data Industry Predictions for 2023
Inside Big Data has shared their predictions for what’s in store for AI, technology, and data in 2023. Sujatha Sagiraju shares her predictions on speed and quality of data and why companies that normally consider these two elements separately should be focusing on both in tandem to achieve success in the new year.