AI is now widespread, and companies are starting to look at the real-world impact of machine learning
Author: Utilizing Tech
Shadow IT is as old as our profession, so it’s no surprise that shadow AI is becoming a major issue
AI is coming fast to the information security world, both in terms of tools and threats
Many of the tasks we perform on a daily basis are beneath our abilities, and these are the ideal targets for AI
Machine learning applications require massive datasets, but it can be challenging to build and store large amounts of unstructured data
Data science and machine learning developments can’t have an impact if they don’t get into everyone’s hands.
Data is the most important component of AI implementation, but most companies neglect data infrastructure and focus too much on the ML models
Many data scientists and ML engineers have faced the challenge of putting AI models into production, and this is the core of MLOps
AI is spreading around the world, both in terms of technology and workforces.
Demand for AI compute is growing faster than conventional systems architecture can match, so companies like Cerebras Systems are building massive special-purpose processing units.