From spotting trends in financial markets to empowering better client experiences, natural language processing (NLP) is transforming the finance sector.
CloudFactory Blog
Learn 3 key takeaways from our latest LinkedIn Live event where we explored what it takes to combine human and machine intelligence effectively.
From fraud detection to automated loan approvals, AI is transforming the world of fintech with smoother client experiences and reduced financial risk.
Humans are necessary while automating decisions and processes with AI, machine learning, and RPA. Experts discuss the need for humans in the loop (HITL).
From faster drug discovery to robotic surgery, AI is transforming the healthcare sector with promises of improved patient care and reduced costs.
An incremental design approach to automation and machine learning affords strategic opportunities for choosing to route exceptions to machines or people.
Automation and AI hold great potential to innovate, improve, and make predictions. Here are three mistakes you’ll want to avoid.
Could the secret to developing ML be more boring than we think? It’s time to give up the quest for the perfect model.
What will 2021 bring to the world of AI and machine learning? CloudFactory CEO and founder Mark Sears shares our predictions.
How can you determine if a data labeling service will deliver quality work? How they communicate and handle quality control are key indicators.
How can you determine if a data labeling service will deliver quality work? It starts with their vetting, hiring, and training processes.
People have unconscious biases that affect hiring decisions. People also can hard-code their biases into an AI system. Humans in the loop can help.
People are involved in everything from training and testing algorithms to labeling data, conducting quality control, and monitoring automation.
Humans play a critical role throughout the AI lifecycle, from data cleaning and labeling to quality control and automation monitoring.
Developing ML models requires a lot of data and skilled people to work with it. Here’s our HITL approach for machine learning model development.
Autonomous vehicles and AI driver safety tools aren’t affordable for all. Driver Technologies made a free innovative app and model training database.
