Articles by Alicia
6 articles
In just the last year, rapid advancements in AI technologies, particularly in natural language processing (NLP), have dramatically impacted virtually every industry. Most recently, large language models (LLMs) have become front and center – driven by the overwhelming popularity of OpenAI's ChatGPT.
Accurately projecting and communicating shipment details in freight and logistics is paramount for successful, safe delivery across the vast supply chain.
The COVID-19 pandemic fundamentally changed how consumers shop, driving more consumers than ever to transact online with traditionally brick-and-mortar retailers. While these economic forces have affected all retail, perhaps none was more profoundly disrupted than the grocery sector.
Customer experience (CX) teams often face a complicated puzzle when it comes to budgetary decisions and resource allocation within their organizations.
Proving the economic value of AI projects remains paramount to the success and continuation of any machine learning-related project. As more companies adopt AI technologies, measuring these projects' success is increasingly important – unfortunately, proving this value is proving anything but straightforward.
Although not often regarded as a technological first-mover, the insurance industry has recently seen robust, even rapid, adoption and deployment of AI capabilities, particularly in those related to natural language processing (NLP).
