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Companies today are drowning in policy documents, employee handbooks, and compliance guidelines—but finding specific answers quickly remains a challenge. What if employees could simply ask questions in natural language and get accurate, instant responses from an AI trained on your exact documents? In my 20-year tech career, I’ve been a catalyst for innovation, architecting scalable…
In today’s fast-paced corporate environment, employees often have questions about company policies—from attendance rules to leave entitlements and codes of conduct. While traditional intranets and HR portals provide static information, generative AI offers a more interactive way to access policy information. For over 20 years, I’ve been building the future of tech, from writing millions…
Machine learning models make various types of predictions beyond just continuous (regression) and discrete (classification). While these two are the most well-known, modern AI applications require more nuanced predictive capabilities. This tech concept explores four additional types: probabilistic, ranking, multi-label, and sequence predictions. For ~20 years now, I’ve been building the future of tech, from…
The majority of data generated today is unstructured, existing in formats such as emails, social media posts, customer reviews, and legal documents. Extracting meaningful insights from this raw text is challenging. This is where Natural Language Processing (NLP) comes in. NLP enables machines to understand, analyze, and structure unstructured text data into a more usable format. Over…
