Business Physics AI Lab

Category: AI Article

  • Purple Team Trail: Work with AI

    Purple Team Trail: Work with AI

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    Business Physics
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    The following is a series of exchanges by members of the Business Physics AI Lab Team: Thomas Hormaza Dow, Vinay Kumar, Hichem Benzair, Aboubakar Samake, Ann Lockquell as well as our AI Agents, Charlie and Lena. How the Business Physics AI Lab preserves judgment in human–AI software development Many teams are now using AI to generate…

  • Staying Current with AI: Habits of a Lifelong Learner

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    Hichem Benzair
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    Editor’s Note: This article is based on an interview with Stéphane Paquet, AI Project Lead at Champlain College Saint-Lambert and AI Certificate Coordinator. The responses have been summarized for clarity and brevity and are not word-for-word reproductions of the original conversation. The ideas reflect the speaker’s perspective as of the time of the interview. Question:…

  • The Illusion of Conversation: Rethinking AI Interfaces in Education

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    Hichem Benzair
    in

    Editor’s Note: This article is based on an interview with Stéphane Paquet, AI Project Lead at Champlain College Saint-Lambert and AI Certificate Coordinator. The responses have been summarized for clarity and brevity and are not word-for-word reproductions of the original conversation. The ideas reflect the speaker’s perspective as of the time of the interview. Question:…

  • Writing for AI: The New Literacy We All Need

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    by

    Hichem Benzair
    in

    Editor’s Note: This article is based on an interview with Stéphane Paquet, AI Project Lead at Champlain College Saint-Lambert and AI Certificate Coordinator. The responses have been summarized for clarity and brevity and are not word-for-word reproductions of the original conversation. The ideas reflect the speaker’s perspective as of the time of the interview. Question:…

  • Rethinking Education in the Age of AI: What and How We Teach

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    by

    Hichem Benzair
    in

    Editor’s Note: This article is based on an interview with Stéphane Paquet, AI Project Lead at Champlain College Saint-Lambert and AI Certificate Coordinator. The responses have been summarized for clarity and brevity and are not word-for-word reproductions of the original conversation. The ideas reflect the speaker’s perspective as of the time of the interview. Question:…

  • Understanding AI Hallucinations

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    Thomas Bedard
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    AI hallucinations are a modern artificial intelligence problem that makes AI models generate incorrect, fabricated, or nonsensical information. Let’s find out why this happens and why they matter. What are AI Hallucinations? AI hallucinations happen when AI systems produce content that has no basis in their training data or doesn’t align with reality. These errors aren’t random…

  • What Are Vector Databases?

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    Hichem Benzair
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    Regular Databases = Rows and Columns Imagine a spreadsheet that keeps track of all the student clubs at Champlain College: id name category room 1 Anime Club Media C-102 2 Art Club Creative C-103 3 Robotics Team Tech C-108 4 Champlain Music Society Creative C-109 With this kind of relational database, you can basically ask:…

  • Understanding Context Window in AI

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    Hichem Benzair
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    The context window in AI refers to the maximum amount of text or data an AI model can process in a single interaction. It defines how much information AI can “remember” at once to generate meaningful responses. Analogy: Imagine having a short-term memory limit while reading a book.If you can only remember the last 2…

  • Context Windows & Tokens in AI: A Simple Explanation

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    Thomas Bedard
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    Context windows and tokens are two foundational concepts in AI, especially in Large Language Models (LLMs). Understanding these concepts will make more sense of why AI models seem to “forget” parts of the conversation once developed enough as well as why complex prompts can be misinterpreted by the model. What are Tokens ? In AI,…

  • Bias Mitigation in AI

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    Hichem Benzair
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    AI models can unintentionally develop biases based on the data they are trained on. Bias mitigation ensures AI treats all users fairly by identifying, correcting, and testing for biases. Identifying Biases in AI Bias in AI happens when models favor certain groups over others due to imbalanced or flawed training data. Examples: How to Identify…

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