Overview
Content: From ChatGPT, Claude and Gemini proprietary GenAI platforms are expanding rapidly. Meanwhile, open-source models such as Mistral, DeepSeek, and LLaMA offer flexible and cost-effective alternatives.
In this learning pill, we’ll break down the key differences, compare leading options, and help you choose the best fit for your team’s needs and goals.
Estimated Duration: 30 mins
Access: the content is FREE and with unlimited access
Entry Requirements: None
For more info contact: [email protected]
Course Description & Learning Outcomes
In this Learning Pill, learners will learn:
The Difference between open-source and proprietary LLMs, a topic described as "highly discussed but very confusing".
Cost Implications: A crucial learning outcome will be recognizing the "hidden costs" of open-source models, and how proprietary models, despite upfront costs, can reduce other departmental expenses through included support and cloud services.
Data Privacy and Control: Participants will understand that open-source models offer full control over data, making them often preferred for regulated industries (e.g., finance, healthcare, oil and gas, telecommunication, governmental bodies), while proprietary models may involve data going offsite with less user control.
Strategic Implementation: A key takeaway will be that "a model is not going to do it all," promoting the adoption of a "hybrid approach" or "portfolio of models". This strategy involves using open-source models where more control or specific compliance is needed, and proprietary models for other use cases or departments, potentially leading to "significant resource savings".
Factors Beyond Cost: Learners will grasp that the decision isn't solely about financial cost but also about GPU availability, specific use cases, internal skills capacity, and access to skilled personnel.
Recommended Prerequisites
No Prerequisites needed
Schedule
Date: 09 Jul 2025, Wednesday
Time: 1:58 PM - 2:58 PM (GMT +8:00) Kuala Lumpur, Singapore
Location: 32 Carpenter Street, 059911
