Author name: tirta

Few-shot prompting leverages few labeled examples to guide LLMs towards desired outputs. By providing a few examples and specific instructions, […]

Shot-based prompting leverages individual training instances to enhance AI’s performance on specific tasks. Instead of relying on massive datasets, this

Zero-shot learning trains models to recognize classes unseen during training, while few-shot requires only a handful of labeled examples per

Zero-shot prompts enable AI models to perform tasks on unseen data by providing instructions in natural language. This is achieved

Transfer learning utilizes pre-trained models to solve new tasks, while few-shot learning tackles tasks with limited training examples. Transfer learning

One shot learning, a subset of few-shot learning in machine learning, enables models to learn from a single example or

Academic-industry collaborations are essential in the innovation ecosystem, fostering knowledge exchange and driving technological advancements. Universities, research institutions, and technology

Value-laden meaning refers to the inherent value judgments and subjective interpretations embedded within language and communication. It acknowledges that words

Utilitarian organizations attract individuals driven by altruism and consequentialist thinking to advocate for social good. They provide platforms for collective

Cooperative binding is a significant phenomenon in biosystems where multiple ligands bind to a multi-subunit protein. This occurs when the

Legitimate peripheral participation (LPP) is a theory that describes how individuals learn by participating in the activities of a community.

Effective collaboration, built on trust, communication, and shared goals, yields outcomes that surpass individual contributions. It fosters synergy, knowledge exchange,