Retrieval-augmented generation (RAG) systems boost AI question-answering but suffer from hallucinations, eroding trust in enterprise uses like support and research. Mitigation strategies include enhanced retrieval, prompt engineering, guardrails, human feedback, fine-tuning, and detection techniques. These innovations promote reliable, ethical AI deployment across sectors.
OpenAI's o3 model, released in April 2025, revolutionizes LLM app development with multimodal input handling (text, images, audio) and structured JSON outputs for reliability. It enables applications in healthcare, transportation, and e-commerce, despite challenges like latency. Future integrations promise advanced, decentralized AI ecosystems.
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Google's NotebookLM is revolutionizing education by enabling teachers to generate summaries, quizzes, and interactive podcasts from uploaded documents, particularly in data science and beyond. It fosters personalized, engaging learning while reducing workload, though challenges like accuracy and privacy persist. As features expand, it promises broader adoption in classrooms.
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