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Practical AI: Machine Learning, Data Science, LLM
Apple Intelligence & Advanced RAG
Jun 25, 2024
45:08
Snipd AI
Discussing Apple's new intelligence announcement and the evolution of AI in enterprises. Exploring Advanced RAG for productive AI pipelines and the challenges of integrating AI into software operations. Delving into the possibilities and pitfalls of chat GPT and the importance of controlling biases in AI outputs.
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Quick takeaways
- Utilizing reliable data enhances the performance of Large Language Models.
- RAG methodologies optimize retrieval processes through advanced techniques like reranking models.
Deep dives
Limitations of Large Language Models (LLMs)
Utilizing Large Language Models (LLMs) like chat GPT may seem like a magical solution initially, but prolonged use reveals limitations such as susceptibility to issues like hallucinations. To counter this, providing LLMs with reliable, up-to-date data grounded in the right context can enhance their performance, ensuring accurate responses. Neo4j's exploration of pairing LLMs with Knowledge Graphs and Vector Search demonstrates a strategic approach to optimize results and address challenges.
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Discover
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Listen to the best highlights from the podcasts you love and dive into the full episode