ChatGPT plugins are a crucial way to help you get more reliable and accurate information out of ChatGPT. Hallucinations can be common when prompting so using ChatGPT plugins helps to reduce them. ScholarAI is one plugin we recommend to help with those issues. Damon Burrow, Co-Founder & CSO of ScholarAI, joins us to talk about the ScholarAI plugin and how to get better information out of ChatGPT.

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Timestamps:
[00:01:30] Daily AI news
[00:04:40] About Damon and ScholarAI
[00:08:10] ScholarAI allows for up-to-date info
[00:13:30] ScholarAI plugin walkthrough
[00:18:05] Other use cases for ScholarAI
[00:21:05] Plugins to pair with ScholarAI
[00:22:00] How ScholarAI came to be
[00:25:00] Audience questions
[00:28:25] Final takeaway on ScholarAI

Topics Covered in This Episode:
1. Importance of Accuracy in AI Systems
2. ScholarAI Plugin for Reliable Information Retrieval
3. ScholarAI Plugin Demonstration
4. Addressing Hallucinations and Lack of Transparency in AI Models
5. Infusing Trust and Accuracy in AI Systems with ScholarAI

Keywords:
generative AI systems, electricity consumption, water for cooling, energy consumption, Argentina's energy usage, electricity usage in AI systems, power usage in generative AI, NVIDIA, AI and ML research, radiation therapy, cancer tumors, large language models, research and commercial settings, accuracy in AI, ScholarAI systems, creativity in generative AI, grounding in truth, domain expertise, peer-reviewed literature, semantic search, synthesizing information, multiple sources, BARD assistant, drafting emails, negotiating job offers, integration into smartphones, data centers, "show me diagrams", visual learning, simplifying information, ChatGPT, ScholarAI plugin, CheckCVT, citing papers, real-time information access, cutoff dates, context window, providing necessary information for ChatGPT, accessing abstracts, paper summaries, user demographics, due diligence, assessing technologies, mergers and acquisitions, journalists, COVID-19 pandemic, misinformation, hallucinations in language models, trust in AI-generated responses, transparency, tethering AI output to reliable sources, hyperlinks to sources, professional knowledge work

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