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AI + all your data = good move or bad move? Sure, AI can do data crunching wonders when we pair the two together. But, what challenges and conflicts should we be aware of before doing so? Aakash Indurkhya, Head of Product at Virtualitics, joins us to discuss AI and data analysis.

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Related Episodes:
Ep 145: NVIDIA Leader Talks GenAI + Data: Unlocking new ways to interact with our world
Ep 142: AI is Changing Data Analysis: Insider Tips

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Topics Covered in This Episode:
1. Generative AI Technology and Data Visualization
2. Role of AI in Data Analysis
3. Statistics Paradox and Data Collection Challenges
4. Importance of Hands-On Experience and Collaboration

Timestamps:
01:30 Daily AI news
04:30 About Aakash and Virtualitics
08:51 Stress of data utilization despite its value.
10:39 Data layers may disagree, causing decision paralysis.
15:33 Generative AI aids human-driven data analytics.
17:38 RAG concept crucial for tracing data decisions.
24:06 Beginning data analysis requires tools, exploration, openness.
26:43 Future of jobs with technology, data and humans.
29:21 Communicate with experts for effective problem-solving.

Keywords:
data in the age of generative AI, large language models, OpenAI model spec, Google DeepMind AlphaFold 3, protein behavior prediction, Zapier Central, AI bots without coding, Virtualisix, data-driven decisions, industry-specific decision intelligence, data abundance paradox, ChatGPT technology, changes in data collection, Apple, Google, maintenance data for HVAC systems, human role in data analysis, industry-specific expertise, generative AI in data visualization, RAG technology, conversational interfaces in generative AI, sensitive data handling, GPT language models, Virtualitix AI platform, decision intelligence apps, data-driven decision paradox, decision congestion, common language in data analysis, data quality, decision socialization.

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