Everyone’s chasing bigger AI. The real opportunity? 

Smarter scaling.

Distributed computing is quietly rewriting the rules of what’s possible—
not just for tech giants, but for everyone building with AI.

We’re talking cost. We’re talking scale. And we’re definitely talking disruption.

Tom Curry, CEO and Co-Founder of DistributeAI, joins us as we dig into the future of distributed power and practical AI performance.

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Topics Covered in This Episode:

1. Distributed Computing for Affordable AI
2. Open Source vs. Proprietary AI Models
3. GPU Demand and Compute Limitations
4. Edge Computing and Privacy Concerns
5. Small Business AI Compute Solutions
6. Future Trends in AI Model Sizes
7. Impact of Open Source AI Dominance

Timestamps:
00:00 Rising Importance of AI Compute

06:21 AI Model Resource Constraints

09:24 AI Models' Efficiency vs. Complexity

12:24 Edge Compute for Daily Tasks

16:00 Compute Cost Drives AI Market

16:58 AI Models: Balancing Cost and Innovation

20:43 Adaptability in Rapidly Changing Business

Keywords:
Distributed computing, compute, GPUs, generative AI, ChatGPT, large language models, open source models, proprietary models, affordable AI, scale, Distribute AI, spare compute, Tom Curry, mid-level businesses, accessible AI ecosystem, API access, power grid, NVIDIA, OpenAI, tokens, chain of thought, models size, reasoning models, edge computing, cell phones analogy, data privacy, DeepSeek, Google Gemini 3, Eloscores, open models, hybrid models, centralized model, OpenAI strategy, Anthropic, Claw tokens, commoditization, applications, government contracts, integration, UX and UI, technology advancements, private source AI, business leaders, AI deployment strategy, flexibility in AI.

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