Everyone's talking about the AI datacenter boom right now. Billion dollar deals here, hundred billion dollar deals there. Well, why do data centers matter? It turns out, AI inference (actually calling the AI and running it) is the hidden bottleneck slowing down every AI application you use (and new stuff yet to be released).

In this episode, Kwasi Ankomah from SambaNova Systems explains why running AI models efficiently matters more than you think, how their revolutionary chip architecture delivers 700+ tokens per second, and why AI agents are about to make this problem 10x worse.

💡 This episode is sponsored by Gladia's Solaria - the speech-to-text API built for real-world voice AI. With sub-270ms latency, 100+ languages supported, and 94% accuracy even in noisy environments, it's the backbone powering voice agents that actually work. Learn more at gladia.io/solaria

🔗 Key Links:

• SambaNova Cloud: https://cloud.sambanova.ai

• Check out Solaria speech to text API: https://www.gladia.io/solaria

• Subscribe to The Neuron newsletter: https://theneuron.ai

🎯 What You'll Learn:

• Why inference speed matters more than model size

• How SambaNova runs massive models on 90% less power

• Why AI agents use 10-20x more tokens

• The best open source models right now