The Age of Neural Inference

For the past decade, the AI narrative has been dominated by training. Who has the biggest cluster? Who has the most parameters? But as we enter 2026, the paradigm is shifting. We are entering the Age of Inference.

The Shift to "Thinking" Models

With the release of Gemini 3.0 and its reasoning capabilities, the compute cost is moving from the data center training run to the "thought loop" at inference time. Agents don't just predict the next token; they plan, reflect, and iterate.

Inference is no longer just playback. It is an active, computational process of reasoning.

Hardware Implications

This shift changes everything for hardware. Memory bandwidth (HBM) becomes king. Latency matters more than pure throughput.

What We Are Watching

• Edge NPUs: Apple, AMD, and Intel are racing to bring high-performance inference to the laptop.
• Specialized Groq/Cerebras Chips: Will ASIC-style inference win over general-purpose GPUs?
• Local Labs: How to build a home server capable of running a 70B parameter reasoning model.

Our Mission

Neural Inference is dedicated to this frontier. We will cover:

1. Agents: How to build and deploy them.
2. LLMs: Benchmarks of the latest "thinking" models.
3. Hardware: Reviews of gear that powers it all.

Welcome to the future.