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Open AI to partner with TSMC to make custom chips?

Open AI to partner with TSMC to make custom chips?

Introduction

OpenAI is making significant strides in developing its first custom AI chip, with plans to finalize the design in the coming months. This ambitious project aims to reduce the company’s reliance on Nvidia, which currently dominates the AI chip market with an 80% share and also compete with Nvidia

Design and Manufacturing Partnership

The ChatGPT maker is collaborating with Taiwan Semiconductor Manufacturing Company (TSMC) to fabricate its inaugural in-house chip. TSMC will manufacture the chip using its advanced 3-nanometer process technology, ensuring cutting-edge performance and efficiency.

Key aspects of the chip design include

High-bandwidth memory (HBM)

Systolic array architecture optimized for AI tasks

Extensive networking capabilities

The chip development is led by Richard Ho, a former Google engineering lead who now heads OpenAI’s 40-person in-house team.

Timeline and Production Goals

OpenAI’s timeline for chip development is ambitious yet structured:

Early 2025

Finalization of chip design

Mid-2025

Tape-out process at TSMC

2026

Target for mass production

The initial phase, known as “taping out,” is a critical and costly step, typically requiring tens of millions of dollars and about six months to produce a prototype.

Strategic Implications

This move into custom chip design carries significant strategic importance for OpenAI:

Reduced dependence on Nvidia

Enhanced negotiating power with chip suppliers

Greater control over AI infrastructure and costs

Initially, the chip will have a limited role within OpenAI’s infrastructure, primarily focused on running AI models. However, future iterations are expected to have broader capabilities, including AI model training.

Challenges and Investments

Developing a custom AI chip is a complex and expensive endeavor. The total cost, including software and peripherals, could approach $1 billion. OpenAI faces several challenges:

Ensuring the chip functions correctly on the first tape-out

Expanding the engineering team to support large-scale production

Building a reliable software ecosystem to complement the hardware

Conclusion

Despite these challenges, OpenAI’s investment in custom chip development underscores its commitment to technological independence and innovation in AI hardware.

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