As the saying goes, with great risk comes great reward.
Because of the profound complexity and intricate dependencies between hardware and software, developing a custom AI chip is one of the most capital-intensive and high-risk endeavors in the semiconductor industry today.
The total project cost can easily exceed $100 million on advanced process nodes. Those costs rise dramatically if the design has to go back to the foundry for a silicon respin. And the worst-case scenarios — missed funding opportunities, time-to-market delays, and the resulting loss of market share — can be catastrophic.
And yet, an increasing number of chipmakers and startups are undaunted by these risks because of the significant rewards they stand to gain. But there is little margin for error, and getting it right the first time has become a technical, financial, and business imperative.
Here are ten proven strategies for achieving first-pass silicon success when developing AI chips: