Baidu's rationale for developing its own silicon isn't to control the supply chain or dominate pre-training. It's a strategic focus on the AI inference market, which the CFO states accounts for 80% of incremental compute demand. Their chips are optimized for this specific task, creating a positive network effect with their cloud business.

Broadcom's AI revenue is increasing exponentially, with projections exceeding $10 billion for next year. This places its custom ASIC (Application-Specific Integrated Circuit) business on a growth curve remarkably similar to where market leader NVIDIA was three years prior, signaling significant upside potential.

Google is abandoning its single-line TPU strategy, now working with both Broadcom and MediaTek on different, specialized TPU designs. This reflects an industry-wide realization that no single chip can be optimal for the diverse and rapidly evolving landscape of AI tasks.

For its next-generation V7 TPU AI chip, Google is diversifying its supply chain. It's retaining incumbent Broadcom for the complex 'training' version while bringing in low-cost entrant Mediatek for the 'inference' version. This sophisticated strategy mitigates supply risk while keeping critical IP with a trusted partner.

Despite its high valuation post-IPO, AI chipmaker Cerebras's long-term strategy focuses on inference, not just training. The bet is that inference will become a much larger segment of the AI compute market. By developing chips specifically optimized for this task, Cerebras aims to take significant market share from NVIDIA.

Contrary to expectations that rivals would erode its lead, Nvidia's AI inference chip market share grew from 66% to 74% in the past year. This is significant as inference now represents the majority (~60%) of AI workloads and revenue, solidifying Nvidia's dominance in the most lucrative segment of the market.

The AI hardware market isn't just about NVIDIA. It's a battle between NVIDIA's full-stack system, Google's powerful TPU, and a combined effort where Broadcom builds the networking fabric and custom ASICs, with AMD serving as a plug-in alternative chip.

Anthropic's choice to purchase Google's TPUs via Broadcom, rather than directly or by designing its own chips, indicates a new phase in the AI hardware market. It highlights the rise of specialized manufacturers as key suppliers, creating a more complex and diversified hardware ecosystem beyond just Nvidia and the major AI labs.

Broadcom is solidifying its position as the key alternative to NVIDIA's locked-in ecosystem by becoming the preferred design partner for custom AI chips (ASICs). Its deep partnerships with major players like Anthropic and OpenAI to develop specialized hardware highlight a growing demand for tailored, cost-efficient silicon.