BlockBeats News, July 26th, Deedy, an investor in Anthropic, pointed out that all startups developing next-generation AI chips are trying to challenge NVIDIA's dominance in different ways, aiming to tackle the fundamental issue of "data movement." Six differentiated challenge approaches include: eliminating DRAM (Groq, already acquired by NVIDIA for $20 billion), eliminating interconnect (Cerebras, IPO'd at around $48 billion market cap), eliminating compute/memory separation (d-Matrix), eliminating server-centric architecture (Majestic), eliminating generality (Etched, Taalas, MatX), and eliminating the $4 billion lithography machine (Substrate).

The IPO and acquisition prices of Cerebras and Groq have set a pricing benchmark for the entire AI chip track, while Etched's valuation doubled this week to $10.3 billion, erupting from stealth mode in just three weeks, further confirming that capital is rapidly reassessing the pricing in this track. Among the 18 major startups, private companies have a combined paper value of around $58 billion, with a public market cap of about $48 billion, covering inference, training/new architecture, systems, fabs, and lithography, among other subdirections.

Each approach is challenging the core assumption of NVIDIA's GPU architecture — that the movement of data between the compute unit and memory consumes both time and energy. Groq replaces DRAM with SRAM to completely eliminate memory level latency, Cerebras eliminates chip-to-chip interconnect bottlenecks at the wafer level, d-Matrix performs calculations directly in memory, and Etched sacrifices generality to design hardware specifically for the Transformer architecture. The AI chip startup ecosystem has evolved from a singular GPU replacement narrative to a multi-point attack at the architecture level. NVIDIA's acquisition of Groq actively engages in this process, indicating its deep understanding that the core of next-generation competition is no longer peak computing power but the complete reconstruction of data movement efficiency.