FarmHopper

DeepSeek is developing its own chips, and VeriSilicon has gained another customer.

I've been discussing Huawei's τ scaling (temporal scaling) with people recently, and noticed the conversation tends to stay at the surface level without reaching its substance — likely because many participants don't come from an EE background and aren't familiar with the classical meaning of τ in circuit theory. The very first time constant you learn in a circuits course is τ = RC: the resistance of a wire multiplied by its capacitance gives the order of magnitude of the time a signal needs to traverse that wire. The longer the wire, the greater the resistance and capacitance, and the slower

Recently, in discussions about Huawei's τ scaling (time scaling), I noticed that the conversations have remained superficial, without touching its essence. This is probably because many friends don't have an EE background and are unaware of the classic meaning of τ in circuits. The first time constant taught in circuit theory is τ = RC—the resistance of a wire multiplied by its capacitance gives the order of magnitude of the time it takes for a signal to travel through that wire. The longer the wire, the larger the resistance and capacitance, and the slower the signal. Within this framework, t

Bernstein raised its target price for Haiguang Information from 280 yuan to 450 yuan yesterday. The core logic is that Agentic AI is overturning the "GPU-dominated AI capex" pattern of the past four years, with CPUs shifting from supporting roles back to leading roles. The global server CPU TAM is expected to expand from $39 billion in 2025 to $223 billion in 2030, a sixfold increase. As the world's only x86 server CPU supplier outside of Intel and AMD, Haiguang is the most direct beneficiary in China of this structural shift.
First, let's look at why Agentic AI's demand for CPUs is completely