Latency demands sustain hardware infrastructure growth
The guest argued that hardware remains the most efficient way to manage low-latency, high-throughput data, preventing highly latency-sensitive industries from moving entirely to the cloud.
The argument
Financial institutions like JPMorgan and Goldman Sachs rely on dedicated hardware to avoid the latency penalties of the cloud, which directly impact profitability. This structural demand, combined with the AI GPU boom, has left hardware supply chains heavily backordered.
The thesis, stress-tested
✓ What validates it
- ✓Continued capital expenditure growth in on-premise hardware by major financial institutions
- ✓Dell or other hardware manufacturers reporting sustained backlogs for high-performance servers
▸ Risks discussed
- ▸Cloud providers improving latency to close the gap with on-premise hardware
- ▸Easing of supply chain bottlenecks reducing hardware pricing power
Hear it yourself
"And so with Methos, these are vulnerabilities where? Sorry? These are vulnerabilities in your own code base? In our own code base? In our own code base. Oh, wow. So Methos was not oversold. It was legit. The capabilities of AI in being able to assess vulnerabilities and code are real. Not just that, if you put it on ultra mode, which is persistent thinking, so it keeps trying until it gets an answer, you can actually daisy chain vulnerabilities, I. E. Finding a new attack path into your comp into your vulnerabilities. Now, we pride ourselves as a top percentile of companies that test our code because we're in a cyber security business."
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