Signal
Intelligence
Have you ever tried keeping up with the AI industry? It's a massive wall of noise. SGNL Intelligence is fixing that using something completely fascinating called GIKE. We send out a literal swarm of AI agents to process every claim in tech, and then a human editor steps into the loop to verify the truth. We don't just summarize the news; we find the signal.
See how GIKE works under the hood →- Connecting the Dots: Why AMD Is the Only Company That Doesn't Need an Acquisition for the SRAM Inference Revolution
The AI inference stack is splitting in two. NVIDIA bought Groq for SRAM. AWS rents Cerebras. But AMD already owns the deepest SRAM Compute-In-Memory IP in the industry through Xilinx — and they're the only company with GPU + FPGA/CIM + NPU + CPU under one roof. They just haven't connected the dots yet.
- Michael Burry vs NVIDIA: The Bear Case Hidden in the 10-K
Michael Burry's NVIDIA bear case has evolved from Twitter hot takes to forensic 10-K analysis. We trace his thesis through three layers: the shovel-seller narrative, the NVIDIA-OpenAI circular capital flow, and what the actual SEC filings reveal about $117B in supply commitments, permanently extending cash cycles, and hidden compensation costs. Then we stress-test it against NVIDIA's record-breaking fundamentals.
- The Machine That Writes the Machine: AI Kernels Surpass a Decade of Human Expertise
DoubleAI's WarpSpeed rewrote every kernel in NVIDIA's cuGraph library and beat all of them -- 3.6x average speedup with 100% correctness. General-purpose LLMs hit only 56-59%. Here's why this matters: AI hasn't just learned to code -- it's learned to write the code that makes computers fast.
- Four Power Plays Reshaping AI Hardware Right Now
AWS buys Cerebras for speed but not its moat. A new optical consortium draws battle lines that exclude Google and AWS. AI agents design chips overnight. And Oracle's $553B backlog is the most extreme demand-price disconnect in tech. Four stories. One thesis: the AI stack is fragmenting.
- The Invisible Bottleneck: Why AI's Next Crisis Is About Light and Logic, Not GPUs
For three years, GPUs were AI's only bottleneck. Now, as clusters scale past 100,000 chips and agents replace chatbots, two invisible layers are breaking: the optical links connecting GPUs and the CPUs orchestrating AI agents. NVIDIA just bet $4B on light. Intel and AMD are sold out of server CPUs for the year. The great bottleneck rotation is underway.