Malware reads its C2 address out of a poem
PoeLLM reads its command-and-control address out of a poem. The malware, an ELF binary named libgcrypt , pulls four words or phrases from a poem tit…
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When the AI Gateway Becomes the Weakest Link: Command Execution in LiteLLM's MCP Test Endpoints
When the AI Gateway Becomes the Weakest Link: Command Execution in LiteLLM's MCP Test Endpoints AI gateways have quietly become production infrastru…
AMD Bets $8.2B on World Models and Fei-Fei Li
AMD just paid $8.2 billion for World Labs, a startup most people haven't heard of, to get its hands on spatial-intelligence models and the researche…
AI Gateways Are Becoming Attack Surface: Measuring Exposed LiteLLM Deployments
AI Gateways Are Becoming Attack Surface: Measuring Exposed LiteLLM Deployments A new category of infrastructure has quietly joined the list of thing…
33,005 Internet-Reachable LiteLLM Gateways: Measuring the AI Gateway Attack Surface After CVE-2026-59822
33,005 Internet-Reachable LiteLLM Gateways: Measuring the AI Gateway Attack Surface After CVE-2026-59822 CVE-2026-59822 is an authentication bypass…
Why LLM Load Tests Are Costing You Thousands
You kick off a load test on your OpenAI integration. By the time it fails at 100,000 requests, you've spent $3,000 on tokens. The failure wasn't in…
When Power Costs Rise, Data Centers Need to Know Where Every Megawatt Is Going
Electricity is becoming one of the defining operating constraints of the AI data center expansion. Recent reporting around the PJM Interconnection h…
LLM Load Testing Is Burning Your API Budget
In 2026, you kick off a stress run against your OpenAI integration. The scenario is straightforward: simulate 100,000 requests at peak concurrency,…
Nvidia is buying power, not just selling GPUs
The Nvidia Cloverleaf data center partnership announced on Friday tells you where the real constraint in AI has moved, and it is not the chip. TechC…
The Meter Is Always Running
The Meter Is Always Running For forty years, enterprise software rested on a comfortable assumption: that it was a fixed cost. You paid a license, a…
Hosting Is Not Owning
Last week I deleted the sentence I was proudest of. It said I run hand-built inference engines: serving stacks I wrote myself, running Qwen and Deep…
Harness Engineering
Why production AI is 90% harness and 10% model. And what most pilots miss. Blake Aber · Predicate Ventures · 2026 The gap between an AI demo that la…
Using LLM for Dialogue Management Tasks
Dialogue management is the logic layer that decides what a conversational system should do next. Traditional implementations rely on finite state ma…
Optimizing LLM Model Performance for Real-Time Applications
Real-time applications, from live coding assistants to conversational voice agents, require LLM latency measured in hundreds of milliseconds, not se…
Optimizing LLM Model Performance: Best Practices and Techniques
Production LLM workloads rarely fail because of model intelligence. They fail when latency spikes, context windows overflow, or inference costs scal…
Few-Shot Learning with LLM: A Deep Dive
Few-shot learning with large language models is one of the most practical ways to steer model behavior without updating weights. By embedding task-s…
LLM Trends and Future Outlook
The conversation around large language models has shifted. The frontier is no longer defined solely by parameter counts or training compute, but by…