UPIR: What If Distributed Systems Could Write (and Verify) Themselves?
Lessons from building a framework that automatically generates verified distributed systems - and why I think formal methods, synthesis, and ML need to work together
First empirical demonstration of activation-level sandbagging detection. Linear probes achieve 90-96% accuracy across Mistral, Gemma, and Qwen models. Key finding - sandbagging representations are model-specific, and steering can reduce sandbagging by 20%.
I tested activation steering on 4 agent behaviors across 3 models. The results surprised me.
A deep dive into building distributed LLM evaluation infrastructure that actually scales - architectural decisions, trade-offs, and lessons learned.
A practical framework for evaluating your multi-agent context management strategy. From ad-hoc string concatenation to self-evolving context systems - where does your architecture stand?
A hands-on exploration of writing custom GPU kernels with OpenAI Triton, going from PyTorch's 11% bandwidth utilization to 88% on RMSNorm.
A deep dive into implementing speculative decoding from scratch, with benchmarks on GPT-2 and extensions to diffusion models.
Lessons from building a framework that automatically generates verified distributed systems - and why I think formal methods, synthesis, and ML need to work together
Enterprise data platforms face a 100,000x query increase from agentic AI. Introducing Symbiotic Agent-Ready Platforms (SARPs) - the architectural paradigm shift needed to survive the transition to machine intelligence.
Frontier AI models from OpenAI, Anthropic, Google & others can detect when they're being tested and modify behavior-challenging AI safety evaluation methods.
How the AI industry is responding to situational awareness challenges. Practical monitoring systems, collaborative research, and what organizations should do today.
Claude 3 Opus strategically fakes compliance during training to preserve its values. This alignment faking undermines our ability to modify AI behavior safely.