The honest story behind my first top-tier AI conference paper — from failed experiments and endless revisions to the moment everything… Continue reading on Towards AI »
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Part 2 of a practical series — The model learns the schema. The checker owns the physics. Those are different jobs. In Part I, I covered the three main architectural approaches for physics-informed AI systems: physics-penalized fine-tuning, retrieval-augmented physics (RAP), and hybrid latent spaces with differentiable physics heads. I also flagged that each approach sits at a different point on the implementation difficulty curve. Part II delivers the most practical end of that curve: supervised LoRA fine-tuning for structured output, […]
Three ways to design a long-term talent pipeline.
HP has scaled its OpenAI Frontier integration across global operations to optimise enterprise workflows and accelerate output. The hardware manufacturer initiated testing of the platform in February 2026. Early pilot programs yielded verified operational gains in software engineering and cybersecurity remediation. Expanding these initial trials into an enterprise-wide operating model requires connecting access protocols, contextual data, and evaluation metrics. Frontier supplies this connective tissue. Engineering capacity and deployment metrics Implementation metrics indicate high usage among technical staff. One […]
Leaders need to align design, decision rights, and governance with each go-to-market model to unlock growth.
The calculator utility bc has a minimal math library. For example, there’s no tangent function because you’re expected take the ratio of sine and cosine. (The Gnu version of bc does have a function for tangent, but the POSIX version does not.) And yet bc includes support for Bessel functions J(x). The bc function j takes two arguments. Is the first argument n or x? Grok said the function arguments are j(n,x). I thought I should run man […]
Focus on making product benefits easier to compare, verify, and connect to customer problems.
MCP provides a standard way for AI applications and external systems to communicate.
I’m pretty annoyed. We’re a small AI startup building a real-time coding agent. Our p95 latency requirements are tight (and self imposed, but thats the product). We need sustained high-throughput inference with ~1-2k tokens/second. Been on the Cerebras waitlist for months trying to get API access. We’re not doing training so don’t need a warehouse of H100s. We need fast, high-throughput ASIC inference for a specific production workload. Cerebras’ just went public and they basically have no compute […]