This valuable study describes a simple and robust approach for estimating information-limiting noise by splitting neural populations and comparing estimator values. The authors report more accurate ...

Open-source tools have made MMM more accessible, but reliable results still depend on clean data, thoughtful modeling, and ...

CIOs will need to stay focused on value and strike a balance between investing in low-hanging fruit and cutting edge capabilities, even as inference gets cheaper for LLM providers. “You have falling ...

Bayesian structural time series for causal inference in Python. A faithful port of Google's CausalImpact R package. No TensorFlow required. The Gibbs sampler is implemented in Rust (via PyO3), ...

Stanford adjunct professor and successfully exited founder Zain Asgar just raised an $80 million Series A for a startup that solve the AI inference bottleneck problem in an astute way. The round was ...

Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with content, and download exclusive resources. Holly Cummins discusses why "nothing is new ...

The creators of the open source project vLLM have announced that they transitioned the popular tool into a VC-backed startup, Inferact, raising $150 million in seed funding at an $800 million ...

Lotteries are hard to win. The odds of hitting the Powerball jackpot are so tiny that, as a CNN commenter once put it, you have a better chance of becoming an astronaut, dating a supermodel, and ...

In this work, we develop a new framework for designing experiments that are robust to model misspecification through generalised Bayesian inference. This repository contains the files needed to ...

Forbes contributors publish independent expert analyses and insights. I write about the economics of AI. When OpenAI’s ChatGPT first exploded onto the scene in late 2022, it sparked a global obsession ...

As frontier models move into production, they're running up against major barriers like power caps, inference latency, and rising token-level costs, exposing the limits of traditional scale-first ...