I’m a traditional software engineer. Join me for the first in a series of articles chronicling my hands-on journey into AI ...

Use the vitals package with ellmer to evaluate and compare the accuracy of LLMs, including writing evals to test local models.

Understand how this artificial intelligence is revolutionizing the concept of what an autonomous agent can do (and what risks ...

If you have your eye on a career in the robotics industry, consider upping your skills via a convenient online or in-person learning platform.

These tools are all things I find useful while doing any kind of Automatic Speech Recognition (ASR) research. These are things I wish had existed when I was first learning about ASR and so I thought I ...

Abstract: Bayesian inference provides a methodology for parameter estimation and uncertainty quantification in machine learning and deep learning methods. Variational inference and Markov Chain ...

Supervised learning algorithms like Random Forests, XGBoost, and LSTMs dominate crypto trading by predicting price directions or values from labeled historical data, enabling precise signals such as ...

See https://github.com/sicpa-dlab/didcomm-demo. Verification materials are expected in JWK, Base58 and Multibase (internally Base58 only) formats. In Base58 and ...

Abstract: Simulation is an excellent tool to study real-life systems with uncertainty. Discrete-event simulation (DES) is a common simulation approach to model time-dependent and complex systems.