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

Data Normalization vs. Standardization is one of the most foundational yet often misunderstood topics in machine learning and data preprocessing. If you''ve ever built a predictive model, worked on a ...

A marriage of formal methods and LLMs seeks to harness the strengths of both.

AI is moving from “interesting tool” to “invisible teammate.” It is now time to focus on more advanced skills that let you design, supervise and multiply that teammate’s impact, especially in ...

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 ...

Threat actors are exploiting misconfigured web applications used for security training and internal penetration testing, such as DVWA, OWASP Juice Shop, Hackazon, and bWAPP, to gain access to cloud ...

A new study from researchers at Stanford University and Nvidia proposes a way for AI models to keep learning after deployment — without increasing inference costs. For enterprise agents that have to ...

In the UK, there was a case where TGN1412, an immunotherapy under development, triggered a cytokine storm within hours of administration to humans, leading to multiple organ failure. Another example, ...

In some ways, Java was the key language for machine learning and AI before Python stole its crown. Important pieces of the data science ecosystem, like Apache Spark, started out in the Java universe.

ABSTRACT: The accurate prediction of backbreak, a crucial parameter in mining operations, has a significant influence on safety and operational efficiency. The occurrence of this phenomenon is ...

WASHINGTON — Immigration and Customs Enforcement has placed new recruits into its training program before they have completed the agency’s vetting process, an unusual sequence of events as it rushes ...