There are three critical areas where companies most often go wrong: data preparation and training, choosing tools and specialists and timing and planning.

Speechify's Voice AI Research Lab Launches SIMBA 3.0 Voice Model to Power Next Generation of Voice AI SIMBA 3.0 represents a major step forward in production voice AI. It is built voice-first for ...

The drive towards newer Java versions and updated enterprise specifications isn’t just about keeping up with the latest tech; ...

AI safety tests found to rely on 'obvious' trigger words; with easy rephrasing, models labeled 'reasonably safe' suddenly fail, with attacks succeeding up to 98% of the time. New corporate research ...

Data Normalization vs. Standardization is one of the most foundational yet often misunderstood topics in machine learning and ...