Search results
Results from the WOW.Com Content Network
Hugging Face, Inc. is an American company that develops computation tools for building applications using machine learning. It is known for its transformers library built for natural language processing applications.
Margaret Mitchell is a computer scientist who works on algorithmic bias and fairness in machine learning.She is most well known for her work on automatically removing undesired biases concerning demographic groups from machine learning models, [2] as well as more transparent reporting of their intended use.
Each speaker recognition system has two phases: enrollment and verification. During enrollment, the speaker's voice is recorded and typically a number of features are extracted to form a voice print, template, or model. In the verification phase, a speech sample or "utterance" is compared against a previously created voice print.
This page was last edited on 6 December 2024, at 04:30 (UTC).; Text is available under the Creative Commons Attribution-ShareAlike 4.0 License; additional terms may apply.
BigScience Large Open-science Open-access Multilingual Language Model (BLOOM) [1] [2] is a 176-billion-parameter transformer-based autoregressive large language model (LLM). The model, as well as the code base and the data used to train it, are distributed under free licences. [3]
Watsonx.ai is a platform that allows AI developers to leverage a wide range of LLMs under IBM's own Granite series and others such as Facebook's LLaMA-2, free and open-source model Mistral and many others present in Hugging Face community for a diverse set of AI development tasks.
Discover the best free online games at AOL.com - Play board, card, casino, puzzle and many more online games while chatting with others in real-time.
During the 2010s, various companies were offering voice recognition systems to the general public in the form of personal digital assistants. [2] One example is the Google Voice service, which allows users to pose questions via a DVI package installed on either a personal computer , tablet , or mobile phone .