Artificial intelligence, AI is one of the most popular directions in scientific research. Companies like IBM, Google, Microsoft, Facebook, and Amazon are investing heavily in research and development, or acquiring startups that have made progress in machine learning, neural networking, natural language, and image processing. Given the level of interest in this, we will not be surprised by the conclusions of Stanford's experts in the artificial intelligence report: "The increasingly powerful artificial intelligence application may have far-reaching implications for our society and economy. Positive impact, this will appear in the time period from now to 2030."
In a recent article, we outlined 45 very interesting or promising artificial intelligence projects. In this article, we will focus on open source artificial intelligence tools to learn more about the 15 most famous open source artificial intelligence projects.
The following open source artificial intelligence applications are at the forefront of artificial intelligence research.
Caffe
It was created by Jayan Yang at the University of California at Berkeley, and Caffe is a deep learning framework based on expression architecture and extensible code. What makes it famous is its speed, which makes it popular with researchers and business users. According to its website, it can process more than 60 million images with just one NVIDIA 40 40 GPU in one day. It is managed by the Berkeley Vision and Learning Center (BVLC) and is funded by companies such as NVIDIA and Amazon to support its growth.
2.CNTK
It is the abbreviation of Computational Network Tool kit, a computing network toolkit. CNTK is a Microsoft open source artificial intelligence tool. It performs well on a single CPU, a single GPU, multiple GPUs, or multiple machines with multiple GPUs. Microsoft mainly uses it for speech recognition research, but it has a good application in machine translation, image recognition, image subtitles, text processing, language understanding and language modeling.
3.Deep learning 4j
Deep learning 4j is an open source deep learning library for the Java Virtual Machine (JVM). It runs in a distributed environment and is integrated into Hadoop and Apache Spark. This allows it to configure deep neural networks and is compatible with Java, Scala and other JVM languages.
The project was managed by a commercial company called Skymind, which provides support, training and a corporate distribution for the project.
4.DMTK
DMTK is the abbreviation of Distributed Machine Learning Toolkit, which is a distributed machine learning tool. Like CNTK, it is Microsoft's open source artificial intelligence tool. As an application designed for big data, its goal is to train artificial intelligence systems faster. It consists of three main components: the DMTK framework, the Light LDA topic model algorithm, and the distributed (poly) word embedding algorithm. To prove its speed, Microsoft claims that on an eight-cluster machine, it can "train a topic model with a vocabulary of 1 million topics and 10 million words (a total of 10 trillion parameters), collecting 1000 in one document. Billions of symbols,". This achievement is unmatched by other tools.
5.H20
Compared to research, H2O pays more attention to serving AI to corporate users. Therefore, H2O has a large number of corporate customers, such as First Capital Financial, Cisco, Nielsen Catalina, Pay Pal and Pan American. It claims that anyone can harness the power of machine learning and predictive analytics to solve business problems. It can be used for predictive modeling, risk analysis and fraud, insurance analysis, advertising technology, health care, and customer intelligence.
It comes in two open source versions: the standard version of H2O and the Sparking Water version, which is integrated into Apache Spark. There are also paid enterprise user support.
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