Open source artificial intelligence
Artificial intelligence is one of the hottest research areas. Large companies such as IBM, Google, Microsoft, Facebook, and Amazon not only increased their capital investment in its development research department, but also started to acquire some small acquisitions in machine learning, neural networks, natural language and image processing. Start-up company. Given the current explosion in the field of artificial intelligence research, Stanford University professors recently made such a report: "The role of artificial intelligence software is getting stronger, and artificial intelligence software that has a strong influence on human society and economy will In the past 2030."
The foreign website Datamation has collated the currently popular 15 open source artificial intelligence softwares. Lei Fengnet (searching for "Lei Feng Net" public number attention) compiled the full text and introduced it as follows:
1.Caffe
Developed by a PhD student at the University of California, Berkeley, Caffe Software is a deep learning framework based on expression architecture and scalable coding. Because of its outstanding processing speed, it is widely loved by researchers and companies. According to its home page, only one NVIDIA K40 GPU is used, and the software can handle over 60 million images a day. The Caffe software project is run by BVLC and is funded by NVIDIA and Amazon and other companies for its development research.
2.CNTK
CNTK is the abbreviation of Computational Network Toolkit (Computing Network Toolkit) and is one of Microsoft's open source artificial intelligence software. Its outstanding feature is that whether it is only CPU work, single GPU, or multiple GPUs, or multiple machines with multiple GPUs, its performance is very good. Although Microsoft primarily uses it for speech recognition research, it can also perform machine translation, image recognition, image capture, text processing, language recognition, and language modeling.
3. Deeplearning4j
Deeplearning4j is a JVM open source deep learning library software. It can run in a distributed environment and integrate Hadoop with Apache Spark. This makes it possible to configure deep neural networks and run other JVM languages ​​such as Java, Scala and others.
Deeplearning4j software project is operated by Skymind commercial company, Skymind is responsible for the project's financial support, personnel training and product promotion.
4.DMTK
Like CNTK, DMTK is the abbreviation of Distributed Machine Learning Toolkit (distributed machine learning tool) and is another Microsoft open source artificial intelligence software. Designed for big data research, it aims to shorten the training time of artificial intelligence systems. DMTK includes three main parts: DMTK framework, LightLDA model algorithm and distributed (multi-sensor) word embedding algorithm. In order to illustrate the processing speed of DMTK, Microsoft claims that it can process one million topics and 10 million words (10 trillion parameters in total) through an 8-node cluster of computers in a collection of over 100 billion marked documents. Thematic model, which is unmatched by similar software.
5.H2O
H2O, which focuses more on corporate experience than scientific research, has received orders from large companies such as Capital One, Cisco, Nielsen Catalina, PayPal, and Transamerica. Oxdata said that anyone can use H2O machine learning and predictive analytics capabilities to solve business problems. H2O can also be used in predictive modeling, fraud and risk analysis, insurance analytics, advertising technology, healthcare, and customer intelligence.
H2O has two open source versions: Standard Edition H2O and Sparkling Water Edition H2O. Both versions are integrated in Apache Spark. Oxdata will provide technical support for paying companies.
6.Mahout
Mahout is an open source project under the ASF (Apache Software Foundation) that provides an open source machine learning framework. According to its official home page description, Mahout has three main features: an extensible algorithmic programming environment, algorithms written in advance with tools such as Spark and H2O, and a built-in vector computing environment called "Samsara." Mahout users include Adobe, Accenture, Foursquare, Intel, LinkedIn, Twitter and Yahoo.
7. MLlib
Apache Spark, known for its processing speed, has become one of the most commonly used software for big data processing. The MLlib algorithm is a Spark extensible machine learning library. It is integrated with Hadoop and can be operated with NumPy and NumPy.R across platforms. It includes a large number of types of machine learning algorithms, including: classification, regression, decision trees, recommendations, aggregation, topic modeling, feature conversion, model evaluation, ML pipeline construction, ML persistence, survival analysis, frequent sets, sequential pattern mining, Discrete linear algebra and statistical analysis of data.
8.NuPIC
NuPIC is operated by Numenta and is an open source artificial intelligence project based on HTM (Layered Time Memory) theory. In fact, the HTM theory is to design a computer system based on the neocortex structure of the human brain, aiming to create a "computer that approaches or exceeds the human ability to handle cognitive tasks."
Numenta not only owns NuPic's open source license, but also its commercial license and patent certificate.
9.OpenNN
OpenNN is an advanced artificial intelligence software for researchers and developers that provides C++ programming libraries that can run neural networks. Its main features are depth framework and efficient performance. The OpenNN website has a detailed introduction to the operation of neural networks. Providing technical support for OpenNN customers is from Artelnics of Spain (main forecast analysis research).
10.OpenCyc
The OpenCyc software developed by Cycorp Inc. has a built-in Cyc knowledge base and common sense reasoning engine. It contains 239,000 terms, about 2.093 million triplets, and about 69,000 online ontology languages. It is like an external semantic database. It is very effective in areas such as rich domain modeling, semantic data fusion, text understanding, domain-specific expert systems and game artificial intelligence. There are two versions of OpenCyc: one is a free, open source version for researchers and the other is a paid version for businesses.
11.Oryx 2
Built on Apache Spark and Kafka, Oryx 2 is a development framework that specializes in large machine learning. It uses a unique three-tier λ architecture. Developers can use Oryx 2 to develop new software that has built-in programs for common large-scale data tasks, such as collaborative filtering, classification, naturalization, and clustering. The big data tool provider Cloudera developed the initial Oryx 1 project and is still continuing its research and development.
12.PredictionIO
As early as February of this year, Salesforce bought the PredictionIO software project. The PredictionIO software project provides ASF with new platforms and trademarks as an incubation project. Although Salesforce Corporation develops its own machine learning technology through the PredictionIO software project, it is still open source. It can use machine learning to deploy related network services and help users build a predictive engine by responding to page dynamic requests in real time.
13.SystemML
SystemML was originally developed by IBM and later acquired by ASF as its big data project. SystemML is a highly scalable platform for advanced mathematical operations, executing R or Python-like statements. SystemML is based on Spark or Hadoop operation and can be used for customer visits to 4S shop vehicle maintenance, airport airspace control, and collection of bank customer social media data.
14.TensorFlow
TensorFlow, one of Google's open source artificial intelligence software, provides a numerical computing library that uses data flow graphs to run on single- or multi-CPU or GPU systems or even mobile devices. Google said that TensorFlow is very flexible, truly portable, has automatic authentication capabilities and supports Python and C++ platforms.
15.Torch
Torch describes himself: "Having a scientific computing framework that supports machine learning algorithms that can prioritize the use of GPUs." Torch is characterized by its outstanding flexibility and outstanding processing speed. It is very handy in dealing with machine learning, computer vision, signal processing, parallel processing, graphics, video, audio and computer networks. It is written in LuaJIT language, a script language based on Lua language.
Datamation
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