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Abacus.AI
Abacus.AI is an Artificial Intelligence and Machine Learning platform headquartered in the San Francisco Bay Area. Description Initially known as RealityEngines.AI, the company was founded by Bindu Reddy, Arvind Sundararajan, and Siddartha Naidu in 2019. Abacus.AI markets using the terms artificial intelligence and machine learning. The company raised $5.3 million in seed funding round led by Eric Schmidt in 2019. In 2020, it raised $13 million led by Index Ventures (changing its name to Abacus.AI in January), and $22 million led by Coatue. In 2021, it raised $50 million led by Tiger Global Management. Technology Abacus.AI can be used to set up data pipelines, specify custom machine learning specific transformations, train models and deploy and monitor them, and build deep learning systems. In addition to the core platform, Abacus.AI provides use-case specific workflows including personalization, forecasting, and anomaly detection. The company has invented several neural archi ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Index Ventures
Index Ventures is a Europe, European venture capital firm with dual headquarters in San Francisco and London, investing in technology-enabled companies with a focus on e-commerce, fintech, mobility, gaming, infrastructure/AI, and security. Since its founding in 1996, the firm has invested in a number of companies and raised approximately $5.6 billion. Index Venture partners appear frequently on ''Forbes''’ Midas List of the top tech investors in Europe and Israel. History Index Ventures has its origins in a Switzerland, Swiss bond (finance), bond-trading firm called Index Securities, founded by Gerald Rimer in 1976. In 1992, Rimer recruited his son, Neil, to join the firm, and together they launched its technology investment arm, which would evolve into an independent entity, Index Ventures. Index Ventures was officially founded in 1996 by Neil Rimer, David Rimer and Giuseppe Zocco, when they raised a pilot fund of $17 million, followed by a $180 million fund ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Coatue Management
Coatue is an American technology-focused investment manager led by founder and portfolio manager Philippe Laffont. Coatue invests in public and private markets with a focus on technology, media, telecommunications. the consumer and healthcare sectors. Coatue has offices in New York City, Menlo Park, California, London, Shanghai and Hong Kong. History Philippe Laffont graduated from MIT in 1991 in computer science. He worked as an analyst for McKinsey & Company from 1992 to 1994 in Madrid, Spain. After working as an independent consultant, he joined Tiger Management LLC as a research analyst in 1996, focusing on telecommunications stocks. In 1999, Laffont founded Coatue making him a member of the Tiger Cubs employees who founded their own hedge funds. Coatue launched its first hedge fund in 1999 with $45 million in capital. Coatue manages this fund in addition to others. Thomas Laffont is the firm’s co-founder and leads Coatue’s private equity investing. Coatue's annual "Ea ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Artificial Intelligence
Artificial intelligence (AI) is intelligence—perceiving, synthesizing, and inferring information—demonstrated by machines, as opposed to intelligence displayed by animals and humans. Example tasks in which this is done include speech recognition, computer vision, translation between (natural) languages, as well as other mappings of inputs. The ''Oxford English Dictionary'' of Oxford University Press defines artificial intelligence as: the theory and development of computer systems able to perform tasks that normally require human intelligence, such as visual perception, speech recognition, decision-making, and translation between languages. AI applications include advanced web search engines (e.g., Google), recommendation systems (used by YouTube, Amazon and Netflix), understanding human speech (such as Siri and Alexa), self-driving cars (e.g., Tesla), automated decision-making and competing at the highest level in strategic game systems (such as chess and Go). ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Neural Network
A neural network is a network or neural circuit, circuit of biological neurons, or, in a modern sense, an artificial neural network, composed of artificial neurons or nodes. Thus, a neural network is either a biological neural network, made up of biological neurons, or an artificial neural network, used for solving artificial intelligence (AI) problems. The connections of the biological neuron are modeled in artificial neural networks as weights between nodes. A positive weight reflects an excitatory connection, while negative values mean inhibitory connections. All inputs are modified by a weight and summed. This activity is referred to as a linear combination. Finally, an activation function controls the amplitude of the output. For example, an acceptable range of output is usually between 0 and 1, or it could be −1 and 1. These artificial networks may be used for predictive modeling, adaptive control and applications where they can be trained via a dataset. Self-learning re ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Conference On Computer Vision And Pattern Recognition
The Conference on Computer Vision and Pattern Recognition (CVPR) is an annual conference on computer vision and pattern recognition, which is regarded as one of the most important conferences in its field. According to Google Scholar Metrics (2022), it is the highest impact computing venue. Affiliations CVPR was first held in Washington DC in 1983 by Takeo Kanade and Dana Ballard (previously the conference was named Pattern Recognition and Image Processing). From 1985 to 2010 it was sponsored by the IEEE Computer Society. In 2011 it was also co-sponsored by University of Colorado Colorado Springs. Since 2012 it has been co-sponsored by the IEEE Computer Society and the Computer Vision Foundation, which provides open access to the conference papers. Scope CVPR considers a wide range of topics related to computer vision and pattern recognition—basically any topic that is extracting structures or answers from images or video or applying mathematical methods to data to extract or ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
International Conference On Machine Learning
The International Conference on Machine Learning (ICML) is the leading international academic conference in machine learning. Along with NeurIPS and ICLR, it is one of the three primary conferences of high impact in machine learning and artificial intelligence research. It is supported by the ( IMLS). Precise dates vary year to year, but paper submissions are generally due at the end of January, and the conference is generally held the following July. The first ICML was held 1980 in Pittsburgh. Locations * ICML 2026 Seoul, South Korea * ICML 2025 Vancouver, Canada * ICML 2024 Vienna, Austria * ICML 2023 Honolulu, Hawaii, United States * ICML 2022 Baltimore, Maryland, United States * ICML 2021 Vienna, Austria (virtual conference) * ICML 2020 Vienna, Austria (virtual conference) * ICML 2019 Los Angeles, United States * ICML 2018 Stockholm, Sweden * ICML 2017 Sydney, Australia * ICML 2016 New York City, United States * ICML 2015 Lille, France * ICML 2014 Beijing, Ch ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Conference On Neural Information Processing Systems
The Conference and Workshop on Neural Information Processing Systems (abbreviated as NeurIPS and formerly NIPS) is a machine learning and computational neuroscience conference held every December. The conference is currently a double-track meeting (single-track until 2015) that includes invited talks as well as oral and poster presentations of refereed papers, followed by parallel-track workshops that up to 2013 were held at ski resorts. History The NeurIPS meeting was first proposed in 1986 at the annual invitation-only Snowbird Meeting on Neural Networks for Computing organized by The California Institute of Technology and Bell Laboratories. NeurIPS was designed as a complementary open interdisciplinary meeting for researchers exploring biological and artificial Neural Networks. Reflecting this multidisciplinary approach, NeurIPS began in 1987 with information theorist Ed Posner as the conference president and learning theorist Yaser Abu-Mostafa as program chairman. Rese ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Internet Of Things
The Internet of things (IoT) describes physical objects (or groups of such objects) with sensors, processing ability, software and other technologies that connect and exchange data with other devices and systems over the Internet or other communications networks. Internet of things has been considered a misnomer because devices do not need to be connected to the public internet, they only need to be connected to a network and be individually addressable. The field has evolved due to the convergence of multiple technologies, including ubiquitous computing, commodity sensors, increasingly powerful embedded systems, as well as machine learning.Hu, J.; Niu, H.; Carrasco, J.; Lennox, B.; Arvin, F.,Fault-tolerant cooperative navigation of networked UAV swarms for forest fire monitoring Aerospace Science and Technology, 2022. Traditional fields of embedded systems, wireless sensor networks, control systems, automation (including home and building automation), independently ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
PyTorch
PyTorch is a machine learning framework based on the Torch library, used for applications such as computer vision and natural language processing, originally developed by Meta AI and now part of the Linux Foundation umbrella. It is free and open-source software released under the modified BSD license. Although the Python interface is more polished and the primary focus of development, PyTorch also has a C++ interface. A number of pieces of deep learning software are built on top of PyTorch, including Tesla Autopilot, Uber's Pyro, Hugging Face's Transformers, PyTorch Lightning, and Catalyst. PyTorch provides two high-level features: * Tensor computing (like NumPy) with strong acceleration via graphics processing units (GPU) * Deep neural networks built on a tape-based automatic differentiation system History Meta (formerly known as Facebook) operates both ''PyTorch'' and ''Convolutional Architecture for Fast Feature Embedding'' ( Caffe2), but models defined by the two f ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
TensorFlow
TensorFlow is a free and open-source software library for machine learning and artificial intelligence. It can be used across a range of tasks but has a particular focus on training and inference of deep neural networks. "It is machine learning software being used for various kinds of perceptual and language understanding tasks" – Jeffrey Dean, minute 0:47 / 2:17 from YouTube clip TensorFlow was developed by the Google Brain team for internal Google use in research and production. The initial version was released under the Apache License 2.0 in 2015. Google released the updated version of TensorFlow, named TensorFlow 2.0, in September 2019. TensorFlow can be used in a wide variety of programming languages, including Python, JavaScript, C++, and Java. This flexibility lends itself to a range of applications in many different sectors. History DistBelief Starting in 2011, Google Brain built DistBelief as a proprietary machine learning system based on deep learning neur ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Generative Adversarial Network
A generative adversarial network (GAN) is a class of machine learning frameworks designed by Ian Goodfellow and his colleagues in June 2014. Two neural networks contest with each other in the form of a zero-sum game, where one agent's gain is another agent's loss. Given a training set, this technique learns to generate new data with the same statistics as the training set. For example, a GAN trained on photographs can generate new photographs that look at least superficially authentic to human observers, having many realistic characteristics. Though originally proposed as a form of generative model for unsupervised learning, GANs have also proved useful for semi-supervised learning, fully supervised learning, and reinforcement learning. The core idea of a GAN is based on the "indirect" training through the discriminator, another neural network that can tell how "realistic" the input seems, which itself is also being updated dynamically. This means that the generator is not tr ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Synthetic Data
Synthetic data is information that's artificially generated rather than produced by real-world events. Typically created using algorithms, synthetic data can be deployed to validate mathematical models and to train machine learning models. Data generated by a computer simulation can be seen as synthetic data. This encompasses most applications of physical modeling, such as music synthesizers or flight simulators. The output of such systems approximates the real thing, but is fully algorithmically generated. Synthetic data is used in a variety of fields as a filter for information that would otherwise compromise the confidentiality of particular aspects of the data. In many sensitive applications, datasets theoretically exist but cannot be released to the general public; synthetic data sidesteps the privacy issues that arise from using real consumer information without permission or compensation. Usefulness Synthetic data is generated to meet specific needs or certain conditions ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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