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Neural networks and deep learning

• image recognition

  Image recognition, in the context of machine vision, is the ability of software to identify objects, places, people, writing and actions in digital images. Continue Reading

• What is generative AI? Everything you need to know

  Generative AI is a type of artificial intelligence technology that can produce various types of content, including text, imagery, audio and synthetic data. Continue Reading

• lemmatization

  Lemmatization is the process of grouping together different inflected forms of the same word. Continue Reading

• Google Bard

  Google Bard is an AI-powered chatbot tool designed by Google to simulate human conversations using natural language processing and machine learning. Continue Reading

• Exploring GPT-3 architecture

  With 175 billion parameters, GPT-3 is one of the largest and most well-known neural networks available for natural language applications. Learn why people are so pumped about it. Continue Reading

• Definitions to Get Started

  • image recognition
  • What is generative AI? Everything you need to know
  • lemmatization
  • Google Bard

  • artificial superintelligence (ASI)
  • generative adversarial network (GAN)
  • automated machine learning (AutoML)
  • What is artificial intelligence (AI)?

  View All Definitions

• artificial superintelligence (ASI)

  Artificial superintelligence (ASI) is a software-based system with intellectual powers beyond those of humans across a comprehensive range of categories and fields of endeavor.Continue Reading

• generative adversarial network (GAN)

  A generative adversarial network (GAN) is a machine learning (ML) model in which two neural networks compete with each other by using deep learning methods to become more accurate in their predictions.Continue Reading

• automated machine learning (AutoML)

  Automated machine learning (AutoML) is the process of applying machine learning (ML) models to real-world problems using automation.Continue Reading

• How AI serves as a cornerstone of Industry 4.0

  For manufacturing environments to be included in Industry 4.0, they must adopt up-to-date technologies to improve operations. AI should be foremost among them.Continue Reading

• What is artificial intelligence (AI)?

  Artificial intelligence is the simulation of human intelligence processes by machines, especially computer systems. Specific applications of AI include expert systems, natural language processing, speech recognition and machine vision.Continue Reading

• reinforcement learning

  Reinforcement learning is a machine learning training method based on rewarding desired behaviors and/or punishing undesired ones.Continue Reading

• GPT-3

  GPT-3, or the third-generation Generative Pre-trained Transformer, is a neural network machine learning model trained using internet data to generate any type of text.Continue Reading

• 4 main types of artificial intelligence: Explained

  AI technology can exceed human performance in many areas, but it is still no match for the human brain. Learn about the four main types of AI.Continue Reading

• How to formulate a winning AI strategy

  Executives are aware of the value artificial intelligence in its many forms can bring to enterprises yet devising a viable AI strategy can be as complex as the technology itself.Continue Reading

• 9 top applications of artificial intelligence in business

  The use of AI in business applications and operations is expanding. Learn about where enterprises are applying AI and the benefits AI applications are driving.Continue Reading

• How do big data and AI work together?

  Enterprises are leaning on big data to train AI algorithms and, in turn, are using AI to understand big data. The results are pushing operations forward.Continue Reading

• self-driving car (autonomous car or driverless car)

  A self-driving car (sometimes called an autonomous car or driverless car) is a vehicle that uses a combination of sensors, cameras, radar and artificial intelligence (AI) to travel between destinations without a human operator.Continue Reading

• narrow AI (weak AI)

  Narrow AI is an application of artificial intelligence technologies to enable a high-functioning system that replicates -- and perhaps surpasses -- human intelligence for a dedicated purpose.Continue Reading

• Turing Test

  A Turing Test is a method of inquiry in artificial intelligence (AI) for determining whether or not a computer is capable of thinking like a human being.Continue Reading

• natural language processing (NLP)

  Natural language processing (NLP) is the ability of a computer program to understand human language as it is spoken and written -- referred to as natural language.Continue Reading

• artificial general intelligence (AGI)

  Artificial general intelligence (AGI) is the representation of generalized human cognitive abilities in software so that, faced with an unfamiliar task, the AI system could find a solution.Continue Reading

• OpenAI

  OpenAI is a nonprofit research company that aims to develop and direct artificial intelligence (AI) in ways that benefit humanity as a whole.Continue Reading

• adversarial machine learning

  Adversarial machine learning is a technique used in machine learning to fool or misguide a model with malicious input.Continue Reading

• generative modeling

  Generative modeling is the use of artificial intelligence (AI), statistics and probability in applications to produce a representation or abstraction of observed phenomena or target variables that can be calculated from observations.Continue Reading

• Recent developments show us the future of chatbots

  Experts in conversational AI are optimistic about what recent advancements in chatbot technology mean for the future. Despite challenges, these advancements can point the way forward.Continue Reading

• How AI can assist industries in environmental protection efforts

  While technology for environmental protection isn't a new concept, AI advancements empower businesses to achieve sustainable operations.Continue Reading

• How significant is AI's role in Industry 4.0?

  Many examples exist to demonstrate the effectiveness of AI in Industry 4.0. It entails the newest revolution in manufacturing, so naturally advanced tech like AI will play a crucial role.Continue Reading

• facial recognition

  Facial recognition is a category of biometric software that maps an individual's facial features mathematically and stores the data as a faceprint.Continue Reading

• neuromorphic computing

  Neuromorphic computing is a method of computer engineering in which elements of a computer are modeled after systems in the human brain and nervous system.Continue Reading

• stemming

  Stemming is the process of reducing a word to its stem that affixes to suffixes and prefixes or to the roots of words known as "lemmas."Continue Reading

• robotic surgery (robot-assisted surgery)

  Robotic surgery is the use of computer technologies working in conjunction with robot systems to perform medical procedures.Continue Reading

• Artificial Intelligence as a Service (AIaaS)

  Artificial Intelligence as a Service (AIaaS) is the third-party offering of artificial intelligence (AI) outsourcing.Continue Reading

• social robot

  A social robot is an artificial intelligence (AI) system that is designed to interact with humans and other robots.Continue Reading

• PyTorch

  PyTorch is an open source machine learning (ML) framework based on the Python programming language and the Torch library.Continue Reading

• algorithmic transparency

  Algorithmic transparency is openness about the purpose, structure and underlying actions of the algorithms used to search for, process and deliver information.Continue Reading

• How AI in weather prediction can aid human intelligence

  AI and machine learning models are becoming more widely used in climate prediction and disaster preparedness to aid experts without replacing them.Continue Reading

• Why and when to consider a feature store in machine learning

  Feature stores exist to make data for training machine learning models reusable. Explore both the benefits and challenges of feature stores that organizations can experience.Continue Reading

• data scientist

  A data scientist is an analytics professional who is responsible for collecting, analyzing and interpreting data to help drive decision-making in an organization.Continue Reading

• convolutional neural network (CNN)

  A convolutional neural network (CNN or convnet) is a subset of machine learning.Continue Reading

• Industries leading the way in conversational AI

  Learn how companies in vertical markets are using conversational AI and even partnering with AI developers for software that's tailored to their unique business needs.Continue Reading

• backpropagation algorithm

  Backpropagation, or backward propagation of errors, is an algorithm that is designed to test for errors working back from output nodes to input nodes.Continue Reading

• The white-box model approach aims for interpretable AI

  The white-box model approach to machine learning makes AI interpretable since algorithms are easy to understand. Ajay Thampi, author of 'Interpretable AI,' explains this approach.Continue Reading

• AI winter

  AI winter is a quiet period for artificial intelligence research and development.Continue Reading

• machine vision

  Machine vision is the ability of a computer to see; it employs one or more video cameras, analog-to-digital conversion (ADC) and digital signal processing (DSP).Continue Reading

• How enterprises can establish an AI-first data strategy

  Enterprises looking to mature in their use of AI must focus on the information they're putting into their models. Their models should create trust in their business.Continue Reading

• expert system

  An expert system is a computer program that uses artificial intelligence (AI) technologies to simulate the judgment and behavior of a human or an organization that has expertise and experience in a particular field.Continue Reading

• How hybrid chatbots improve customer experience

  Hybrid chatbots combine human intelligence with AI used in standard chatbots to improve customer experience. Learn how industries are using them to engage with customers.Continue Reading

• Weighing quantum AI's business potential

  Quantum AI has the potential to revolutionize business computing, but logistic complexities create sizeable obstacles for near-term adoption and success.Continue Reading

• conversational AI

  Conversational AI is a type of artificial intelligence that enables consumers to interact with computer applications the way they would with other humans.Continue Reading

• knowledge engineering

  Knowledge engineering is a field of artificial intelligence (AI) that tries to emulate the judgment and behavior of a human expert in a given field.Continue Reading

• data splitting

  Data splitting is when data is divided into two or more subsets. Typically, with a two-part split, one part is used to evaluate or test the data and the other for training the model.Continue Reading

• Stochastic point processes and their practical value

  Data scientists learn and utilize stochastic point processes for myriad pragmatic uses. Data scientist Vincent Granville explains this in his new book.Continue Reading

• computational linguistics (CL)

  Computational linguistics (CL) is the application of computer science to the analysis and comprehension of written and spoken language.Continue Reading

• How AI ethics is the cornerstone of governance

  The concept of AI ethics ensures that AI systems provide accuracy and reliability. Businesses will benefit from adopting AI ethics strategies of their own.Continue Reading

• cognitive computing

  Cognitive computing is the use of computerized models to simulate the human thought process in complex situations where the answers may be ambiguous and uncertain.Continue Reading

• Learn the benefits of interpretable machine learning

  In this excerpt from 'Interpretable Machine Learning with Python,' read how machine learning models and algorithms add value when they are both interpretable and explainable.Continue Reading

• predictive modeling

  Predictive modeling is a mathematical process used to predict future events or outcomes by analyzing patterns in a given set of input data.Continue Reading

• Tips and tricks for deploying TinyML

  A typical TinyML deployment has many software and hardware requirements, and there are best practices that developers should be aware of to help simplify this complicated process.Continue Reading

• edge AI

  Edge artificial intelligence (edge AI) is a paradigm for crafting AI workflows that span centralized data centers (the cloud) and devices outside the cloud that are closer to humans and physical things (the edge).Continue Reading

• telepresence robot

  A telepresence robot is a remote-controlled, wheeled device that has wireless internet connectivity.Continue Reading

• ambient intelligence (AmI)

  Ambient intelligence (AmI) is the element of a pervasive computing environment that enables it to interact with and respond appropriately to the humans in that environment.Continue Reading

• robot economy

  The robot economy is a scenario in which most of the labor required to sustain human life is automated.Continue Reading

• robo-advisor

  A robo-advisor is an artificial intelligence (AI) driven virtual financial advisor.Continue Reading

• neurosynaptic chip (cognitive chip)

  A neurosynaptic chip, also known as a cognitive chip, is a computer processor that functions more like a biological brain than a typical CPU does.Continue Reading

• Model optimization methods to cut latency, adapt to new data

  This last part of the series on machine learning explains two final model optimization techniques: lightweight model implementation and incremental model learning.Continue Reading

• Why transparency in AI matters for businesses

  To ensure model accuracy, businesses need to understand why their machine learning models make their decisions. Certain tools and techniques can help with that.Continue Reading

• natural language generation (NLG)

  Natural language generation (NLG) is the use of artificial intelligence (AI) programming to produce written or spoken narratives from a data set.Continue Reading

• The benefits of an AI-first strategy

  Enterprises should put AI first in their business strategies by constantly collecting and using new data to power AI models, argues startup investor Ash Fontana.Continue Reading

• 2 supervised learning techniques that aid value predictions

  Learn how two supervised machine learning techniques -- numerical prediction and category prediction -- work to predict values and, thus, can aid model training.Continue Reading

• fuzzy logic

  Fuzzy logic is an approach to computing based on "degrees of truth" rather than the usual "true or false" (1 or 0) Boolean logic on which the modern computer is based.Continue Reading

• 10 AI tech trends data scientists should know

  The rising environmental and monetary costs of deep learning are catching enterprises' attention, as are new AI techniques like graph neural networks and contrastive learning.Continue Reading

• 2 data-wrangling techniques for better machine learning

  Before data can be usefully inputted into algorithms, it must first be prepared. Learn two of the techniques that do the job and make machine learning work.Continue Reading

• 11 data science skills for machine learning and AI

  As companies realize the power of data, they're tasked with finding data science practitioners with AI and ML skill sets to help them use the data to make better business decisions.Continue Reading

• machine learning engineer (ML engineer)

  A machine learning engineer (ML engineer) is a person who focuses on researching, building and designing self-running AI systems that automate predictive models.Continue Reading

• How feature selection, extraction improve ML predictions

  In this discussion of machine learning patterns, learn how feature selection and feature extraction help make data more useful and, thus, improve predictions.Continue Reading

• Associativity, graphical summary computations aid ML insights

  Associativity computation and graphical summary computation allow for more complex insights, and in turn improve predictions. Explore how these ML techniques work in practice.Continue Reading

• machine learning

  Machine learning (ML) is a type of artificial intelligence (AI) that allows software applications to become more accurate at predicting outcomes without being explicitly programmed to do so. Machine learning algorithms use historical data as input ...Continue Reading

• deep learning

  Deep learning is a type of machine learning and artificial intelligence (AI) that imitates the way humans gain certain types of knowledge.Continue Reading

• supervised learning

  Supervised learning is an approach to creating artificial intelligence (AI), where a computer algorithm is trained on input data that has been labeled for a particular output.Continue Reading

• What is a neural network? Explanation and examples

  In information technology, an artificial neural network is a system of hardware and/or software patterned after the operation of neurons in the human brain.Continue Reading

• Common ML patterns: Central tendency and variability

  Four common patterns provide approaches to solving machine-learning problems. Learn how two -- central tendency computation and variability computation -- work.Continue Reading

• The supervised approach to machine learning

  In part 2 of our machine learning tutorial, learn how to use the supervised learning approach to machine learning to produce the best predictions.Continue Reading

• dropout

  Dropout refers to data, or noise, that's intentionally dropped from a neural network to improve processing and time to results.Continue Reading

• AWS SageMaker training, making machine learning accessible

  Making machine learning more accessible and helping developers with AWS SageMaker training is at the core of Julien Simon's book, 'Learn Amazon SageMaker.'Continue Reading

• 5 examples of effective NLP in customer service

  Through use cases such as chatbots, recommendation systems and customer relationship management, NLP and AI are playing an important role in enterprise customer service.Continue Reading

• Introduction to using machine learning

  The first part of our machine learning series, excerpted from training materials for Arcitura's Machine Learning Specialist certification, introduces algorithms, models and model training.Continue Reading

• Training GANs relies on calibrating 2 unstable neural networks

  Understanding the complexities and theory of dueling neural networks can carve out a path to successful GAN training.Continue Reading

• Do you have competitive data science key skills?

  Data scientists should be familiar with a variety of programming languages, machine learning algorithms and databases and must be able to communicate these skills across teams.Continue Reading

• responsible AI

  Responsible AI is a governance framework that documents how a specific organization is addressing the challenges around artificial intelligence (AI) from both an ethical and legal point of view. Resolving ambiguity for where responsibility lies if ...Continue Reading

• A basic design pattern for image recognition

  Learn how a design pattern based on convolutional neural networks can be adapted to create a visual graphics generator model for image recognition.Continue Reading

• General AI vs. narrow AI comes down to adaptability

  AI today has limited and specific applications, but the continual growth of the technology may just lead to the replication of human intelligence through general AI.Continue Reading

• Understanding motion analytics, where it is and where it's going

  Machine learning is helping make motion analysis more usable for the average enterprise, creating new use cases and applications that can drive value.Continue Reading

• GPT-3 AI language model sharpens complex text generation

  GPT-3 is the latest natural language generation model, but its acquisition by Microsoft leaves developers wondering when, and how, they'll be able to use the model.Continue Reading

• Modern AI evolution timeline shows a decade of rapid progress

  AI has become an asset for organizations to better understand their business position, and its capabilities have improved dramatically over the past decade.Continue Reading

• unsupervised learning

  Unsupervised learning refers to the use of artificial intelligence (AI) algorithms to identify patterns in data sets containing data points that are neither classified nor labeled.Continue Reading

• Learn the business value of AI's various techniques

  To drive business value from AI, business managers need to distinguish between the various AI techniques, starting with the many flavors of machine learning.Continue Reading

• Use of AI-assisted surgery remains limited despite its benefits

  While AI adoption to assist with surgeries remains limited, the technology holds great potential to increase quality of care and decrease patient risk.Continue Reading

• Neuro-symbolic AI emerges as powerful new approach

  The unification of two antagonistic approaches in AI is seen as an important milestone in the evolution of AI. Read about the efforts to combine symbolic reasoning and deep learning by the field's leading experts.Continue Reading

• intelligent process automation (IPA)

  Intelligent process automation (IPA) is a combination of technologies used to manage and automate digital processes.Continue Reading

• Science fiction vs. reality: A robotics industry overview

  Robots have made their way into industrial, manufacturing and military settings, but the robots of science fiction remain a long-term goal rather than a reality.Continue Reading