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Bring yourself up to speed with our introductory content.
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Bring yourself up to speed with our introductory content.
How to source AI infrastructure components
Rent, buy or repurpose AI infrastructure? The right choice depends on an organization's planned AI projects, budget, data privacy needs and technical personnel resources. Continue Reading
neurosynaptic chip
A neurosynaptic chip, also known as a cognitive chip, is a computer processor that is designed to function more like a biological brain than a typical central processing unit (CPU). Continue Reading
retrieval-augmented generation
Retrieval-augmented generation (RAG) is an AI framework that retrieves data from external sources. Continue Reading
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IBM Watson supercomputer
Watson was a supercomputer designed and developed by IBM. This advanced computer combined artificial intelligence (AI), automation and sophisticated analytics capabilities to deliver optimal performance as a 'question answering' machine. Continue Reading
language modeling
Language modeling, or LM, is the use of various statistical and probabilistic techniques to determine the probability of a given sequence of words occurring in a sentence. Language models analyze bodies of text data to provide a basis for their word... Continue Reading
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Definitions to Get Started
- What is Bayes' theorem? How is it used in machine learning?
- What is reinforcement learning?
- gradient descent
- large language model operations (LLMOps)
- automated machine learning (AutoML)
- self-driving car (autonomous car or driverless car)
- What is artificial intelligence (AI)? Everything you need to know
- What is Google Gemini (formerly Bard)
Amazon Bedrock (AWS Bedrock)
Amazon Bedrock -- also known as AWS Bedrock -- is a machine learning platform used to build generative artificial intelligence (AI) applications on the Amazon Web Services cloud computing platform.Continue Reading
AI prompt
An artificial intelligence (AI) prompt is a mode of interaction between a human and a large language model that lets the model generate the intended output.Continue Reading
Why and how to use Google Colab
Whether you're looking to gain experience or you're already an expert data scientist, Google Colab can help boost ML and AI initiatives. Follow this tutorial to learn the basics.Continue Reading
image-to-image translation
Image-to-image translation is a generative artificial intelligence (AI) technique that translates a source image into a target image while preserving certain visual properties of the original image.Continue Reading
10 prompt engineering tips and best practices
Asking the right questions is key to using generative AI effectively. Learn 10 tips for writing clear, useful prompts, including mistakes to avoid and advice for image generation.Continue Reading
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AI prompt engineer
An AI prompt engineer is an expert in creating text-based prompts or cues that can be interpreted and understood by large language models and generative AI tools.Continue Reading
LangChain
LangChain is an open source framework that lets software developers working with artificial intelligence (AI) and its machine learning subset combine large language models with other external components to develop LLM-powered applications.Continue Reading
Lessons on integrating generative AI into the enterprise
At Generative AI World 2023, various industries convened to explore existing and potential generative AI use cases. Review insights from one company's implementation experience.Continue Reading
anomaly detection
Anomaly detection is the process of identifying data points, entities or events that fall outside the normal range.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 and digital signal processing.Continue Reading
What is regression in machine learning?
Regression in machine learning helps organizations forecast and make better decisions by revealing the relationships between variables. Learn how it's applied across industries.Continue Reading
Build a natural language processing chatbot from scratch
In this excerpt from the book 'Natural Language Processing in Action,' you'll walk through the steps of creating a simple chatbot to understand how to start building NLP pipelines.Continue Reading
Q&A: How to start learning natural language processing
In this Q&A, 'Natural Language Processing in Action' co-author Hobson Lane discusses how to start learning NLP, including benefits and challenges of building your own pipelines.Continue Reading
decision tree in machine learning
A decision tree is a flow chart created by a computer algorithm to make decisions or numeric predictions based on information in a digital data set.Continue Reading
Prompt engineering vs. fine-tuning: What's the difference?
Prompt engineering and fine-tuning are both practices used to optimize AI output. But the two use different techniques and have distinct roles in model training.Continue Reading
neural network
A neural network is a machine learning (ML) model designed to mimic the function and structure of the human brain.Continue Reading
Why and how to develop a set of responsible AI principles
Enterprise AI use raises a range of pressing ethical issues. Learn why responsible AI principles matter and explore best practices for enterprises developing an AI framework.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
Compare machine learning vs. software engineering
Although machine learning has a lot in common with traditional programming, the two disciplines have several key differences, author and computer scientist Chip Huyen explains.Continue Reading
clustering in machine learning
Clustering is a data science technique in machine learning that groups similar rows in a data set.Continue Reading
The history of artificial intelligence: Complete AI timeline
From the Turing test's introduction to ChatGPT's celebrated launch, AI's historical milestones have forever altered the lifestyles of consumers and operations of businesses.Continue Reading
linear regression
Linear regression identifies the relationship between the mean value of one variable and the corresponding values of one or more other variables.Continue Reading
natural language understanding (NLU)
Natural language understanding (NLU) is a branch of artificial intelligence (AI) that uses computer software to understand input in the form of sentences using text or speech.Continue Reading
CNN vs. RNN: How are they different?
Convolutional and recurrent neural networks have distinct but complementary capabilities and use cases. Compare each model architecture's strengths and weaknesses in this primer.Continue Reading
4 main types of artificial intelligence: Explained
How close are we to creating an artificial superintelligence that surpasses the human mind? Though we aren't close, the pace is quickening as we develop more advanced types of AI.Continue Reading
machine translation
Machine translation technology enables the conversion of text or speech from one language to another using computer algorithms.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
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
Artificial Intelligence as a Service (AIaaS)
Artificial Intelligence as a Service (AIaaS) is the third-party offering of artificial intelligence (AI) outsourcing.Continue Reading
How data quality shapes machine learning and AI outcomes
Data quality directly influences the success of machine learning models and AI initiatives. But a comprehensive approach requires considering real-world outcomes and data privacy.Continue Reading
cognitive computing
Cognitive computing is the use of computerized models to simulate the human thought process in complex situations where the answers might be ambiguous and uncertain.Continue Reading
Fréchet inception distance (FID)
Fréchet inception distance (FID) is a metric for quantifying the realism and diversity of images generated by generative adversarial networks (GANs).Continue Reading
machine teaching
Machine teaching is the practice of infusing context -- and often business consequences -- into the selection of training data used in machine learning (ML) so that the most relevant outputs are produced by the ML algorithms.Continue Reading
15 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
variational autoencoder (VAE)
A variational autoencoder (VAE) is a generative AI algorithm that uses deep learning to generate new content, detect anomalies and remove noise.Continue Reading
The role of AI parameters in the enterprise
What is the correlation between the number of parameters and an AI model's performance? It's not as straightforward as the parameter-rich generative AI apps would have us believe.Continue Reading
responsible AI
Responsible AI is an approach to developing and deploying artificial intelligence (AI) from both an ethical and legal point of view.Continue Reading
machine learning bias (AI bias)
Machine learning bias, also sometimes called algorithm bias or AI bias, is a phenomenon that occurs when an algorithm produces results that are systemically prejudiced due to erroneous assumptions in the machine learning process.Continue Reading
unsupervised learning
Unsupervised learning is a type of machine learning (ML) technique that uses artificial intelligence (AI) algorithms to identify patterns in data sets that are neither classified nor labeled.Continue Reading
singularity
In technology, the singularity describes a hypothetical future where technology growth is out of control and irreversible.Continue Reading
What is trustworthy AI and why is it important?
What are the tenets of trustworthy AI and how do the funders and developers of AI ensure they're upheld?Continue Reading
multimodal AI
Multimodal AI is artificial intelligence that combines multiple types, or modes, of data to create more accurate determinations, draw insightful conclusions or make more precise predictions about real-world problems.Continue Reading
Q-learning
Q-learning is a machine learning approach that enables a model to iteratively learn and improve over time by taking the correct action.Continue Reading
Use cases show the combined potential of AI and blockchain
AI and blockchain are both hot topics in IT, yet used for different purposes. However, enterprises across various sectors can now combine both technologies to their advantage.Continue Reading
automated reasoning
Automated reasoning is the area of computer science concerned with applying reasoning in the form of logic to computing systems.Continue Reading
AI art (artificial intelligence art)
AI art (artificial intelligence art) is any form of digital art created or enhanced with AI tools.Continue Reading
cognitive search
Cognitive search represents a new generation of enterprise search that uses artificial intelligence (AI) technologies to improve users' search queries and extract relevant information from multiple diverse data sets.Continue Reading
History of generative AI innovations spans 9 decades
ChatGPT's debut has prompted widespread publicity and controversy surrounding generative AI, a subset of artificial intelligence that's deep-rooted in historic milestones.Continue Reading
case-based reasoning (CBR)
Case-based reasoning (CBR) is an experience-based approach to solving new problems by adapting previously successful solutions to similar problems.Continue Reading
Types of AI algorithms and how they work
AI algorithms can help businesses gain a competitive advantage. Learn the main types of AI algorithms, how they work and why companies must thoroughly evaluate benefits and risks.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
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
Dall-E
Dall-E is a generative AI technology that enables users to create new images with text to graphics prompts.Continue Reading
face detection
Face detection, also called facial detection, is an artificial intelligence (AI)-based computer technology used to find and identify human faces in digital images and video.Continue Reading
deconvolutional networks (deconvolutional neural networks)
Deconvolutional networks are convolutional neural networks (CNN) that work in a reversed process.Continue Reading
cognitive modeling
Cognitive modeling is an area of computer science that deals with simulating human problem-solving and mental processing in a computerized model.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
transformer model
A transformer model is a neural network architecture that can automatically transform one type of input into another type of output.Continue Reading
CNN vs. GAN: How are they different?
Convolutional neural networks and generative adversarial networks are both deep learning models but differ in how they work and are used. Learn the ins and outs of CNNs and GANs.Continue Reading
intelligent process automation (IPA)
Intelligent process automation (IPA) is a combination of technologies used to manage and automate digital processes.Continue Reading
crypto-agility
Crypto-agility, or cryptographic agility, is a data encryption practice used by organizations to ensure a rapid response to a cryptographic threat.Continue Reading
neural radiance field (NeRF)
Neural radiance fields (NeRF) are a technique that generates 3D representations of an object or scene from 2D images by using advanced machine learning.Continue Reading
What do large language models do in AI?
To capitalize on generative AI, business IT leaders must understand the features of large language models.Continue Reading
sustainable AI
Sustainable AI is the use of artificial intelligence systems that operate in ways contingent with sustainable business practices.Continue Reading
assistive technology (adaptive technology)
Assistive technology is a set of devices intended to help people who have disabilities.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
How AI has cemented its role in telemedicine
Many healthcare clinicians rely on AI when performing daily tasks and see benefits that outweigh the drawbacks.Continue Reading
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
lemmatization
Lemmatization is the process of grouping together different inflected forms of the same word.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
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
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
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
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
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
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
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
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
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
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
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
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
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