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Generative AI vs. predictive AI: Understanding the differences
Generative AI and predictive AI vary in how they handle use cases and unstructured and structured data, respectively. Explore the benefits and limitations of each. Continue Reading
gradient descent
Gradient descent is an optimization algorithm that refines a machine learning (ML) model's parameters to create a more accurate model. Continue Reading
Learn how to create a machine learning pipeline
Well-considered machine learning pipelines provide a structured approach to AI development in modern IT environments, ensuring uniformity, speed and business alignment. Continue Reading
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Attributes of open vs. closed AI explained
What's the difference between open vs. closed AI, and why are these approaches sparking heated debate? Here's a look at their respective benefits and limitations. Continue Reading
Generative models: VAEs, GANs, diffusion, transformers, NeRFs
Choosing the right GenAI model for the task requires understanding the techniques each uses and their specific talents. Learn about VAEs, GANs, diffusion, transformers and NerFs. Continue Reading
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Definitions to Get Started
- 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)
- data splitting
- machine learning engineer (ML engineer)
GitHub Copilot vs. ChatGPT: How do they compare?
Copilot and ChatGPT are generative AI tools that can help coders be more productive. Learn about their strengths and weaknesses, as well as alternative coding assistants.Continue Reading
large language model operations (LLMOps)
Large language model operations (LLMOps) is a methodology for managing, deploying, monitoring and maintaining LLMs in production environments.Continue Reading
Supervised vs. unsupervised learning explained by experts
Learn the characteristics of supervised learning, unsupervised learning and semisupervised learning and how they're applied in machine learning projects.Continue Reading
automated machine learning (AutoML)
Automated machine learning (AutoML) is the process of applying machine learning models to real-world problems using automation.Continue Reading
A guide to deploying AI in edge computing environments
Deploying AI at the edge is increasingly popular due to processing speed and other benefits. Consider hosting requirements, latency budget and platform options to get started.Continue Reading
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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
How to build a machine learning model in 7 steps
Building a machine learning model is a multistep process involving data collection and preparation, training, evaluation, and ongoing iteration. Follow these steps to get started.Continue Reading
AI, copyright and fair use: What you need to know
As AI technology advances, U.S. and international copyright laws are struggling to keep pace, raising legal and ethical questions about ownership and AI-generated content.Continue Reading
What is artificial intelligence (AI)? Everything you need to know
Artificial intelligence is the simulation of human intelligence processes by machines, especially computer systems.Continue Reading
Compare natural language processing vs. machine learning
Both natural language processing and machine learning identify patterns in data. What sets them apart is NLP's language focus vs. ML's broader applicability to many AI processes.Continue Reading
The different types of machine learning explained
Rigorous experimentation is key to building machine learning models. Learn about the main types of ML models and the many factors that go into training the right one for the task.Continue Reading
What is Google Gemini (formerly Bard)
Google Gemini -- formerly called Bard -- is an artificial intelligence (AI) chatbot tool designed by Google to simulate human conversations using natural language processing (NLP) and machine learning.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
machine learning engineer (ML engineer)
A machine learning engineer (ML engineer) is a person in IT who focuses on researching, building and designing self-running artificial intelligence (AI) systems to automate predictive models.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
telepresence robot
A telepresence robot is a robotic device that enables a user to maintain a virtual presence in a remote location.Continue Reading
Gemma
Gemma is a collection of lightweight open source generative AI models designed mainly for developers and researchers.Continue Reading
data poisoning (AI poisoning)
Data or AI poisoning attacks are deliberate attempts to manipulate the training data of artificial intelligence and machine learning models to corrupt their behavior and elicit skewed, biased or harmful outputs.Continue Reading
OpenAI
OpenAI is a private research laboratory that aims to develop and direct artificial intelligence (AI) in ways that benefit humanity as a whole.Continue Reading
How to build an MLOps pipeline
Machine learning initiatives involve multiple complex workflows and tasks. A standardized pipeline can streamline this process and maximize the benefits of an MLOps approach.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
How to identify and manage AI model drift
The training data and algorithms used to build AI models have a shelf life. Detecting and correcting model drift ensures that these systems stay accurate, relevant and useful.Continue Reading
semantic search
Semantic search is a data searching technique that uses natural language processing (NLP) and machine learning algorithms to improve the accuracy of search results by considering the searcher's intent and the contextual meaning of the terms used in ...Continue Reading
Best practices for getting started with MLOps
As AI and machine learning become increasingly popular in enterprises, organizations need to learn how to set their initiatives up for success. These MLOps best practices can help.Continue Reading
facial recognition
Facial recognition is a category of biometric software that maps an individual's facial features to confirm their identity.Continue Reading
What is the inception score (IS)?
The inception score (IS) is a mathematical algorithm used to measure or determine the quality of images created by generative AI through a generative adversarial network (GAN).Continue Reading
What are graph neural networks (GNNs)?
Graph neural networks (GNNs) are a type of neural network architecture and deep learning method that can help users analyze graphs, enabling them to make predictions based on the data described by a graph's nodes and edges.Continue Reading
What are vector embeddings?
Vector embeddings are numerical representations that capture the relationships and meaning of words, phrases and other data types.Continue Reading
What are masked language models (MLMs)?
Masked language models (MLMs) are used in natural language processing (NLP) tasks for training language models.Continue Reading
What is 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
prompt chaining
Prompt chaining is a technique used when working with generative AI models in which the output from one prompt is used as input for the next.Continue Reading
Embedding models for semantic search: A guide
Embedding models in semantic search are changing how we interact with information by going beyond keyword matching to capture meaning and relationships in text and other data.Continue Reading
How to use Perplexity AI: Tutorial, pros and cons
AI-powered search engine Perplexity offers a conversational tone and much-needed source citations -- but it's not perfect. Learn how the tool works and how to start using it.Continue Reading
vision language models (VLMs)
Vision language models (VLMs) combine machine vision and semantic processing techniques to make sense of the relationship within and between objects in images.Continue Reading
neuro-symbolic AI
Neuro-symbolic AI combines neural networks with rules-based symbolic processing techniques to improve artificial intelligence systems' accuracy, explainability and precision.Continue Reading
Tips for planning a machine learning architecture
When planning a machine learning architecture, organizations must consider factors such as performance, cost and scalability. Review necessary components and best practices.Continue Reading
Mixture-of-experts models explained: What you need to know
By combining specialized models to handle complex tasks, mixture-of-experts architectures can improve efficiency and accuracy for large language models and other AI systems.Continue Reading
How to build an enterprise generative AI tech stack
Generative AI tech stacks consist of key components like LLMs, vector databases and fine-tuning tools. The right tech stack can help enterprises maximize their generative AI ROI.Continue Reading
AI red teaming
AI red teaming is the practice of simulating attack scenarios on an artificial intelligence application to pinpoint weaknesses and plan preventative measures.Continue Reading
How to get started with machine learning
Machine learning roles are rapidly evolving and require a diverse range of skills. Looking to join the field? Start by exploring job responsibilities and required experience.Continue Reading
chain-of-thought prompting
Chain-of-thought prompting is a prompt engineering technique that aims to improve language models' performance on tasks requiring logic, calculation and decision-making by structuring the input prompt in a way that mimics human reasoning.Continue Reading
The need for common sense in AI systems
Building explainable and trustworthy AI systems is paramount. To get there, computer scientists Ron Brachman and Hector Levesque suggest infusing common sense into AI development.Continue Reading
Compare large language models vs. generative AI
While large language models like ChatGPT grab headlines, the generative AI landscape is far more diverse, spanning models that are changing how we create images, audio and video.Continue Reading
Prompt engineering tips for ChatGPT and other LLMs
Master the art of prompt engineering -- from basic best practices to advanced strategies -- with practical tips to get more precise, relevant output from large language models.Continue Reading
augmented intelligence
Augmented intelligence is the use of technology to enhance a human's ability to execute tasks, perform analysis and make decisions.Continue Reading
BERT language model
BERT language model is an open source machine learning framework for natural language processing (NLP).Continue Reading
natural language processing (NLP)
Natural language processing (NLP) is the ability of a computer program to understand human language as it’s spoken and written -- referred to as natural language.Continue Reading
Improve AI security by red teaming large language models
Cyberattacks such as prompt injection pose significant security risks to LLMs, but implementing red teaming strategies can test models' resistance to various cyberthreats.Continue Reading
fine-tuning
Fine-tuning is the process of taking a pretrained machine learning model and further training it on a smaller, targeted data set.Continue Reading
The role of trusted data in building reliable, effective AI
Without quality data, creating and managing AI systems is an uphill battle. Methods such as zero-copy integration and primary key consistency can ensure trusted data for better AI.Continue Reading
8 top generative AI tool categories for 2024
Need a generative AI-specific tool for your organization's development project? Explore the major categories these tools fall into and their capabilities.Continue Reading
Retrieval-Augmented Language Model pre-training
A Retrieval-Augmented Language Model, also referred to as REALM or RALM, is an artificial intelligence language model designed to retrieve text and then use it to perform question-based tasks.Continue Reading
AI model optimization: How to do it and why it matters
Challenges like model drift and operational inefficiency can plague AI models. These model optimization strategies can help engineers improve performance and mitigate issues.Continue Reading
AgentGPT
AgentGPT is a generative artificial intelligence tool that enables users to create autonomous AI agents that can be delegated a range of tasks.Continue Reading
autonomous artificial intelligence (autonomous AI)
Autonomous artificial intelligence (AI) is a branch of AI in which systems and tools are advanced enough to act with limited human oversight and involvement.Continue Reading
Video guide to generative AI
Generative AI has the potential to revolutionize technology. Learn about popular interfaces such as ChatGPT, the future of generative AI and its effects on businesses.Continue Reading
knowledge graph in ML
In the realm of machine learning (ML), a knowledge graph is a graphical representation that captures the connections between different entities.Continue Reading
ChatGPT explained in a minute
ChatGPT is an AI-powered chatbot developed by OpenAI. With its ability to communicate in natural language patterns, it can create various types of content for many use cases.Continue Reading
Artificial intelligence vs. human intelligence: Differences explained
Artificial intelligence is humanlike. There are differences, however, between natural and artificial intelligence. Here are three ways AI and human cognition diverge.Continue Reading
How AI is advancing assistive technology
Recent advances in generative AI could revolutionize assistive technology. For people relying on assistive tools, AI-powered devices could usher in a new era of accessibility.Continue Reading
conversational AI (conversational artificial intelligence)
Conversational AI (conversational artificial intelligence) is a type of AI that enables computers to understand, process and generate human language.Continue Reading
artificial intelligence (AI) governance
Artificial intelligence governance is the legal framework for ensuring AI and machine learning technologies are researched and developed with the goal of helping humanity adopt and use these systems in ethical and responsible ways.Continue Reading
convolutional neural network (CNN)
A convolutional neural network (CNN) is a category of machine learning model, namely a type of deep learning algorithm well suited to analyzing visual data.Continue Reading
What is sentiment analysis?
Learn how AI is used to perform sentiment analysis, the different categories of sentiment that can be identified and how the analysis can be used to improve customer satisfaction.Continue Reading
What is natural language processing (NLP)?
NLP enables computers to understand language like humans. This video explores its techniques, applications and challenges, highlighting its importance in businesses.Continue Reading
Explore the impact of data science in business workflows
Data science and machine learning are reshaping business workflows and customer experiences, ushering in an era of highly tailored services and predictive strategies.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 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
How an AI governance framework can strengthen security
Learn how AI governance frameworks promote security and compliance in enterprise AI deployments with essential components such as risk analysis, access control and incident response.Continue Reading
deep tech
Deep technology, or deep tech, refers to advanced technologies based on some form of substantial scientific or engineering innovation.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
Compare 8 prompt engineering tools
To get the most out of large language models, developers and other users rely on prompt engineering techniques to achieve their desired output. Review 8 tools that can help.Continue Reading
adversarial machine learning
Adversarial machine learning is a technique used in machine learning (ML) to fool or misguide a model with malicious input.Continue Reading
How to become an MLOps engineer
Explore the key responsibilities and skills needed for a career in MLOps, which focuses on managing ML workflows throughout the model lifecycle.Continue Reading
A guide to ChatGPT Enterprise use cases and implementation
ChatGPT Enterprise promises powerful generative AI capabilities for business use cases, but successful implementation requires careful planning for security, costs and integration.Continue Reading
How to build a winning AI strategy, explained by experts
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
robo-advisor
A robo-advisor is a virtual financial advisor powered by artificial intelligence (AI) that employs an algorithm to deliver an automated selection of financial advisory services.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
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
How do LLMs like ChatGPT work?
AI expert Ronald Kneusel explains how transformer neural networks and extensive pretraining enable large language models like GPT-4 to develop versatile text generation abilities.Continue Reading
Demystifying AI with a machine learning expert
In this interview, author Ronald Kneusel discusses his new book 'How AI Works,' the recent generative AI boom and tips for those looking to enter the AI field.Continue Reading
AI watermarking
AI watermarking is the process of embedding a recognizable, unique signal into the output of an artificial intelligence model, such as text or an image, to identify that content as AI generated.Continue Reading
data dignity
Data dignity, also known as data as labor, is a theory positing that people should be compensated for the data they have created.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
Machine learning vs. neural networks: What's the difference?
Though machine learning and neural networks are both forms of AI, neural networks are a specific type of ML algorithm. Learn more about their similarities and differences.Continue Reading
ambient intelligence (AmI)
Ambient intelligence, sometimes referred to as 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
neural net processor
A neural net processor is a central processing unit (CPU) that holds the modeled workings of how a human brain operates on a single chip.Continue Reading
prompt engineering
Prompt engineering is an AI engineering technique encompassing the process of refining LLMs with specific prompts and recommended outputs, as well as the process of refining input to various generative AI services to generate text or images.Continue Reading
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
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
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