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• AI is supposed to cut lots of jobs? Not so fast

  Workers have long feared AI will one day displace them. But emerging evidence suggests otherwise: AI might preserve jobs, even as it reshapes roles and skill requirements. Continue Reading

• Democratizing AI in business: The good, bad and ugly

  AI democratization planned and introduced correctly can profoundly increase AI's business value -- but inadequate AI tools and poor workforce training can bring it all down. Continue Reading

• Business vs. provider: AI software restrictions to know

  How much control do businesses have over the use of AI platforms they buy? Vendor acceptable use contracts and policies can determine an AI deployment's success or failure. Continue Reading

• GenAI in accounting: Chat BDO's ride from pilot to production

  Accounting and advisory firm BDO built and deployed a proprietary AI platform so its tax and audit pros could automate routine tasks and significantly increase client-facing time. Continue Reading

• GenAI in product manufacturing cuts costs but adds risks

  In product design and manufacturing, GenAI systems are consolidating supplier data, improving processes and cutting significant software costs -- yet they raise unique concerns. Continue Reading

• Definitions to Get Started

  • What is automated machine learning (AutoML)?
  • What are AI agents? Types and examples
  • What is an intelligent agent? Definition, use cases and benefits
  • What is natural language processing (NLP)?

  • What is a neural network?
  • What is AgentOps? What it does and how it powers AI agents
  • What is neural radiance field (NeRF)?
  • What is Gemma? Google's open sourced AI model explained

  View All Definitions

• Overcome roadblocks to GenAI adoption and unlock ROI

  GenAI deployments can fall prey to unrealistic goals, misguided pilots, job loss fears, hidden costs and lack of trust. Governance and workforce readiness are keys to success.Continue Reading

• History of generative AI innovations spans 9 decades

  Rapid GenAI advances are reshaping industries, sparking legal battles and driving embodied AI innovations, paving the way for transformative business processes and tools.Continue Reading

• Businesses face complex cost-cutting options with GenAI

  Some GenAI cost saving candidates might disappoint. The best approach to cost reductions vary according to the business function and an enterprise's strategic business priorities.Continue Reading

• GenAI is ready for more autonomy, but supply chains are not

  Disruptions, vulnerabilities, late deliveries and customer interactions are among the supply chain concerns that GenAI could address autonomously -- if businesses can trust it.Continue Reading

• Smarter robots: Agentic and physical AI converge in business

  The robotics industry is entering a new era where, thanks to AI, robots learn, optimize and solve the world's most complex supply chain, logistics and labor challenges in real time.Continue Reading

• Is GenAI villain and hero in data center power drama?

  GenAI's infrastructure requirements drive up power demands for hyperscalers and other large data centers, but GenAI, and AI-based automation, could also help manage consumption.Continue Reading

• C-suite shakeup: Demand for chief AI officers accelerates

  GenAI's infiltration into virtually every aspect of business demands the C-suite make room for a CAIO focused on AI development, strategy, implementation, education and governance.Continue Reading

• GenAI streamlines enterprise knowledge management process

  Business leaders sharpen insights, speed decisions and boost productivity using GenAI-powered knowledge management systems with their ability to unify and synthesize data.Continue Reading

• 10 AI business use cases that produce measurable ROI

  When justifying their investments in AI deployments, business leaders know keeping up with the Joneses isn't enough without uncovering a positive ROI. Here's where to find it.Continue Reading

• Context engineering takes prompting to a higher business level

  In the care and feeding of AI models and chatbot interfaces, prompting alone can be a fool's errand in strategic business planning without the proper context to interpret prompts.Continue Reading

• The dollars and sense of implementing AI

  Calculating ROI of an AI project to prove business value requires a complicated mix of costs, including data prep, infrastructure, integration, staffing, training and power needs.Continue Reading

• Regression in machine learning: A crash course for engineers

  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

• AI governance can make or break data monetization

  As pressures mount for businesses to get the most value from their data, AI governance ensures the data to be monetized is secure, protected, trustworthy and used responsibly.Continue Reading

• 4 types of machine learning models explained

  Rigorous experimentation is key to building machine learning models. Learn about the main types of ML models and the factors that go into picking and training them for a specific task.Continue Reading

• 9 top generative AI tool categories for 2026

  Agentic systems and AI data centers are driving forces shaping the development of GenAI tools and frameworks to build LLMs, orchestrate processes and integrate physical AI.Continue Reading

• What is automated machine learning (AutoML)?

  Automated machine learning (AutoML) is the automated process that applies machine learning models to real-world problems.Continue Reading

• How engineers can build a machine learning model in 8 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

• What are AI agents? Types and examples

  AI agents are autonomous intelligent software components that form the foundation of artificial intelligence (AI) systems.Continue Reading

• What is an intelligent agent? Definition, use cases and benefits

  An intelligent agent is a program that can perceive its environment, make decisions, take action and perform services based on its environment, user input and previous experiences.Continue Reading

• What is 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

• What is a neural network?

  A neural network is a machine learning (ML) model designed to process data in a way that mimics the function and structure of the human brain.Continue Reading

• How ReAct agents can transform the enterprise

  Humans solve complex problems with reasoning and actionable steps. Now, agentic AI can do the same. Are ReAct agents the future of enterprise problem-solving?Continue Reading

• Agentic AI architecture: An enterprise guide

  Agentic architectures can work independently to automate and orchestrate complex tasks in manufacturing, retail operations and supply chains but they present several challenges.Continue Reading

• How agentic RAG supports effective business workflows

  AI agents can complete business tasks with little to no human intervention. What if they could access domain-specific knowledge when completing those tasks?Continue Reading

• What is AI agent memory? Types, tradeoffs and implementation

  AI agents with short- and long-term memory leapfrog simple task-oriented assignments into areas of autonomy, pattern recognition, personalization and strategic business planning.Continue Reading

• How to build your first agentic AI system

  Agentic AI systems can be a value add for many businesses -- but only if they're built properly. Development teams looking to build agentic AI can use this guide to get started.Continue Reading

• AI agent frameworks: A guide to evaluating agentic platforms

  Navigate the agentic AI tool landscape and accelerate successful deployment with this comparison of AI agent frameworks, platforms and capabilities.Continue Reading

• What is AI orchestration? How it works and why it matters

  AI orchestration manages how models, data, and tools work together, using integration, automation and oversight to support complex systems.Continue Reading

• What is AgentOps? What it does and how it powers AI agents

  AgentOps is the collection of practices, tools and systems that organizations use to create, deploy and manage AI agents in operational situations.Continue Reading

• AI agent vs. chatbot: Breaking down the differences

  Despite using similar AI technologies, AI agents automate tasks while chatbots converse with users. Understanding their differences is key to using the right AI for business needs.Continue Reading

• IBM's enterprise AI vision for customization, collaboration

  IBM focuses on the enterprise by making its WatsonX platform customizable for different cloud environments and applications.Continue Reading

• Vertical AI agents explained: The future of enterprise tech

  The need for ever more AI expertise and performance has spawned vertical AI agents -- a new breed of autonomous agents purpose-built for specific industries. Learn how they work.Continue Reading

• Agentic AI vs. generative AI: What's the difference?

  While often discussed together, agentic AI and generative AI have distinct differences. Understanding those differences is key to implementing both effectively.Continue Reading

• Why does AI hallucinate, and can we prevent it?

  Despite their sophistication, LLMs still often produce inaccurate or misleading output. Will these hallucinations ever go away for good?Continue Reading

• What is neural radiance field (NeRF)?

  Neural radiance fields (NeRFs) use deep learning to turn 2D images of objects or scenes into detailed 3D representations by encoding the entire scene into an artificial neural network.Continue Reading

• What is Gemma? Google's open sourced AI model explained

  Gemma is a collection of lightweight open source generative AI models designed mainly for developers and researchers.Continue Reading

• What is GenAI? Generative AI explained

  Generative artificial intelligence, or GenAI, uses sophisticated algorithms to organize large, complex data sets into meaningful clusters of information in order to create new content, including text, images and audio, in response to a query or ...Continue Reading

• What is Perplexity AI?

  Perplexity AI is an artificial intelligence-powered web search tool that can generate answers to user queries and complete other content-generation tasks.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

• What are diffusion models?

  Diffusion models are a category of generative AI that excels at creating images, audio, video and other types of data by using a two-step process: forward diffusion and reverse diffusion.Continue Reading

• What is an autoregressive model?

  An autoregressive model is a category of machine learning models in which algorithms predict future data based on a series of their own past data.Continue Reading

• What is a variational autoencoder (VAE)?

  A variational autoencoder (VAE) is one of several generative models that use deep learning to generate new content, detect anomalies and remove noise.Continue Reading

• What is cognitive bias?

  Cognitive bias is a systematic thought process caused by the tendency of the human brain to simplify information processing through a filter of personal experience and preferences.Continue Reading

• What is prompt chaining? Definition and benefits

  Prompt chaining is a technique used when working with generative artificial intelligence (generative AI) models in which the output from one prompt is used as input for the next.Continue Reading

• What are vision language models (VLMs)?

  Vision language models (VLMs) are a type of artificial intelligence (AI) model that can understand and generate text about images.Continue Reading

• What is prompt engineering?

  Prompt engineering is an artificial intelligence (AI) engineering technique that refines large language models (LLMs), with specific prompts and recommended outputs. It also is part of the process of refining input to various generative AI (GenAI) ...Continue Reading

• What is 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

• What is a generative model?

  A generative model uses AI and statistical and probabilistic methods to create representations or abstractions of observed phenomena or target variables.Continue Reading

• What is artificial superintelligence (ASI)?

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

• What is a robo-advisor? Everything to know before using one

  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

• What is 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

• What is retrieval-augmented generation (RAG) in AI?

  Retrieval-augmented generation (RAG) is an AI framework that retrieves data from external sources of knowledge to improve the quality of responses.Continue Reading

• Generative AI vs. machine learning: Key differences and use cases

  Generative AI differs from simpler forms of machine learning in several ways, but both can enhance efficiency, personalize customer experiences and drive revenue growth.Continue Reading

• The different types of AI explained

  Despite the rapid evolution and mind-boggling capabilities of AI tools, AI does not yet possess the general intelligence of humans, let alone ASI. Learn about four levels of AI.Continue Reading

• What is 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

• What is 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

• What is artificial intelligence as a service (AIaaS)?

  Artificial intelligence as a service (AIaaS) is a cloud-based service that enables organizations to access artificial intelligence (AI) through a third-party offering.Continue Reading

• AI readiness: What is it, and is your business ready?

  Artificial intelligence (AI) readiness encompasses all the elements, processes and steps needed to prepare an organization to implement AI systems.Continue Reading

• What is 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

• What is a convolutional neural network (CNN)?

  A convolutional neural network (CNN) is a category of machine learning model. Specifically, it is a type of deep learning algorithm that is well suited to analyzing visual data.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

• What is 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

• What is 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

• What is data poisoning (AI poisoning) and how does it work?

  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

• What is 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

• What is 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

• What is computational linguistics? Definition and career info

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

• How to detect AI-generated content

  AI- or human-generated? To test their reliability, six popular generative AI detectors were asked to judge three pieces of content. The one they got wrong may surprise you.Continue Reading

• What is 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

• What is a knowledge graph in ML (machine learning)?

  In the realm of machine learning (ML), a knowledge graph is a graphical representation that captures the connections between different entities.Continue Reading

• What is an 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

• What is 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

• What is AI art and how is it created?

  Artificial intelligence art (AI art) is any form of art that has been created or enhanced with AI tools.Continue Reading

• What is responsible AI?

  Responsible AI is an approach to developing and deploying artificial intelligence (AI) from both an ethical and legal point of view. The goal of responsible AI is to use AI in a safe, trustworthy and ethical fashion.Continue Reading

• What is conversational AI (conversational artificial intelligence)?

  Conversational AI, also known as conversational artificial intelligence, is a type of AI that enables computers to understand, process and generate human language.Continue Reading

• What is a generative adversarial network (GAN)?

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

• Interpretability vs. explainability in AI and machine learning

  Understanding how AI models make decisions is challenging, but two concepts -- interpretability and explainability -- can shed light on model outputs.Continue Reading

• How to effectively manage AI projects in 12 steps

  AI is a high priority for companies but results often fall short of expectations. These 12 steps will help you successfully manage AI projects and deliver business value.Continue Reading

• How to create a winning AI strategy for your business

  To deliver real business value, AI projects must be aligned with organizational goals. Here is a 10-step program for developing an effective AI strategy, plus sample templates.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

• What is a 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

• What is AI (Artificial Intelligence)? Definition, Types, Examples & Use Cases

  Artificial intelligence is the simulation of human intelligence processes by machines, especially computer systems.Continue Reading

• Responsible AI vs. ethical AI: What's the difference?

  Ethical AI establishes principles for AI development and use, while responsible AI ensures they're implemented in practice. Learn how the two differ and complement each other.Continue Reading

• AI parameters: Explaining their role in AI model performance

  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

• What is embodied AI? How it powers autonomous systems

  Embodied AI refers to artificial intelligence systems that interact with and can learn from their environments using a suite of technologies that include sensors, motors, machine learning and natural language processing.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

• What is linear regression?

  Linear regression is a statistical technique that identifies the relationship between the mean value of one variable and the corresponding values of one or more other variables.Continue Reading

• What is deep learning and how does it work?

  Deep learning is a type of machine learning (ML) and artificial intelligence (AI) that trains computers to learn from extensive data sets in a way that simulates human cognitive processes.Continue Reading

• What is an AI accelerator?

  An AI accelerator is a type of hardware device that can efficiently support AI workloads.Continue Reading

• Trustworthy AI explained with 12 principles and a framework

  To be considered trustworthy, AI systems should meet these 12 principles and employ a four-step framework to ensure the use of AI is ethical, lawful and robust.Continue Reading

• What is machine learning bias (AI bias)?

  Machine learning bias, also known as '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 (ML) process.Continue Reading

• What business leaders should know about EU AI Act compliance

  AI compliance expert Arnoud Engelfriet shares key takeaways from his book 'AI and Algorithms,' describing the EU AI Act's effects on innovation, risk management and ethical AI.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

• What is singularity in technology and AI?

  In technology, the singularity describes a hypothetical future where technology growth is out of control and irreversible.Continue Reading

• What is the 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