Cognitive Project Management for AI – CPMAI At a Glance [Infographic]

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AI & Data Best Practices The Cognitive Project Management for AI (CPMAI) methodology provides a step by step approach to AI project management that has seen significant success in enterprise, government, academic, consulting, and technology vendor implementations. This infographic provides an overview of CPMAI at a glance, but read below for more details.   What …

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The Steps for a Machine Learning Project

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AI & Data Best Practices Following a step-by-step repeatable, documented, and iterative approach will ensure project success. These steps provide an AI project template that provides guidance on each phase in development and provides an agile, flexible approach that allows you to iterate your project as needs change or you develop experience with AI systems. …

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Infographic: The Steps for an AI Project

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AI & Data Best Practices How do you plan an AI project? AI projects can be challenging, daunting, and scary, especially if you’ve never run an artificial intelligence or machine learning project before. Fortunately, there are proven, best practices approaches to running Artificial intelligence projects.   How many Steps are in the Stepwise Approach to …

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Synthetic Data Generation Market: Research Snapshot Feb. 2022

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Machine learning training data is not always readily available. In many cases, “ground truth” data is unavailable, can be difficult to collect, or is considered private, making its use difficult. Synthetic data is often used in scenarios where there isn’t sufficient training data available to be used in machine learning algorithms, especially in supervised machine …

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Data Labeling Market: Research Snapshot Dec. 2021

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In order for machine learning systems to be able to create accurate generalizations, they must be trained on data. Advanced forms of machine learning, especially deep learning neural networks, require significant volumes of data to be able to create models with desired levels of accuracy. Customers often don’t have the resources to label large data …

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Worldwide AI Country Strategies and Competitiveness 2021

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The race for competitive advantage in artificial intelligence (AI) is not just the domain of companies and organizations. Countries vie with each other for dominance in the space of AI, seeking competitive advantages for their industrial ecosystem, military and defense, academic institutions, and areas of private and public sector enterprise. Countries that can take advantage …

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Machine Learning Platforms 2020

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Document ID: CGR-MLP20 | Last Updated: Dec. 8, 2020 Machine learning systems are core to enabling each of the seven patterns of AI. Machine learning platforms facilitate and accelerate the development of machine learning models by providing functionality that combines many necessary activities for model development and deployment. In this report, Cognilytica evaluates five major categories …

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Digitization and Digitalization Report (June 2020)

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Document ID: CGR-DIG20 | Last Updated: Jun. 23, 2020 Digitization focuses on the capturing and extraction of value from non-digital data by converting it to a usable digital state. Digitalization expands upon the idea of digitization by addressing human-bound processes and processes that have previously been dependent on non-digital information. Digitization and Digitalization are seen …

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ML Model Management and Operations 2020 (“MLOps”)

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Document ID: CGR-MOM20 | Last Updated: Mar. 11, 2020 As the markets for AI shift from those organizations that have the technical expertise required to build models from scratch to those enterprises and organizations looking to consume models built by others, the focus shifts from tooling and platforms focused solely on model development to tools …

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Worldwide AI Laws and Regulations 2020

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Document ID: CGR-REG20 | Last Updated: Feb. 20, 2020 The pace of adoption for artificial intelligence (AI) and cognitive technologies continues unabated with widespread, worldwide, rapid adoption of AI and its various patterns. As a result, governments around the world are moving quickly to ensure that existing laws, regulations, and legal constructs remain relevant in …

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Worldwide Country AI Strategies and Competitiveness 2020

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Document ID: CGR-STR20 | Last Updated: Feb. 6, 2020 The race for competitive advantage in artificial intelligence (AI) is not just the domain of companies and organizations. Countries vie with each other for dominance in the space of AI, seeking competitive advantages for their industrial ecosystem, military and defense, academic institutions, and areas of private …

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Voice Assistant Benchmark 2.0 (2019)

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Document ID: CGR-VAB19 | Last Updated: August 31, 2019 Voice assistants are voice-based conversational interfaces paired with intelligent cloud-based back-ends. The device itself provides basic Natural Language Processing (NLP) and Natural Language Generation (NLG) capabilities, and the back-end intelligence gives these devices AI-powered intelligence. Examples of voice assistants include Amazon Alexa, Apple Siri, Google Home, …

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Data Engineering, Preparation, and Labeling for AI 2019

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Document ID: CGR-DE100 | Last Updated: Jan. 31, 2019 It has always been the case that garbage in is garbage out in computing, but it is especially the case with regards to machine learning data. In this report, Cognilytica evaluates the requirements for data preparation solutions that aim to clean, augment, and otherwise enhance data …

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Cognilytica’s Classification of the AI Vendor Ecosystem: Part II

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[Part I of this article here] In our previous article, we explained our classification and categorization of the AI vendor landscape. With almost 3000 vendors to classify in ways that were useful this was no small feat. If you haven’t read that article yet, you should do so now before continuing, because this article builds …

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Cognilytica’s Classification of the AI Vendor Ecosystem: Part I

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[Read Part II of this article here] Cognilytica tracks almost 3000 companies that offer AI-specific or AI-enhanced products for sale in the market. Like most analyst firms, we call these companies “vendors” because they are offering products for sale verses the enterprise “end users” who are implementing them. However, as you can imagine, there’s a …

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Quality Assurance (QA) in the Context of AI

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AI operationalization is different than traditional deployment and putting things into “production”. But if it’s different for deployment and different in development, then it follows that AI projects are unlike traditional projects even with regards to QA. Simply put, you don’t QA AI projects like you QA other projects. This is because the concept of what we’re testing, how we test, and when we test is radically different in AI Projects.

No, Data is NOT the New Oil

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This post was featured in our Cognilytica Newsletter, with additional details. Didn’t get the newsletter? Sign up here In our many travels, conferences, speaking engagements, and other interactions with customers, technology vendors, press and others, we seem to often hear the same refrain: “Data is the new oil” as if that’s supposed to mean something …

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Operationalizing AI

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[Image source: Pixabay] This post was featured in our Cognilytica Newsletter, with additional details. Didn’t get the newsletter? Sign up here When AI practitioners talk about taking their machine learning models and deploying them into real-world environments, they don’t call it deployment. Instead the term that’s used in the industry is “operationalizing”. This might be …

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White Paper: What is Artificial Intelligence?

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Cognilytica is excited to present the “What is Artificial Intelligence” white paper we wrote in collaboration with the Consumer Technology Association (CTA). One way to describe artificial intelligence (AI) is the ability of machines to exhibit the intelligence of humans. People have been working on the development of AI systems for over half a century. …

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Assisted Intelligence vs. Augmented Intelligence

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This post was featured in our Cognilytica Newsletter, with additional details. Didn’t get the newsletter? Sign up here In the conversation around the application and adoption of artificial intelligence (AI) and cognitive technologies, two recurring types of solutions usually come up: AI solutions meant to work in conjunction with people to help them accomplish their …

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