Small, iterative changes to an existing business model, such as adding a new product to the existing offering.
"An example of incremental innovation would be a coffee shop adding iced coffee to the menu alongside the existing hot beverages."
Domain-specific factors that influence a company's strategy, such as the number and power of a company's competitive rivals, regulation, new market entrants, suppliers, and the threat of substitute products.
"Industry forces such as generative AI systems are forcing education companies to revisit their business models, as traditional pay-for-content approaches are harder to justify."
Creation of narrow or focused artificial intelligences for use in a specific industry (like BloombergGPT's 50-billion-parameter finance model) or domain (like FoodUDT-1B, which has a billion food-specific parameters).
"ChatGPT was useful but not particularly creative for cooks, and too broad for a narrow use. In comparison, FoodUDT-1B recognizes that an input containing 'apple' is more likely to be about fruit than a computer company."
Software and hardware used to organize data, often inside organizations. "IT" can also be shorthand for not just information technology, but the teams/departments who build and maintain it.
"IT used to mean the people I'd call when my work computer froze up, but now tech is part of most of our products and customer interactions; I know the board considered creating a 'digital' team to separate out IT's product efforts from utility functions."
Ensuring that users who provide their data know where and how that data will be used, and what this might mean for them in the future.
"Clicking 'accept' without reading and fully understanding the agreement—and the related technologies, like Generative AI—does not count as informed consent."
Applying the concepts of open-source software to proprietary software. This means only those inside the business can edit it, with the intention to take advantage of open-source management benefits (like shared code and documentation and agile development) without risking outside influence on essential software.
“Several teams are working on that—we’ve innersourced the common functions to keep security and performance high.”
Understandings derived from analyzing data; crucially separate from the data itself.
"The insights we gained from the new app data are central to updating our user interface—it turns out that users don't like having to turn their phone sideways to see videos, so we're going to introduce a vertical format."
Artificial Intelligence (AI) is sometimes best thought of as 'intelligence augmentation.' Artificial intelligence implies being autonomous and aware in a way that is unrealistic for machines. Intelligence Augmentation better describes what machines are capable of at the moment, which is support for human intelligence.
"When we stopped thinking of it as artificial intelligence and started thinking of it more as intelligence augmentation, it was easier to see how it would fit into our very relationship-focused business."
The ability for devices to share data and communicate with one another and with human users through an internet connection. Commonly used to refer to 'smart home' devices or sensor networks.
"The Internet of Things makes it possible for my phone to automatically tell the heater and lights to turn on at my house when I'm on my way home from work."
Tracking specific problems (like bugs, security, and missed user expectations) as 'tickets' with a case history, associated user/stakeholder contacts, prioritization, and plans for resolution.
"The call center rep listened to the user's problems and suggested a few fixes, but when they did not work, she created a ticket to ensure the problem was solved by the development team (and that the customer was notified)."
The things a business does to create value for customers.
"The coffee shop's key activities include providing a social space outside of work and home, providing a selection of tasty foods, and, of course, selling coffee."
Suppliers, vendors, and other partners required for a business to function.
"The coffee shop's key partners would be the roastery that supplies coffee beans."
The most important assets, infrastructure, ideas, and technologies that the business needs to work properly.
"One of the key resources of Apple is a talented and skilled tech support workforce to help users at the Apple Store's Genius Bar and on its support lines."
A knowledge graph is a structured representation of knowledge that captures relationships between entities, concepts, or facts in a specific domain. It organizes information in a graph-like structure, where nodes represent entities or concepts, and edges represent the relationships between them.
"As we built our movie chatbot, we created a knowledge graph of all the movies available at our library, cross-referenced in many different ways, like what kind of story they told."
An AI-powered system designed to understand and generate human language. Language learning models are trained on sets of existing data to identify and synthesize patterns in language. Language learning models are considered part of the natural language processing and generative AI fields. Common LLMs include ChatGPT and BERT.
"When you check your grammar with our tool, the system will update a specific language learning model for your company's particular tone and style."
A software development approach that emphasizes efficiency by creating minimum viable products for testing and iteration, instead of trying to create a perfect product before users try it.
“Using a lean development approach, we were able to get an MVP of our photo editing app to market much sooner, and we can apply users’ feedback to find out which features matter most to users before we invest more in new functions.”
Specific data about an individual (in contrast to Big Data, which aggregates many datapoints).
"Apple Fitness measures distance walked, calories burned, etc., displaying 'little data' about a user to give them insights into their own health and behaviors."
A mental model for machines that reconceptualizes them as peers rather than tools, to prompt new thinking about technology opportunities and threats. The machine coworker model popularized by Causeit cross-references machine capabilities to human thinking styles and roles.
"Our company introduced a new machine coworker, Betty, that we can chat with in Slack to ask questions about our products."
Computer systems that update their algorithms based on datasets/data sources fed to them to become more accurate over time, such as image recognition tools that become more accurate the more images they analyze. Machine learning is usually paired with human correction to avoid false conclusions through both ‘supervised’ and ‘unsupervised’ strategies.
“Self-driving cars use many forms of machine learning to update their ‘awareness’ of the road conditions around them, driver preferences, and traffic patterns.”
Large-scale economic trends that may affect business, such as global market conditions; access to resources; high or low commodities prices.
"Car dealers underestimated the role of macroeconomic forces (like access to capital) and cars sales screeched to a halt as customers balked at higher interest rates."
The actions and needs of buyers and sellers which cause changes in supply and demand for goods and services.
"The value of our content product is determined by market forces of supply and demand for education in general."
A document that details any market conditions that are relevant to a product, including customers and users and what specific problems a product will solve for them.
"The MRD helped us understand what our potential enterprise customers expected and what they will need to accomplish. It helps us make relevant and useful software, because our startup's software developers cannot always directly observe and interview users, and don't necessarily have enterprise work experience."
Data about another piece of data, used to understand, sort, and validate datasets to increase their usefulness.
"The email's metadata includes the sender and recipient, as well as the date and time it was sent."
An online, always-on 3D world that happens in real time. It is a decentralized virtual space where users can interact with other users—both human and AI. The metaverse is accessed through the use of VR, AR and MR tech.
“Acura established the first virtual showroom in the metaverse for cars, and an accompanying NFT.”
Small, single-function services, designed to be interoperable with other microservices on a pick-and-choose basis, offering a fully customizable approach instead of a full suite of tools and functionality from a single provider.
"Amazon created AWS by breaking their Amazon.com website down into each individual function and offering them to other businesses to select only the ones they needed."
A set of algorithms that is designed to perform a specific analysis, such as image classification or natural language processing, based on the input data it is provided. The model is trained on a large dataset, which allows it to make predictions or decisions about new, unseen data. "Model" can also refer to non-algorithmic information (an 'abstraction') used by data scientists to understand the subject matter.
"We created an ML model of our supply chain to predict how long it will take a product to get to customers from the time we begin manufacturing."
The control and/or legal and financial stakes in a given AI system's underlying data. ChatGPT is based on GPT, a model owned by OpenAI. Organizations may wish to create their own AI models to avoid competition or disclosure of private information.
"Our company told us we can't use any customer information with generative AI tools unless we own the large language model due to promises made to our users about privacy."
A single system designed to deal with all of a company's digital needs. It is often proprietary, static, and very difficult to adapt or update.
"Before the software market had matured, many organizations developed massive custom systems with a monolithic architecture mindset to address all of a company's digital needs from one place."
A multimodal model is a type of artificial intelligence system in which multiple input sources are used to generate a single output.
"The document-reading tool's multimodal model allows it to process all elements of a file (visual, text, video and audio) to determine what the document is and what each component means. It then takes action based on that analysis."
Narrow AIs are focused on a particular area of expertise or limited scope. Other terms for narrow AI are 'artificial narrow intelligence' or 'weak AI.'
"Assistant.ai is a well-known narrow AI with a specific purpose of helping people schedule appointments."
A machine capability to synthesize human language from machine content, such as writing a summary of a company's market performance or describing upcoming events from a user's health record in plain terms. NLG is a subset of the field of natural language processing (NLP) and is a necessary step before the synthesis of human-like speech.
"Early natural language generation systems essentially 'filled in the blanks' of ad lib statements like, 'your next appointment is at ____ o'clock;' new systems like ChatGPT can generate much more nuanced outputs such as imitating a particular author's style."
The capability of computers to understand human language. Natural language processing (NLP) evolved from computational linguistics and uses computer science, artificial intelligence, linguistics, and data science methods. In casual use, NLP often encompasses both the understanding and generation of language.
"Siri's breakthroughs in natural language processing means that it can receive voice and text inputs from users and respond in kind, like a conversation with an assistant."
A subset of natural language processing is used to comprehend human language using syntactic (grammar) and semantic (meaning) analysis. NLU is a necessary step before the estimation of language sentiment (tone or feeling).
"InstructGPT, a project of OpenAI, is a natural language understanding model designed to parse the intent and specific parameters of a user's input are properly 'understood' by machines."
The phenomenon in which a network becomes exponentially more valuable as more nodes or connections are added to it, such as the number of people in a social network or train routes in a transit network.
“Facebook had little value before it created network effects; early users created content, which attracted more users, who were attracted by yet more content, and attracted even more users—resulting in exponential growth.”
A specific kind of no-code development tool designed to connect apps and services from various providers via application program interfaces (APIs)—but without requiring custom development.
"We automated our marketing tools with Zapier, a no-code integration tool. When a new user signs up on our website, they are now automatically added to our MailChimp e-mail newsletter, receive a welcome chat message on WhatsApp, and are added to our Salesforce CRM–all of which are from different developers."
A way to connect reusable modules together to create programs or automation with little or no software coding skills. No-code development is intended to simplify and democratize technological innovation by lowering the barriers to technology tool integration, usually inside of a graphical user interface.
"We used a no-code development tool to create an internal app for our company that organizes our customer information, marketing and sales activity, and support tickets into a simple interface."
Software code that is available to and editable by an entire community of developers
"That code is open-source, so anyone can work on it, even if it doesn't have a clear business model, which is awesome—but it does mean we have to participate in the developer community if we want the project to continue to work well for our specific needs."
The element of brand narrative that connects past with future and serves as a source for authenticity.
" Brand DNA is who you are, who you've always been, and what you inspire in others. For example, Nike's DNA might be described as the combination of entrepreneurship, innovation and athleticism."
When a model (such as a machine learning or generative AI large language model) captures the 'noise' of or 'memorizes' training data (rather than detecting patterns and trends which can be generalized to new inputs). An overfit model is too complex for the problem it is intended to solve.
"We dumped all the emails from the entire company into the LLM, and it's overfit. Now random emoji and email signatures end up in the text it generates and it can't really respond 'creatively.'"
Similarities between decomposed elements, allowing them to be grouped together and/or processed in the same way.
"The developers created a number of common patterns for how users needed to interact with the app, so they standardized key parts of the interface to decrease the learning curve and development complexity."
Measurement units to express the estimated overall effort required to implement a backlog item or any other piece of work. Teams assign story points based on complexity, the amount of work, and risk or uncertainty.
"The team started assigning story points to the various user stories and found that there wasn't always agreement on the effort level needed to solve problems in the interface."
A term coined by Barry Johnson, describing the state in which there is truth, wisdom or good options on either side of a seemingly-contrasting choice, such as activity and rest, play and work, hierarchies and networks, or human and machine.
"Polarity thinking steers us away from either-or thinking; for example, seeing that both incremental and exponential strategies can co-exist in a business."
Use of existing AI models to accelerate the development of a particular AI-powered system. For example, well-classified or 'structured' data about an organization's products, a general-purpose image-recognition algorithm, and natural language processing models could all be combined to create a company-specific tool for recognizing or generating images and text about a company's products on social media.
"Part of what makes ChatGPT so effective is the inclusion of many years worth of pre-trained language models, so it 'knew' many things right out of the gate."
Using data, statistical algorithms, and machine learning to calculate the likelihood of future outcomes.
This is different from traditional analytics which focus only on what happened in the past.
"When airlines integrated predictive analytics into their flight update systems, they got much better at forecasting realistic flight times and flight statuses."
A bundle of resources and functions that solve a problem for a user or customer.
"Apple's iCloud product offers data storage, online document editing, photo sharing, and other common functions to iOS and Mac OS users."
Product Management involves balancing business goals with user needs to develop a product that is relevant, feasible, and valuable.
"Our Product Managers ensure we're creating offerings that customers find useful and valuable, while still making a return on our investment. In some apps, a key feature can be though of as its own product."
A document that details what a specific product will be able to do in terms of key functions and features.
"If you want to understand what the app will need to do when it's finished, check out the PRD—it lays out every use case and function the app has."
The maturity level of a piece of software, such as alpha (limited functionality and low reliability), beta (near full functionality but limited reliability), and general availability/GA (fully functional and reliable).
"Microsoft's AI Copilot is at the beta product stage—it's available to select users in the real world so the developers can refine its performance."
A collection of instructions and necessary datasets for a computer to perform functions for a human or machine user. Also known as an app or application.
"After the dev team decomposed the user's needs, modeled a system, found patterns and made algorithms, everything was brought together into a cohesive program people could actually use."
Input for an AI model used to elicit a particular response, such as a question in plain language, a set of keywords, or an image. Prompts provide context and/or instruction to a model, and their quality influences the results it returns. For example, users' questions for tools like Google or ChatGPT generate different responses based on even seemingly-minor word choices or order.
"Our most effective researchers stand out not because of their existing knowledge so much as how good they are at writing the best prompts for Google or ChatGPT to get what they need."
Sequencing a number of prompts for an AI tool, like a generative AI chat system, in order to accomplish a given goal.
"To get this to work, we need to do some basic prompt-chaining—first, feed it our source news article and then ask the tool to 'rewrite the article in a more casual tone' and then 'create a metaphor for the technology shift mentioned' and then 'translate into Spanish.'"
Prompt engineering (also known as prompt crafting or prompt design) refers to the process of designing and refining prompts or instructions given to an AI language model to get the desired responses (such as by adding context or specifying outut formats).
"We had to do some prompt engineering with specific instructions to make sure ChatGPT returned consistent summaries of our articles."
Testing and validating that software functions properly and securely. The term evolved from quality assurance—a step towards the end of the process—to quality assistance, which provides programmers with quality support throughout the development process.
"Pages that didn't render correctly on iPads were caught by the QA teams and their tools."
A type of processing that uses tiny (subatomic) mechanical devices at very low temperatures to solve problems that are not time- or cost-effective with conventional binary computers. Due to quantum physics, the 'qubits' these machines use can be both '1' and '0' at the same time (like shades of gray instead of black vs. white), which allows these machines to solve complex multi-dimensional problems in science, finance, and other important fields.
"Quantum computing's ability to handle massive combinations easily means that it could crack open encrypted data that was previously very time-consuming or impossible to break, causing national security organizations great concern."
Data that has not yet been manipulated, processed, or sorted; rarely of use to humans.
"Raw data, at least at large scale, must be processed in order to be useful."
Humans who deliberately attempt to trick or negatively influence a machine system to increase its quality, accuracy, security, or consistency. Red teams in AI work to lessen the number of offensive, inaccurate, biased, and/or undesirable results users experience. In cybersecurity, red teams are sometimes part of 'white hat' hacking for testing.
"The red team attempted to trick the AI tool into saying racist things so that developers could spot ways to prevent the model from coming to those false conclusions."
a type of machine learning where an AI agent (such as a generative AI chatbot) learns to make better decisions to achieve a goal like 'sounding human.' The agent receives rewards or penalties for the actions it takes—such as thumbs up or thumbs down from a user—and learns to maximize the total reward over time.
"We're using reinforcement learning to training our chatbot to provide the right amount of technical information in answers based on the type of user interacting with it."
A technology designed to create long-term, social and emotional bonds with users. Relational agents often use conversational AI, chat or voice interfaces, and user-specific data to earn rapport and trust with a user, raising many new possibilities—and ethical quandaries.
"Woebot is a relational agent for mental health, designed to support users' reflection and personal growth."
A strategy for 'grounding' AI tools in accurate facts by combining generative and retrieval models. RAG uses a pre-trained model to retrieve relevant information from vetted and verified documents (a knowledge graph) and then uses a generative model to output content based in fact.
"Our chatbot was confidently giving incorrect answers to our patients. Since we're in medicine, that's not acceptable, even for casual use, so we used a RAG strategy so that the chatbot retrieve facts from medical texts but then makes them easier to read for lay users."
Key sources of income for a business model.
"The company's revenue structure included subscriptions, in-app payments and professional service fees."
Using machines to mimic repetitive human processes performed on computers (such as changing file formats or sending out meeting invites). RPA is ideally applied to free up human capacity for more high-value opportunities—and sometimes is used to reduce jobs. RPA does not require machine learning, artificial intelligence, or other advanced technologies and thus is often a first step in automation and augmentation efforts.
“Our company is doing a ‘build your own bot’ RPA project, where IT is helping people automate mundane computer work.”
A technology layer that enables developers to configure, monitor, and manage interactions between various services or microservices designed with interoperability in mind. Users can often choose various options from different providers to create a fully-customizable 'service mesh' that has all the functionality they require.
"The service mesh of the online store included a no-code website builder, inventory management, and payment microservices, each from different providers but working seamlessly via APIs."
IT that is not managed by the IT organization but used by employees to do their work (or otherwise touches company data).
"I copied all of that into a Google Doc so we could work on it together using their new AI tools. It'll be much quicker, just use your personal email account and don't tell anyone we're using shadow IT."
An evolution of monolithic architecture where resources are consolidated into a central organization that serves 'internal clients' in the company.
"Our company's shared services include our facilities, IT, and tax/accounting functions that serve our various operating companies and departments."
In a simple problem, both the problem and solution are known.
"Increasing the visibility of our brand seems like a simple problem—we just need to advertise more or better."
A (usually hypothetical) point in time beyond which predictions of the future are not likely to be accurate. "The Singularity" often refers to a technological singularity, where AI and other advanced tech reach a state so advanced that humans and society are fundamentally and irreversibly changed.
"Some thought leaders say the concept of needing to 'work for a living' will be outdated when The Singularity arrives (since machines will do so much)—while others point out that AI-generated value will not be distributed evenly unless we change our policies."
Common points of discussion or sharing within a community or network that create or reinforce relationships; for example, stories, pictures, tips, or comments.
"The social objects of Facebook include posts, events, and comments."
A set of digital tools and components provided by a company for use by third-party developers who want to make applications that are compatible with a specific platform, operating system or framework.
"Apple offers several different SDKs for developers wanting to create apps for iPhone."
The strategy and process for creating or updating computer programs, taking into account every aspect of the software's use, including planning, deployment, and eventual retirement.
"Originally, our developers' software development life cycle was focused on long-term, well-defined functions; since it didn't always account for how quickly we have to change things in today's market, we've also added in lean development and other approaches."
A tool used by futurists to explore the question "what if?" by creating other-than-real-world scenarios, both utopian—and dystopian. Speculative fiction helps futurists explore and explain how key technologies or other trends could change everyday life.
"To explore AI's impact on our organization, we wrote speculative fiction to imagine how users would interact with digital 'agents' in addition to our existing employees."
A focused, accelerated work period for a team, intended to complete a substantial software development goal.
"Once we finish this sprint on the new user interface, we'll move to the next core part of the app."
A step after a sprint is completed, where all involved share feedback and learnings to improve the experience and efficiency of the next sprint.
"Always keep a note of all the issues and challenges you faced, as we can use them during the sprint retro to learn how to make the process better next time."
Being able to fine-tune, adjust, correct, or otherwise guide an AI system to operate more in line with the expectations and ethics of its owner or user. Traditional analytical algorithms are generally easier to steer—and explain—than machine learning and generative AIs.
"While we've had success steering AI for content recommendations to our users when it was based on tags, we're concerned about adding generative AI to that because it will be harder to adjust."
The creation of plausible, factually-grounded data for training of machine models rather than, or in addition to, importing real-world data. Synthetic data use is intended to reduce bias, quickly train models, and improve accuracy. For example, synthesizing demographically-accurate data about the population of a university might be preferable to risking leaks of individuals' real addresses, grades, or other private information.
"The credit-scoring firm introduced synthetic data that corrected for inherited privilege, to counteract societal biases against women."
A shorthand for describing the effort and/or complexity of a task in a larger project.
"The t-shirt size of the bug fix for capitalized text is an extra-small, but integrating 'sign in with google' is a size large."
A backlog of necessary tech updates, caused by postponing updates for fear of disruption or cost.
"With larger, older companies having decades of tech debt, it's no wonder that newer organizations can move and adapt more quickly to changing circumstances."
Highly specific and rigorous reference and support materials for technologists and other experts
"We try to make sure our technical documentation is updated as often as our user docs are—it makes sure we can bring in new developers quickly. We're able to do that more easily now with generative AI."
a professional with both marketing expertise and technical skills, allowing them to leverage technology and data in marketing strategies and campaigns.
"We hired a technical marketer to turn implement our brand strategy into in-app messages, chat, and marketing automation tools."
Job loss due to automation, augmentation, or other efficiency gains made by new tools. First noted during industrialization, technological unemployment remains both a fear and a reality for workers. While new jobs are often created by tech, workers cannot always transition to them quickly, and it is not certain that digitally-displaced jobs will be replaced with new opportunities.
"I am experiencing technological unemployment—my editing job was replaced by text synthesis tools like ChatGPT and robotic process automation."
A set of tools used together, sometimes in a specific sequence, in order to perform a complex action or process.
"Creating updates for our software products is so much faster and more reliable now that we use a consistent DevOps toolchain to develop and test new versions before release, make sure they are secure, and monitor their performance.”
The mental discomfort or revulsion some humans experience when viewing machine-based experiences or content that realistic, but 'not quite real enough,' such as some AI avatars, generative AI chatbots, or virtual reality.
"This synthesized video is creepy—I wish they had just avoided the uncanny valley and paid a real person to present."
The practice of identifying existing mental models, mindsets, and biases and then selectively 'letting go' of them to make room for new thinking.
"We're unlearning old ways of thinking about our relationship with customers as they move from being consumers of what we make to becoming co-creators of digital content and data."
A purpose for applying a technology to a real problem or opportunity. In business, a 'use case' is a way to ground advanced technology discussions in practical value for the organization or its end users.
"Sure, ChatGPT sounds cool, but right now, there's not a practical use case for it in our regulated environment. We expect to see one soon, but our investors demand clear use cases to justify allocating labor and cash to it."
A final phase of a software development process wherein users determine whether the software performs as intended and expected.
"The team thought they were done with the 'save' dialog box until they got to UAT and found that it didn't show up on Android mobile devices."
The sum of all interactions a user could have with an app or other digital offering. Also can refer to the discipline of examining and working to improve the way that human users must interact with a digital tool or website to get value from it.
"I stopped using that app because the UX was terrible. I could never figure out how to get back to the menu, and it kept logging me out."
Examples of use cases for a product, usually collected from the real world via a feedback loop; essential to Continuous Improvement and Agile development processes.
"With structured user stories, we have a better idea of how our product is actually being used in the real world, by how many people, and how to improve it for our users."
Value Propositions specify how a business's offerings will solve a particular user or customer need and why they are more attractive than other solutions.
"The new app from AcmeCo has a very compelling value proposition—it's a learning app to help people quickly pick up new concepts and skills using techniques informed by brain science to save time and repetition."
Ways a customer's 'jobs to be done' could be easier, faster, or otherwise improved, as described in a Value Proposition.
"Our value prop focuses on a key customer gain: faster time to market for enterprise app developers."
Emotional, social, or functional tasks a user may need to complete, as addressed in a Value Proposition
"Our customer's 'jobs to be done,' like 'create a blog post,' 'come up with social media hashtags' and 'create a press release' are directly mapped to buttons in the app."
Any risks and obstacles a customer may wish to avoid or minimize in the course of their 'jobs to be done', as described in a Value Proposition.
"We relieve the customer's pains for international payments—we make tax, compliance and currency conversion seamless so they can just focus on their products."
In the context of digital factories, velocity is a reflection of a team's ability to communicate efficiently. It refers to the speed at which the software can be adapted to changes in security environments, the needs of users, or business updates.
"One of the best measurements of a digital factory's success is velocity—and we have improved ours ten-fold since switching to an agile methodology."
Virtual reality is technology which immerses a user into a computer generated 3D world, often accessed through VR headsets like Meta's Oculus or HTC's Vive Pro.
"Meta's Oculus devices can be used for VR apps like video games, or for accessing their version of the metaverse."
A traditional, linear method of software development where each phase of the project cascades into the next, and all movement is in a single direction toward a 'finished' product that (hopefully) requires no updates or revisions.
"For compliance reasons, we're using a waterfall approach for this project, so we need to make sure we have all our features planned out before we start development—we won't be able to go back and change them easily."
Early, subtle indications of progress sought by futurists, investors, and ethicists to identify or validate trends. Seen on their own, weak signals may not appear relevant, but can show patterns and directionality when analyzed through a particular lens. Fundamental research breakthroughs (like initial OpenAI GPT models) and early adoption of apps or technologies (like Facebook's rollout in universities in the early 2000s) are examples of weak signals.
"The venture capital board regularly invited guest speakers and researchers to help them make sense of weak signals in the marketplace so they could invest wisely in the right kinds of startups."
In a wicked problem, the problem is not fully known, nor is a solution.
"Climate change is a 'wicked problem'—it involves numerous causes, stakeholders who don't always agree, and effects that are spread across the globe. Worse, solving one aspect might reveal or create other problems."
Another term for broadly-applicable general AI, or sometimes artificial general intelligence (AGI). Contrasts to narrow AI, which is purpose-specific.
"OpenAI's ChatGPT tool can be thought of as a wide AI because it can handle almost any human language prompt."
A map of a webpage(s) or screen(s) showing the visual structure of its functions, abstracted to the most essential information. Primarily used for planning user interface layout, content placement, and navigation through the site, service or app.
"We wanted to see how all the pages on our site will be connected to each other before we placed the content, so we asked our developer to create a wireframe."
