Development Security Operations or DevSecOps is the practice of including security and compliance departments from the beginning of development processes, rather than as a sign-off stage after most architecture, feature and data choices have already been made.
"Before we implemented DevSecOps, we launched fast and often—only to have to postpone or roll back releases once our security and compliance teams saw problems. Now we include security stakeholders at every stage of production."
True understanding of the thinking, data, business models, tools and skills needed for people and companies to digitally transform, ’go digital,’ or offer digital products.
"We're upping our teams' Digital Fluency with a new mentoring and education program."
Digital Twin: a machine data model of a physical object, such as a jet engine, a person's body, or a building. This model is built using precise measurements and is usually 'brought to life' with live sensor readings and predictive machine learning algorithms intended to predict aging, performance, failure risks, and other information.
"The car has a digital twin of the motor and uses an algorithm to adjust recommended maintenance intervals based on how much stress the motor is experiencing."
There is no rigid, 'official' definition, but Digital Value propositions use exponential technologies to offer speed, scale, or ease which is not possible with a conventional value proposition such as one focused on physical assets or human services.
"Uber's original digital value proposition was to offer you 'your own private driver'. Offered to everyday middle-class users in San Francisco, the digital platform marketplace drastically lowered the cost of a private luxury ride."
Inclusion of unique data points (such as pixels, special characters, or key phrases) in AI-generated or -edited content. Digital watermarks can be used to spot plagiarism, manage intellectual property, or lessen the risk of 'deepfakes' and other problematic uses of AI.
"OpenAI announced work on a digital watermark to ensure student use of their tool was properly cited, addressing a key concern of academia and educators."
Analog: 1) the use of signals or information represented by a variable physical quantity, like position, voltage, or wave frequency; 2) a contrast or predecessor to the use of digital computer technologies.
Digital: 1) the use of numbers and mathematical representations (usually the binary 1 or 0) to capture and convey information; 2) software-defined value, offerings, and organizations.
“We used to manage all of our customer relationships through team members in our branches, but now we also work with our customers digitally—via APIs, chat systems and on-demand support documentation.”
A mode of thinking which generates ideas that are not necessarily aligned with a group, organization, or the status quo. This is a desirable kind of thinking in ideation and early stages of innovation.
"Our company struggles with divergent thinking. Although we're quick to say we want new ideas, we're even quicker to say why they won't work. It's why we give the innovation team non-revenue metrics so that good ideas don't get written off before they've been matured a bit."
Configuring and training AI systems for use in particular contexts. Examples include training writing systems for a specific company's tone and vocabulary, ensuring medical systems respond with culturally-appropriate answers, or configuring legal tools for particular jurisdictions.
"AcmeCo trained their large language model in the specific terms used by their users and customers to make their customer service tool more effective and relevant."
A special kind of non-fungible token with dynamic contents which can be updated under certain conditions.
"An artist released a dNFT that layers unique, algorithmically-generated art which displays different results based on the current weather conditions of the user (like an advanced camera filter)."
Artificial intelligence systems which run partially or fully near the sensors or end devices users interact with rather than solely on central servers. Edge AI examples include autonomous vehicle decision-making systems, smartphone facial recognition software, and security camera motion-sensing systems.
"Some of Apple's image recognition occurs on users' devices so that their photo data is not passed through cloud servers and cannot be accessed by Apple or hackers who might breach a cloud system."
Numerical representations of text or other data that make it easy to compare similarity.
"We used embeddings to quickly find documents related to the customer’s support ticket."
A contract outlining the terms and conditions that a user must agree to in order to use a specific app or digital service.
"I know I probably should read all the fine print in a EULA, but I usually just click 'agree' so I can move on to using the app. But now I'm wondering if I gave away rights for my content to train an AI system."
Collections of User Stories, usually grouped according to theme as part of a feedback loop in Agile development and Devops.
"The team grouped all the user stories relating to how users searched for data into an epic."
Expert systems attempt to mirror a human expert's knowledge and decision-making power through absolute knowledge recall from a database. These systems can be thought of as flow charts or 'if this, then that' decision trees.
"Generative AI systems should sometimes be paired with more traditional 'expert systems' to ensure their answers on critical topics like medicine are grounded in facts—in the way a human doctor uses a diagnostic manual to carefully rule out possible diseases and aid in common diagnoses."
Artificial intelligence (AI) or machine learning (ML) models that can be sufficiently reverse-engineered to illustrate why a particular response to a query was given. In lay terms, a human can often (but not always) 'explain their thinking' when questioned about a decision, but not all AI/ML models can due to either their proprietary nature and/or the mathematical processes within.
"Conversational AI like ChatGPT is not always explainable AI, making it unsuitable for situations where decision-making must be explained, such as credit scoring, hiring decisions or academia."
A fundamental change in the way a business creates and delivers value, using network effects that (usually) come with new, digital, technologies.
"Uber's ridesharing business model was an exponential innovation because it harnessed network effects: as more drivers and riders joined the system, the value of the network grew exponentially rather than linearly."
Extended Reality or XR is an umbrella term for any technology that blends the digital world with the analog physical world.
"Our extended reality team is working to make sure our products are usable in virtual worlds, whether VR, augmented reality, the metaverse or video games."
Concern that it won't be possible to keep up with with technology-related job requirements, economic pressures and/or social changes.
"Today I saw a presentation on how all future hires will have to have coding and AI experience—I'm having major FOBO. Does this mean I'm not relevant anymore?
Anxiety about not being able to participate in something exciting or new, or being left out or left behind.
"I see all these AI startups getting tons of cash and attention and talent, and I feel a lot of FOMO—did we time the market wrong? Or are we just getting started?"
Crowd-based, informal classification of data that occurs 'organically' and emerges from users, rather than being imposed from a central power like a taxonomy.
"Twitter's hashtags are the ultimate folksonomy—all hashtags are created or chosen by individual users and emerge as trends."
Something directly and intentionally measured, like a list of stock investments or an image file on a camera.
"The fundamental data about the company includes its quarterly reports, stock performance, and degree of volatility in the marketplace."
Artificial intelligence models that synthesize new data (like text, music, video or images) based on patterns from existing datasets. These models are designed to create new and unique content resembling the input data their algorithms were trained on, like ChatGPT or DALL-E.
"Generative AIs are increasingly being used to replace rote work at our company—but we haven't really addressed how that will affect entry-level jobs."
Software that uses AI to draft marketing copy, blog posts, or ad content.
"The team used a generative AI-powered copywriting tool to create ad variations quickly."
Gradient descent is a step-by-step method used in machine learning to improve a model by reducing its errors. It does this by adjusting the model's settings based on how much it is "off" from the desired outcome. The algorithm calculates the direction and amount of adjustment needed and gradually moves the model towards the best possible performance.
"We used gradient descent and user feedback to tune the model to find the answer most likely to please people using the chatbot."
A data structure made of nodes and connections (edges) that shows relationships, often used in knowledge graphs or social networks.
"The AI used a graph of customer interactions to recommend new products."
a model/strategy that combines a database retrieval mechanism with a language generation model to aid in 'grounded' responses (factual, relevant answers), and avoid hallucinations (false answers).
"In order to make sure answers relevant to users, based in the articles our newspaper had actually written, and accurate, we chose a Graph RAG model for our 'fact-checker bot.'"
The practice of ensuring that generative AI tools return results that are accurate ('grounded' in facts) rather than just those which are statistically probable or pleasing to a user.
"OpenAI's ChatGPT can now provide citations of its sources so that users can understand the context of its answers."
A control or safeguard placed around AI systems to limit harmful or undesired outputs.
"The platform added AI guardrails to block inappropriate language in customer chats."
Rules or filters that limit what an AI can say or do, usually for safety or compliance.
"Guardrails prevented the bot from giving financial advice outside approved guidelines."
In the context of AI, a hallucination refers to a situation where an artificial intelligence system generates or perceives information that is not based on real or accurate data. It is an erroneous or false perception or output produced by the AI system.
"ChatGPT thought that in addition to owning Causeit, Inc. that I am a screenwriter for Marvel movies. So I said, 'where're my royalty payments?'"
A mental model which blends a new way of thinking with something familiar. The term 'horseless carriage' was a way to introduce the concept of the automobile to a world used to thinking about transportation as horses, qualifying an implied question with a familiar concept: 'How would a carriage function without a horse pulling it?'
"When technologists first introduced the idea of sending messages on the internet, the term 'e-mail' was used as a sort of horseless carriage to make the concept more understandable. Even though far more instantaneous chat messaging was already possible, it was too much of a mental and technological leap for mass adoption."
An open source community of AI users and experts focused on large language models and generative artificial intelligences (LLMs and GenAI). HuggingFace also offers a set of tools like Autotrain, which allow people to create their own AI models and share them with others, and HuggingChat, which is an open-source ChatGPT competitor.
"ChatGPT runs the risk of being disrupted by open source models. Anyone can hop on HuggingFace, connect a few training data sets, and launch something workable without having to use the opaque OpenAI models—but will open source models be of better or worse quality, scalability and ethics?
Inclusion of a human reviewer in an AI system, such as a review of articles a generative AI writes, signoff on legal documents synthesized by an AI attorney, or creative oversight of an image generation tool.
"We need to make sure there's a human in the loop with AI scheduling assistants, especially when talking to VIP clients or scheduling across complex time zones."
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."
Applications where users and AI engage in back-and-forth exchanges, often via chat- or conversation-based interfaces, to co-create or explore content.
"The museum designed an interactive AI experience where visitors could ask a virtual guide about the exhibits."
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 structured way of linking facts and entities to show relationships.
"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.”
A basic statistical method that models the relationship between one variable and another using a straight line.
"We applied linear regression to predict sales based on advertising spend."
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."
The collection of marketing technologies an organization uses to plan, execute, and measure campaigns.
"We added an AI-powered analytics tool to our martech stack."
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."
A standard that lets AI models talk to external tools, APIs, or other models in a safe, structured way—giving them a plug-and-play connector to extend their abilities without retraining.
"Using the MCP, the chatbot pulled information directly from the CRM system without needing retraining."
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 type of AI system inspired by the way brains work, made up of layers of simple math units ("neurons") that learn patterns from data.
"We trained a neural network on thousands of photos so it could recognize cats in new images."
Hybrid AI combining neural and symbolic reasoning.
"Neurosymbolic AI enabled the legal AI agent to evaluate messy contracts while applying complex regulatory logic consistently."
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."
an approach designed to help organizations align their goals and measure their success in a structured and transparent manner by focusing on Objectives and Key Results. It goes beyond Key Performance Indicators (KPIs), which often measure performance of a system but not always outcomes.
"We loaded our OKRs into our project management tool so everyone could map their projects and tasks to them. If a task couldn't be mapped to an OKR, it got de-prioritized."
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."
An AI research and deployment company known for models like GPT, ChatGPT, Sora and DALL·E.
"We used OpenAI’s GPT model to power our customer support chatbot."
The process of adjusting a model’s parameters and/or underlying data to minimize errors or maximize performance on a task.
"Optimizing our model by removing out-of-date map information reduced errors in predicting delivery times."
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.'"
Data that can identify an individual, such as names or phone numbers.
"We stripped PII like phone numbers before feeding customer chats to the AI."
A fine-tuning method for generative AI models, like Adam or LoRA, that fine-tune only parts of a model.
"PEFT let us adjust the model for legal terminology without changing the underlying model, for a lot less compute cost and review time."
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."
Steps applied after a model produces output, such as filtering, formatting, or fact-checking.
"We used post-processing to flag all factual claims for human review."
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."
The automated buying and selling of online ads using software and algorithms.
"We used programmatic advertising to target the right audience in real time."
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."
