Concern about the future impact of artificial intelligence, such as changes to or loss of jobs, safety, ethics, creativity, law, bias, or surveillance.
"AI anxiety is sweeping our company right now as people realize that what they are currently paid to do can be done by machines more cheaply and consistently. We need to immediately make our AI strategy's impact on jobs clearer.
A tool that allows users (such as software developers) to generate some or all of the code needed to make a program work, increasing the accuracy and velocity of coding efforts. OpenAI's Codex and Github's Copilot are two examples of code assistants.
"Using Codex allowed us to spot bugs in our web app quickly and patch them even though our usual developer was away on leave."
The use of analytical and generative AI tools to create or refine medication, especially to find the right target for medicines in the body, design molecules to interact with that system, and identify people that molecule is most helpful to.
"An AI discovered a potential cure for a rare type of brain cancer, but it may still be difficult to perform real tests and validation due to how few people have this disease."
A standardized way to pass data and commands between multiple programs or systems. Enables different tools to communicate stably and securely with each other for specific tasks—reducing the need for custom integrations.
“We used the Salesforce API to connect our customer data to our e-commerce and billing tools.”
Creation of a model of a system or problem which leaves out any unnecessary parts.
"The data science team created an abstraction of the consumer airline market to see how key changes to supply and demand might affect flight pricing."
An approach to project management (usually in software) consisting of short, iterative cycles of development, emphasizing responsiveness to changing requirements and resources.
"An agile approach to our content means we don't have to try and think up every possible client need—we can launch on the site and then update live as we learn more about how it fares in the real world."
An approach to software project management consisting of short, iterative cycles of development, emphasizing responsiveness to changing requirements and resources. Originally based around the Agile Manifesto, a set of decision principles emphasizing adaptability, working software, and rapid delivery.
"An agile approach means we don't have to try and think up every possible feature or use case—we can launch and then update as we learn more about how it fares in the real world."
A series of unambiguous instructions (usually for machines) to process data, make decisions and solve problems. These may be documented as a series of decisions, like a flow chart or decision tree.
"We created an algorithm to quickly sort customer support requests by topic, priority, and wait time to send them to the right agent and reduce our users' frustration."
Bias embedded in and/or amplified by machine systems, primarily because they are based on existing (biased) human culture and/or lack safeguards like critical thinking.
"The large language model exhibited racist biases when asked certain questions, so we're trying to counter that with new training data and pre- and post-processing (to filter problematic prompts and outputs)."
An adjacent or 'non-traditional' dataset that is used to infer something about a ‘traditional’ dataset, for example using weather data to project a swimwear company's retail sales potential over the summer months.
"By connecting market fundamental data to alternative data about parking patterns at malls around the holidays, we were able to predict which brands would report high or low earnings for the holiday season in time to adjust our position."
A collection of instructions and necessary datasets that allows a computer to perform functions for a human or machine user. Also known as a program or software application. In casual usage, may refer to apps purchased from an app store and/or used on a mobile device.
"My bank is offering an app now, so I can download it and use it on my phone to do my banking instead of logging in to my account through a web browser."
Full artificial intelligence capable of learning or understanding any intellectual task of humans or animals instead of just narrow use cases like scheduling appointments. Full AI is often called Wide AI or sometimes 'strong' AI (which can also refer to sentient or conscious machines).
"Science fiction authors have dreams (or nightmares) that their prediction could come true—an artificial general intelligence could emerge and then soon eclipse humans to rise to the top of the 'food chain' of the planet."
Artificial intelligence emulates human intelligence (knowledge retrieval, problem-solving, and decision-making) in machine systems, either to augment or automate human work. In common usage, AI often includes the concepts of machine learning, analytics, recommendation engines, and expert systems.
"Our new photo editing app uses AI to detect what's in the images users upload and recommends edits based on the 'scene' depicted in the image."
An overlay of digital information from a virtual world onto our analog physical world. AR can be accessed by using smartphones or visual interfaces like Google Glass and/or visors.
"Ikea offers an augmented reality tool to see how furniture will look in your own house."
A user support system reliant on a combination of AI and support documentation to resolve common user issues immediately and escalate to the appropriate parties automatically.
"If a user searches for an answer that is not covered in our FAQ, an auto ticket creation system lets us know so we can reach out to them directly."
Auto-GPT is a code library which can be used to connect generative AI tools to everyday work (like navigating the web and using applications). The Auto-GPT agent(s) set up by users can then automate tasks ranging from simple actions to content creation.
"We used Auto-GPT to take an outline, turn it into an article, find related hashtags and images, and post it on various social media channels."
Automatic Code Generators (ACG) suggest code and functions in real time so that developers can see errors swiftly.
"Github's Copilot X goes beyond traditional automatic code generators to not just recall common functions, but synthesize new code."
A prioritized list detailing the current state of unfinished tasks and dependencies for a given project.
"Add it to the backlog, we'll deal with it as soon as we're done with the urgent stuff."
A conversational AI interface made by Google to search and digest web knowledge for users, based on the company's Large Language Models (LLMs). The generative AI provides plain-language conversational responses and content summaries when people search and learns as they do so.
"Google's Bard, a 'rival' of ChatGPT, will make it so that instead of just seeing webpage results when you search, you'll see answers."
The aggregation of diverse data points into large datasets, followed by analyzing those datasets using Machine Learning to find insights.
"The default strategy (or mental model) for big data is to bring together as many data points as possible to help the company do things better, faster, and/or cheaper."
A specific version of a software or program, after the separate pieces of code have been combined, but before release.
"Once all of these changes have been put into the new build, we'll need to test it before release."
A description of the key components that make up an organization and how it creates value in the world.
"Without a well-considered business model, there's no way the organization could make a profit."
A practical, widely-applied tool for mapping the essentials of a business model, created by Strategyzer.
"The Business Model Canvas really helped me see my business as a whole, without getting distracted by the details."
Forces outside of a specific business model that may still act upon it.
"To understand what new possibilities could be pursued inside the business, leaders need to track what's going on in the business model environment outside the business, like market forces, key trends, industry forces and macroeconomic trends."
An AI language model developed by OpenAI, used for natural language processing tasks, such as generating human-like text responses to prompts. (ChatGPT wrote this definition of itself.)
"ChatGPT is causing an uproar amongst journalists and other knowledge workers as a slew of generic content is being generated, bringing into question the future of their careers."
A text-based interface with a machine using human language, often for the purposes of user or customer support. Chatbots can be built on basic 'expert systems' like a decision tree and database of preset answers, which is the connotation of the term, which may evolve to include interfaces with more complex language learning models like GPT (such as ChatGPT).
"I get so annoyed when chatbots ask what your question is but then only have 2-3 available answers. But when they work well they can save a lot of time."
An employee or other user who builds business apps for themselves using low-code or no-code tools and who doesn't have formal training in computer programming.
"Most of this will be done by 'citizen developers' in the business who build apps for themselves and others using low- or no-code tools, without formal programming training."
Files and other data stored online, rather than on a local hard drive.
"Google Drive, Dropbox, and iCloud are all examples of cloud storage providers."
Machine-readable, absolute instructions using specific structures and programming languages.
"At some point, we need to move from idea to code, or we'll never be able to put this in front of users."
A directory, local or remote, that holds the code being worked on, in various versions, as well as documentation and notes.
"The whole team uses the same code repository, so we can always find the most up-to-date versions of whatever we're working on."
A server whose function is receiving code updates to a repository and distributing builds.
"We organize all of our commits in a code repository manager that helps track progress and debug problems caused by forked code."
A collection of attributes that determine a software or selection of code’s adaptability, efficiency, legibility for other developers, whether it has been tested, and ability to be updated in the future.
"High quality code is stable under testing, easily upgradeable, and has uniform syntax so it is easy for other developers to understand."
Submission of software code to a version-controlled repository, usually grouped around a specific problem which has been solved (such as a bug fix).
"The team committed several changes to the app today, focused on patching security hole and improving pairing with bluetooth devices."
A problem where the problem is understood, but not how to solve it.
"Anticipating business user behavior is a complex problem—there are a lot of interconnected factors that we can't fully understand because we can't fully see the enterprises our customers exist within."
A mindset that allows machines and humans to work together to solve real-world problems, using Decomposition, Abstraction, Patterns, Algorithms, and Programs.
"Using computational thinking, we can break down the task of pouring a glass of water into a series of smaller, machine-friendly tasks, such as 'determine the position of the glass relative to the jug'."
Lightweight packages of application code along with just the things the application specifically depends on, such as specific versions of programming languages and libraries required to run a component of software being programmed.
"By using containers, the developer was able to ensure the software ran in any computing environment across the company, simplifying the deployment process."
The practice of developing software in short, repeated release cycles with the intent to consistently raise its quality, performance or utility—rather than wait for the next major edition of the software before making fixes or improvements. (This is sometimes used interchangeably or in conjunction with ‘continuous improvement.’)
“We always want our customers to have the best, most current version of our app possible, so instead of doing a quarterly update, we practice continuous delivery.”
Continuous Delivery is the practice of developing software in short release cycles where the software is incrementally updated and manually deployed; as opposed to continuous deployment, wherein the software is automatically deployed
"We always want our customers to have the best, most current version of our app possible, so instead of doing a quarterly update, we practice continuous deployment."
The practice of regularly collecting both structured and unstructured assessments and critiques to apply to future development.
"Since we implement continuous feedback, our developers feel like they know our users better."
The usage of automated and manual assessments of a program’s efficiency and stability as soon as the code changes
"Continuous testing is your only safeguard against software failure."
Computer server(s) and program(s) which automatically build and update software according to predefined rules.
"By implementing a CI server in our development pipeline, we automated integrating code changes, which increased the speed and efficiency of our software development process and lowered stress."
AIs designed to create human-like interaction via chat or voice dialog using natural language processing and language learning models like GPT.
"The conversational AI field has reached an inflection point as the size and accuracy of LLMs like GPT have become sufficient (and sufficiently accessible) to allow everyday productivity improvements."
A breakdown of all costs involved in running an organization.
"The cost structure of the business included fixed costs like facilities rent, but also variable costs such as cloud storage and hosting fees."
The ways a business connects with its customers.
"Call centers, help desks, and even community forums are all customer channels being changed by generative AI."
Fictional profiles of users, customers, or other stakeholders who exemplify the kind of individuals an organization wants to serve.
"One of our customer personas is Saul, a 35-year-old single father who works as an attorney and lives in the city center."
The nature of the relationships created between business and its customers, as described in a Business Model.
"Do we have to create all value in our relationships with customers like a traditional widget company, or could we co-create with them like Starbucks does when they crowdsource flavor ideas?"
Dividing a company's customers into groups that reflect similarity among customers in each group, with an eye to relate to each segment in ways that maximize the value of each customer to the business.
"As our user advocate, I identified three customer segments: convenience-seeking young professionals, value-conscious families, and tech enthusiasts. This allowed us to tailor our features and plans to each group."
The merging of organic and inorganic, or human and machine, to create a third type of entity. Cyborgs feature in science fiction (like Robocop). The cyborg concept is also a mental model of humans' relationship to technology as co-constitutive, wherein humans don't just make tech, but it remakes and reshapes them. Implants, exoskeletons, augmented reality, and even lower-tech connections like humans aided by smartphones are all cyborg relationships.
"Humans and their vehicles can be thought of as cyborgs, where the human is both extended by their interface with the machine, but also changed by it—we started to imagine new ways to navigate, more like 'robo-shoes' and less like 'cars.'"
A person who uses the mental model of a human-machine 'cyborg' to study the impact of technology on individuals, cultures, and the planet. Cyborg Anthropologists help businesses and organizations understand the impact of complex issues like artificial intelligence, data ethics, the future of work, and virtual worlds.
"A health company hired a cyborg anthropologist to help them understand how 'augmentation' implants like optical-nerve-to-computer interfaces could positively or negatively affect users' confidence in themselves."
DALL-E is an AI-powered image generator developed by OpenAI. It is a variant of the GPT-3 language model, trained on a diverse dataset of text and images to generate original, high-resolution images from textual descriptions. DALL-E can create a wide range of images, from photorealistic to highly imaginative, based on input text that describes the desired image. (ChatGPT wrote this definition of DALL-E.)
“We were imagining new characters for our video game, and we used DALL-E to quickly turn the character bios into sketches.”
A short, informal meeting at the beginning of the day to share current individual project statuses and make requests for support.
"Fortunately, during the daily standup, I found out the feature that I was planning on rushing out the door is no longer as urgent, so I can refine it a bit more."
A user interface or feature that tricks users into doing things that may not be good for them, often for the benefit of the developer. This term is also sometimes used to describe ongoing problematic patterns in business or culture.
"The biggest tax software maker is known for its dark patterns, such as tricking users into selecting a paid plan when free plans were available, by making it hard to find the free option."
A part of the internet that is not indexed by mainstream search engines and which usually must be accessed through special software (like Tor), known for attracting illegal content, communication, and transactions.
"Hackers leaked the passwords onto the dark web to attract purchasers who intended to use them for fraud and identity theft."
Software tools which show key performance indicators related to business or user needs.
"During meetings, the software team leader would often show a project management dashboard that displayed the current backlog of programming tasks and the team's velocity in finishing them."
Examining and transforming data into information—finding meaning and/or insights through scrutiny.
"Through rigorous data analysis, ProPublica found that the 'predictive sentencing systems' used by judges across the country were regularly over-sentencing black people who turned out to be lower risks than their white counterparts."
The models, policies, rules, and standards that govern which data is collected and how it is stored, arranged, integrated, and put to use in data systems and in organizations.
"When we're merging with AcmeCo, we'll need to update data architectures in both companies to revisit decisions about how we store and process data, and make sure that standards, policies and expectation-setting for users are aligned."
Data that is not actively moving from one device or system to another; for example, files saved to a local hard drive.
"Our company's mindset is very 'Data at Rest:' files in a filing cabinet, rows in a spreadsheet, events on the wall calendar: data is static, only available in one place, and stays the same until a human modifies it."
Comprehensive, organized lists of what datasets are available from an organization or other source.
"This data catalog indicates all of types of customer and user data available within the company, such as website actions, purchases, and contact information."
A set of signed, legally-binding agreements that define the terms and conditions of interactions between two or more parties. Data contracts may specify the roles and responsibilities of each party, ownership of data and usage rights, acceptable levels of privacy, provenance, data sovereignty, methods of data validation, and storage/disposal requirements.
"When we partnered with another company to process our user's inputs into our chatbot, we had to set up data contracts to make sure our users' privacy preferences were honored and that their data stayed in the right legal jurisdictions."
The mindsets, frameworks, values, rules and principles for responsibly gather, manipulating, applying and monetizing data from users and organizations.
"A lot of AI developers are exploring ideas which seem good—like providing increased access to medical information. However, they don't always have a strong data ethics strategy to protect against leaks, give consistent analysis or disclose an AI system's limits to unsuspecting users."
Something recorded or logged from a machine systgem without a specific intent in mind.
"Our data exhaust includes keycard logins, the individual devices that connect to the office wifi, and security camera feeds."
The practice of checking, correcting, labeling, and normalizing data. Common activities related to data hygiene include checking for accuracy, ensuring formats are the same in each dataset (such as the format for date & time), determining or creating a unique identifier (such as an email address or phone number, which allows combining one dataset with others), and categorizing data.
"We have a lot of responses from past marketing efforts, but the data hygiene is very poor—none of the questions asked of users were the same, and the contact information is not checked for accuracy or typos. It would be cheaper to start over than fix it."
Data in Motion is dynamic, 'live', moving and changing in real time, as opposed to a static file saved on one machine.
"Data in motion can be thought of like water—a ‘stream’ like a live video feed or a ‘flow’ of stock market data."
Storing large amounts of data to be processed later; often refers to data 'at rest.'
"Facebook's Social Graph is an enormous data lake that stores countless pieces of data on every user for various analyses, some of which were perhaps not obvious at the time of collection."
Spaces designed for parties to buy, sell, and lease data to each other, including both broad and highly-focused datasets.
"The Amazon Web Services Marketplace offers a very large range of datasets for subscription, with both data providers and data processors; many companies list AI-optimized training data in the marketplace."
Streams of data from various sources aggregated into one flow. Related to the concepts of data lakes and data in motion.
"Through aggregation of many different data streams, we now have a 'data river' of nearly all customer transactions and interactions across all our platforms, from Amazon to Zoom."
The concept that data should be subject to the laws of the country in which is it collected, stored, and processed while it is within that country.
"When we expand into European countries, we have to make sure we respect the data sovereignty requirements which necessitate storing data about EU users in a member state rather than our US servers."
People or machines who disclose data
"The 'historical AI video' based on data subjects like Steve Jobs couldn't consent to their data being used for generative AI training, because generative AI was not something people understood at the time they were recorded."
Classification systems used to group and sort data; usually formal and applied by organizing bodies.
"The Dewey Decimal System is one of the most well-known data taxonomies of the 20th century, used to organize topics in libraries and research."
Breaking down a complex problem into several simpler problems.
"When we decompose hailing a rideshare service, we see that it can be broken down into simpler problems, including determining journey start and end points, finding an efficient route between the two, and calculating an appropriate fare."
Believable impersonation of a human's likeness using advanced machine learning/generative AI tools, usually without consent, to spread misinformation, engage in parody or synthesize content (such as pornography or music). Deepfakes usually refer to photos, audio, or video and may be coupled with text written a particular style and/or distributed on hacked or impersonated social media.
"BuzzFeed shared a video of former U.S. President Barack Obama vulgarly insulting Trump—only to go on to reveal that the video was a deepfake and to caution people about 'truth' on the internet."
A human-centered approach to innovation that focuses on understanding the problems and goals of potential customers or users as a method of defining and testing new product ideas.
"We used design thinking methods, such as user observation and empathy experiences, to ensure that we solve real problems for real people, rather than just spending our time making products we thought might be good but weren't necessarily helpful."
A software development cycle that allows companies to produce, release, and monitor iterative software updates on vastly reduced timetables, compared to traditional development cycles.
"Our DevOps team constantly updates and deploys software as new features, fixes and use cases develop—which was a big mindset shift from older, annual releases which were considered 'done' once launched."
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."
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."
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."
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."
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."
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 Caueit, Inc. that I am a screenwriter for Marvel movies. So I sais, '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."
