What is GPT?
Generative Pre-trained Transformers, commonly known as GPT, are a family of neural network models that uses the transformer architecture and is a key advancement in artificial intelligence (AI) powering generative AI applications such as ChatGPT. GPT models give applications the ability to create human-like text and content (images, music, and more), and answer questions in a conversational manner. Organizations across industries are using GPT models and generative AI for Q&A bots, text summarization, content generation, and search.
Why is GPT important?
The GPT models, and in particular, the transformer architecture that they use, represent a significant AI research breakthrough. The rise of GPT models is an inflection point in the widespread adoption of ML because the technology can be used now to automate and improve a wide set of tasks ranging from language translation and document summarization to writing blog posts, building websites, designing visuals, making animations, writing code, ]researching complex topics, and even composing poems. The value of these models lies in their speed and the scale at which they can operate. For example, where you might need several hours to research, write, and edit an article on nuclear physics, a GPT model can produce one in seconds. GPT models have sparked the research in AI towards achieving artificial general intelligence, which means machines can help organizations reach new levels of productivity and reinvent their applications and customer experiences.
What are the use cases of GPT?
The GPT models are general-purpose language models that can perform a broad range of tasks from creating original content to write code, summarizing text, and extracting data from documents.
Here are some ways you can use the GPT models:
Create social media content
Digital marketers, assisted by artificial intelligence (AI), can create content for their social media campaigns. For example, marketers can prompt a GPT model to produce an explainer video script. GPT-powered image processing software can create memes, videos, marketing copy, and other content from text instructions.
Convert text to different styles
GPT models generate text in casual, humorous, professional, and other styles. The models allow business professionals to rewrite a particular text in a different form. For example, lawyers can use a GPT model to turn legal copies into simple explanatory notes.
Write and learn code
As language models, the GPT models can understand and write computer code in different programming languages. The models can help learners by explaining computer programs to them in everyday language. Also, experienced developers can use GPT tools to autosuggest relevant code snippets.
The GPT model can help business analysts efficiently compile large volumes of data. The language models search for the required data and calculate and display the results in a data table or spreadsheet. Some applications can plot the results on a chart or create comprehensive reports.
Produce learning materials
Educators can use GPT-based software to generate learning materials such as quizzes and tutorials. Similarly, they can use GPT models to evaluate the answers.
Build interactive voice assistants
The GPT models allow you to build intelligent interactive voice assistants. While many chatbots only respond to basic verbal prompts, the GPT models can produce chatbots with conversational AI capabilities. In addition, these chatbots can converse verbally like humans when paired with other AI technologies.
You can now create custom versions of ChatGPT that combine instructions, extra knowledge, and any combination of skills.
We’re rolling out custom versions of ChatGPT that you can create for a specific purpose—called GPTs. GPTs are a new way for anyone to create a tailored version of ChatGPT to be more helpful in their daily life, at specific tasks, at work, or at home—and then share that creation with others. For example, GPTs can help you learn the rules to any board game, help teach your kids math, or design stickers.
Anyone can easily build their own GPT—no coding is required. You can make them for yourself, just for your company’s internal use, or for everyone. Creating one is as easy as starting a conversation, giving it instructions and extra knowledge, and picking what it can do, like searching the web, making images or analyzing data. Try it out at chat.openai.com/create.
Example GPTs are available today for ChatGPT Plus and Enterprise users to try out including Canva and Zapier AI Actions. We plan to offer GPTs to more users soon.
GPTs let you customize ChatGPT for a specific purpose
Since launching ChatGPT people have been asking for ways to customize ChatGPT to fit specific ways that they use it. We launched Custom Instructions in July that let you set some preferences, but requests for more control kept coming. Many power users maintain a list of carefully crafted prompts and instruction sets, manually copying them into ChatGPT. GPTs now do all of that for you.
The best GPTs will be invented by the community
We believe the most incredible GPTs will come from builders in the community. Whether you’re an educator, coach, or just someone who loves to build helpful tools, you don’t need to know coding to make one and share your expertise.
The GPT Store is rolling out later this month
Starting today, you can create GPTs and share them publicly. Later this month, we’re launching the GPT Store, featuring creations by verified builders. Once in the store, GPTs become searchable and may climb the leaderboards. We will also spotlight the most useful and delightful GPTs we come across in categories like productivity, education, and “just for fun”. In the coming months, you’ll also be able to earn money based on how many people are using your GPT.
We built GPTs with privacy and safety in mind
As always, you are in control of your data with ChatGPT. Your chats with GPTs are not shared with builders. If a GPT uses third party APIs, you choose whether data can be sent to that API. When builders customize their own GPT with actions or knowledge, the builder can choose if user chats with that GPT can be used to improve and train our models. These choices build upon the existing privacy controls users have, including the option to opt your entire account out of model training.
We’ve set up new systems to help review GPTs against our usage policies. These systems stack on top of our existing mitigations and aim to prevent users from sharing harmful GPTs, including those that involve fraudulent activity, hateful content, or adult themes. We’ve also taken steps to build user trust by allowing builders to verify their identity. We’ll continue to monitor and learn how people use GPTs and update and strengthen our safety mitigations. If you have concerns with a specific GPT, you can also use our reporting feature on the GPT shared page to notify our team.
GPTs will continue to get more useful and smarter, and you’ll eventually be able to let them take on real tasks in the real world. In the field of AI, these systems are often discussed as “agents”. We think it’s important to move incrementally towards this future, as it will require careful technical and safety work—and time for society to adapt. We have been thinking deeply about the societal implications and will have more analysis to share soon.
Developers can connect GPTs to the real world
In addition to using our built-in capabilities, you can also define custom actions by making one or more APIs available to the GPT. Like plugins, actions allow GPTs to integrate external data or interact with the real-world. Connect GPTs to databases, plug them into emails, or make them your shopping assistant. For example, you could integrate a travel listings database, connect a user’s email inbox, or facilitate e-commerce orders.
The design of actions builds upon insights from our plugins beta, granting developers greater control over the model and how their APIs are called. Migrating from the plugins beta is easy with the ability to use your existing plugin manifest to define actions for your GPT.
ChatGPT is changing fast – here’s everything you need to know
What exactly is it?
What does ChatGPT stand for?
When was it released?
How much does it cost?
How does it work?
What can you use it for?
Does it have an app?
What is ChatGPT 4?
We’ve recently seen an explosion in the number and the ability of generative artificial intelligence (AI) tools available to everyone, and OpenAI’s ChatGPT is leading the way. It hit the 100 million user milestone inside in just two months, and it continues to rapidly grow in terms of its scope and its functionality.
In fact, it feels like ChatGPT is having an iPhone moment, changing the technology landscape in fundamental ways that we’re only just beginning to understand. It promises to significantly change the way we find and parse information, and the way in which content and art is created.
We’ve put together this ChatGPT explainer to answer all the questions you could possibly have about the AI chatbot, from the origins of the tool to the most recent upgrades in its performance. If you’re wondering what ChatGPT is, and what it can do for you, then you’re in exactly the right place.
WHAT IS CHATGPT?
ChatGPT is an AI chatbot that was initially built on a family of Large Language Models (or LLMs), collectively known as GPT-3. OpenAI has now announced that its next-gen GPT-4 models are available. These models can understand and generate human-like answers to text prompts, because they’ve been trained on huge amounts of data.
For example, ChatGPT’s most original GPT-3.5 model was trained on 570GB of text data from the internet, which OpenAI says included books, articles, websites, and even social media. Because it’s been trained on hundreds of billions of words, ChatGPT can create responses that make it seem like, in its own words, “a friendly and intelligent robot”.
ChatGPT can answer questions on almost everything
This ability to produce human-like, and frequently accurate, responses to a vast range of questions is why ChatGPT became the fastest-growing app of all time, reaching 100 million users in only two months. The fact that it can also generate essays, articles, and poetry has only added to its appeal (and controversy, in areas like education).
But early users have also revealed some of ChatGPT’s limitations. OpenAI says that its responses “may be inaccurate, untruthful, and otherwise misleading at times”. OpenAI CEO Sam Altman also admitted in December 2022 that the AI chatbot is “incredibly limited” and that “it’s a mistake to be relying on it for anything important right now”.
Sam Altman: GPT-5 underway and will substantially differ from GPT-4
OpenAI is seeking more funds from Microsoft to build future models both companies can profit from.
Even as it unveils new features of GPT-4, artificial intelligence (AI) company OpenAI is already working on a much more transformative version, GPT-5, that will be launched next, CEO Sam Altman told Financial Times in a recent interview. Altman stopped short of assigning a timeline to this release.
Since its blockbuster product, ChatGPT, which came out in November last year, OpenAI has released improved versions of GPT, the AI model that powered the conversational chatbot. Its most recent iteration, GPT Turbo, offers a faster and cost-effective way to use GPT-4.
Tech companies across the globe have been hopeful of replicating OpenAI’s success by training their own AI models. Sooner or later, the San Francisco-based company needs to unveil a different version of the AI model to set itself apart, and Altman has provided a glimpse of what it might be.
GPT release date prediction – Is OpenAI working on GPT 5?
What we know about OpenAI’s GPT-5.
GPT 5 release date predictions are starting to fly in anticipation of what will be OpenAI’s most advanced large language model yet. Is OpenAI working on GPT 5 yet, and if so, when is GPT 5 coming out? OpenAI CEO Sam Altman is set to change the digital world once again when it does. The release of GPT-5 was initially tapped for December 2023 by ex-board member Elon Musk. With that now disproven, here’s everything we know so far about the next best AI Chatbot and rumored GPT-5 release date.
GPT 5 Release Date Prediction
GPT-4, OpenAI’s current flagship AI model, is now a mature foundation model. With GPT-4V and GPT-4 Turbo released in Q4 2023, the firm is ending the year strong. However, there has been little in the way of official announcements from OpenAI on their next version.
At an MIT event in April, OpenAI CEO Sam Altman shared that they are not currently training GPT-5 at that time. Since then, the chief executive has sought new funding from key investor Microsoft to build a new superintelligence.
OpenAI is building next-generation AI GPT-5 — and CEO claims it could be superintelligent
OpenAI has started building ChatGPT 5 — its next-generation AI model GPT-5. CEO Sam Altman confirmed this in a recent interview, and claimed it could possess superintelligence, but the company would need further investment from its long-time partner Microsoft to make it a reality.
Speaking to the Financial Times, Altman said the partnership with Microsoft is working really well, and that he expects to raise a lot more money over time from the Windows creator and other investors.
Building a major AI model like ChatGPT requires billions of dollars and masses of computer resources, training on billions or trillions of pages of data, and extensive fine-tuning and safety testing.
Going beyond the human
While GPT-4 is an impressive artificial intelligence tool, its capabilities come close to or mirror the human in terms of knowledge and understanding. The next generation of AI models is expected to not only surpass humans in terms of knowledge, but also match humanity’s ability to reason and process complex ideas.
This is also known as artificial general intelligence (AGI), which goes beyond simply parroting a new version of what it is given and provides an ability to express something new and original. It is this type of model that has had governments, regulators and even big tech companies themselves debating how to ensure they don’t go rogue and destroy humanity.
Case Study: Building A GPT App With GPT In 2024
Reflecting on the journey of building a GPT-powered app provides valuable lessons learned and insights into the industry impact of such endeavors. The integration of advanced AI like GPT into applications has the potential to revolutionize how users interact with technology, making it more intuitive, efficient, and personalized.
One of the key lessons learned is the importance of a solid foundation in data collection and model training. The success of a GPT app hinges on the quality and diversity of its training data. Ensuring that data is ethically sourced and free from biases is critical for the development of fair and effective AI systems.
The scalability of GPT technology has demonstrated a significant impact on the industry, encouraging businesses to adopt AI solutions that can grow with their needs. The ability to process natural language at scale enables a wide range of applications, from customer service bots to content creation tools.
Another lesson is the necessity of user-centric design. The best GPT app is not only technologically advanced but also accessible and enjoyable to use. Regular user feedback and testing are invaluable in creating an application that truly meets user needs and expectations.
Challenges encountered during development, such as resource management and integration complexities, highlight the need for robust planning and a skilled, adaptable development team. Overcoming these challenges can lead to a more resilient and high-quality product.
The marketing and launch strategies adopted for GPT apps underscore the importance of clear messaging and engagement with the target audience. The impact of a well-executed launch can set the stage for user adoption and long-term success.
Post-launch, the focus shifts to maintaining and improving the app through regular updates and support. The commitment to continuous improvement and responsiveness to user feedback can strengthen the app’s market position and user loyalty.
Finally, the monetization strategies explored for GPT apps reveal a variety of approaches to generating revenue while providing value to users. A thoughtful monetization model is crucial for the financial sustainability of the app.
The industry impact of GPT apps is far-reaching, with implications for how businesses operate and how consumers access information and services. As the technology continues to evolve, it is likely to create new opportunities and challenges alike.
The journey of building a GPT-powered app is a microcosm of the broader AI revolution taking place across industries. The lessons learned from this case study can serve as a guide for future AI
endeavors, driving innovation and shaping the future of technology.
What enterprise software vendors are doing with generative AI
CIOs are cautiously evaluating generative AI for use in their own applications, while enterprise software vendors showcase the AI at a furious pace.
2023 was a break-out year for generative AI technology, as tools such as ChatGPT graduated from lab curiosity to household name. But CIOs are still cautiously evaluating how to safely deploy generative AI in the enterprise, and what guard-rails to put around it. Sometimes, though, it sneaks in through the back door as a result of ad-hoc individual or departmental initiatives — or even through the front door, bundled by the vendors of enterprise applications already in widespread use.
With major enterprise software vendors adding new generative AI features and support for new large language models (LLM) almost monthly, CIO.com offers this round-up of the latest announcements to help IT leaders keep tabs on their exposure to this new technology.
Making money from GPTs in 2024
As we step into 2024, the realm of Generative Pre-trained Transformers (GPTs) has become a fertile ground for innovative business applications and a beacon for developers seeking to monetize this technology. The rapid evolution of GPTs has transformed them from mere conversation tools to sophisticated systems capable of driving business solutions and creating new revenue streams.
In this dynamic landscape, two critical areas stand out: building a strong reputation in the Open AI Marketplace and customizing GPTs for specific business needs. However, venturing into the world of GPTs requires more than just technical expertise; it demands a strategic approach and a deep understanding of the market.
This guide delves into these facets, offering insights and strategies for those looking to harness the full potential of GPT technology. Whether you are a seasoned developer or new to the field, understanding these key areas will be instrumental in your journey towards creating successful and impactful GPT applications.
How to make money from GPT development
Firstly, keeping abreast of the latest advancements in GPT technology is essential. The field is rapidly evolving, with each iteration of GPT models offering enhanced capabilities. Understanding these advancements not only helps in creating cutting-edge solutions but also in anticipating future trends.
Secondly, identifying the niche market or specific business need that your GPT application will address is crucial. The versatility of GPTs means they can be adapted to a wide range of industries and functions, from customer service and content creation to more specialized applications like legal consulting or healthcare advice.
Thirdly, the ethical implications of GPT technology cannot be overlooked. As developers, it is imperative to consider the impact of your creations on privacy, security, and societal norms. Ensuring that your GPT applications adhere to ethical guidelines and regulations will be a key factor in their success and acceptance.
Finally, developing a keen sense of user experience and interface design can significantly enhance the effectiveness of your GPT applications. In a market where user engagement and satisfaction are paramount, the ease of use and intuitiveness of your application can make a substantial difference.
Other articles we have written that you may find of interest on the subject of designing and making custom GPT applications :
How to make GPTs using ChatGPT in minutes – Beginners Guide
How to add custom GPTs to any website
Combining GPTs and Zapier to create AI automated workflows
Connect GPTs with Zapier to improve your productivity workflow
How to make GPTs – custom ChatGPT AI models – no code
What are OpenAI GPTs and how do they work?
ChatGPT is about to revolutionize the economy. We need to decide what that looks like.
New large language models will transform many jobs. Whether they will lead to widespread prosperity or not is up to us.
Whether it’s based on hallucinatory beliefs or not, an artificial-intelligence gold rush has started over the last several months to mine the anticipated business opportunities from generative AI models like ChatGPT. App developers, venture-backed startups, and some of the world’s largest corporations are all scrambling to make sense of the sensational text-generating bot released by OpenAI last November.
You can practically hear the shrieks from corner offices around the world: “What is our ChatGPT play? How do we make money off this?”
But while companies and executives see a clear chance to cash in, the likely impact of the technology on workers and the economy on the whole is far less obvious. Despite their limitations—chief among of them their propensity for making stuff up—ChatGPT and other recently released generative AI models hold the promise of automating all sorts of tasks that were previously thought to be solely in the realm of human creativity and reasoning, from writing to creating graphics to summarizing and analyzing data. That has left economists unsure how jobs and overall productivity might be affected.
For all the amazing advances in AI and other digital tools over the last decade, their record in improving prosperity and spurring widespread economic growth is discouraging. Although a few investors and entrepreneurs have become very rich, most people haven’t benefited. Some have even been automated out of their jobs.
Productivity growth, which is how countries become richer and more prosperous, has been dismal since around 2005 in the US and in most advanced economies (the UK is a particular basket case). The fact that the economic pie is not growing much has led to stagnant wages for many people.
What productivity growth there has been in that time is largely confined to a few sectors, such as information services, and in the US to a few cities—think San Jose, San Francisco, Seattle, and Boston.
Will ChatGPT make the already troubling income and wealth inequality in the US and many other countries even worse? Or could it help? Could it in fact provide a much-needed boost to productivity?
Ethical ChatGPT: Concerns, Challenges, and Commandments
Abstract—Large language models, e.g. ChatGPT are currently contributingenormously to make artificial intelligence even more popular, especially amongthe general population. However, such chatbot models were developed as tools tosupport natural language communication between humans. Problematically, it isvery much a “statistical correlation machine” (correlation instead of causality) andthere are indeed ethical concerns associated with the use of AI language models such as ChatGPT, such as Bias, Privacy, and Abuse. This paper highlightsspecific ethical concerns on ChatGPT and articulates key challenges whenChatGPT is used in various applications. Practical commandments for differentstakeholders of ChatGPT are also proposed that can serve as checklist guidelinesfor those applying ChatGPT in their applications. These commandment examples are expected to motivate the ethical use of ChatGPT.
Chat Generative Pre-Trained Transformer (alsoknown as ChatGPT), can fluently answerquestions from users and has the ability togenerate human-like text with a seemingly logical connection between different sections. Individuals havereportedly used ChatGPT to formulate university essays, scholarly articles with references , debug computer program code, compose music, write poetry,give restaurant reviews, generate advertising copy andsolve exams , co-author journal articles and manyothers.
ChatGPT models are basically massive neural networks with billions of parameters, which resulted ingains in quality, accuracy, and breadth of generatedcontent. Their behaviors are learned from a largeamount of text data of Internet resources such asweb pages, books, research articles and social chatter,not programmed explicitly. They are trained with twophases: 1) the initial “pre-training” phase learns topredict the next word in a sentence with a large amountof Internet text from a vast array of perspectives;and 2) the second phase “fine-tunes” models withthe use of datasets that human reviewers crafted tonarrow down system behavior . Such combination ofunsupervised pre-training and supervised fine-tuninghelps to generate human-like responses to queries and in particular provide responses to queried topics thatresemble that of a human expert.
The rapid widespread adoption of ChatGPT afterrelease has demonstrated its tremendous powerfulness of potential uses in different areas ranging fromtechnical assistance such as coding, essay writing,business letters, to customer engagement as well asmany others . Despite the powerful capacity ofChatGPT to help people with various writing tasks andexperiments engendering both positive and adverseimpacts, the society has critical concerns on allowingusers to cheat and plagiarize especially in academyand education communities, potentially spreading misinformation, and enabling unethical business practicesas well as other ethical issues.
Weidinger et al. summarises the ethical risklandscape with Large Language Models (LLM), identifying six ethical concerns: 1) Discrimination, Exclusion,and Toxicity, 2) Information Hazards, 3) Misinformation Harms, 4) Malicious Uses, 5) Human-ComputerInteraction Harms, and 6) Automation, Access, andEnvironmental Harms. ChatGPT shares not only thesimilar ethical issues with other AI solutions includingfairness, privacy and security, transparency, accountability, etc,, it may also introduce additionalethical concerns because of its specific characteristics.For example, people have difficulty to distinguish factsand fake with the ChatGPT’s human-like conversations; in education, teachers may have difficulty todifferentiate the authorship between human and AI inhome work; in the creative areas such as designingand creative writing, ChatGPT may introduce changesto not only the authorship, but also the creativity ofhuman in the long time
This paper first highlights specific ethical concernson ChatGPT and articulates key challenges when ChatGPT is used in various applications. We then propose practical commandments for different stakeholders of ChatGPT that can serve as checklist guidelinesfor those applying ChatGPT in their applications.