Explainer: What is Generative AI, the technology behind OpenAI’s ChatGPT?

Through collaboration and experimentation over time, we’ll uncover even more benefits from generative AI. 9 job types that might be affectedThese nine job types — including administrative, customer service and teaching — might be replaced, augmented genrative ai or improved by the latest artificial intelligence wave. ChatGPT’s ability to generate humanlike text has sparked widespread curiosity about generative AI’s potential. The convincing realism of generative AI content introduces a new set of AI risks.

If the generative model is large, fine-tuning it on enterprise data can become prohibitively expensive. They allow you to adapt the model without having to adjust its billions to trillions of parameters. They work by distilling the user’s data and target task into a small number of parameters that are inserted into a frozen large model. Autoencoders work by encoding unlabeled data into a compressed representation, and then decoding the data back into its original form.

Generative AI’s popularity is accompanied by concerns of ethics, misuse, and quality control. Because it is trained on existing sources, including those that are unverified on the internet, generative AI can provide misleading, inaccurate, and fake information. Even when a source is provided, that source might have incorrect information or may be falsely linked. It’s also worth noting that generative AI capabilities will increasingly be built into the software products you likely use everyday, like Bing, Office 365, Microsoft 365 Copilot and Google Workspace. This is effectively a “free” tier, though vendors will ultimately pass on costs to customers as part of bundled incremental price increases to their products. But generative AI only hit mainstream headlines in late 2022 with the launch of ChatGPT, a chatbot capable of very human-seeming interactions.

Software development

You may have heard of recent popular examples of generative AI such as ChatGPT, DALL-E or StableDiffusion. By contrast, ChatGPT builds a transformer-based language model from a generative pre-trained transformer (GPT) to process sequential data, such as language, and then calculate the most probable words that will follow in a sequenced response. One neural network artificially manufactures fake outputs disguised as real data, while the other works to distinguish between the artificial data and real data — all the while using deep learning methods to improve their techniques. Generative AI is a type of artificial intelligence that can produce content such as audio, text, code, video, images, and other data.

• While some major US companies are torn on whether to embrace generative AI, others are introducing AI into their businesses with caution.
• Today’s generative AI can create content that seems to be written by humans and pass the Turing test established by notable mathematician and cryptographer Alan Turing.
• And businesses are developing applications to address use cases across all these areas.
• The productivity gains aren’t limited to just certain industries that are more content-intensive, such as the media and entertainment sector.
• Generative AI also can disrupt the software development industry by automating manual coding work.

Widespread AI applications have already changed the way that users interact with the world; for example, voice-activated AI now comes pre-installed on many phones, speakers, and other everyday technology. To learn more about what artificial intelligence is and isn’t, check out our comprehensive AI cheat sheet. There are plenty of examples of chatbots, for example, providing incorrect information or simply making things up to fill the gaps. While the results from generative AI can be intriguing and entertaining, it would be unwise, certainly in the short term, to rely on the information or content they create. Our goal is to deliver the most accurate information and the most knowledgeable advice possible in order to help you make smarter buying decisions on tech gear and a wide array of products and services. Our editors thoroughly review and fact-check every article to ensure that our content meets the highest standards.

What is Generative AI?

“Plain” autoencoders were used for a variety of purposes, including reconstructing corrupted or blurry images. Variational autoencoders added the critical ability to not just reconstruct data, but to output variations on the original data. Reuters, the news and media division of Thomson Reuters, is the world’s largest multimedia news provider, reaching billions of people worldwide every day. Reuters provides business, financial, national and international news to professionals via desktop terminals, the world’s media organizations, industry events and directly to consumers. Examples of generative art that does not involve AI include serialism in music and the cut-up technique in literature.

Machine learning refers to the subsection of AI that teaches a system to make a prediction based on data it’s trained on. An example of this kind of prediction is when DALL-E is able to create an image based on the prompt you enter by discerning what the prompt actually means. Years from now, it’s possible that Generative AI will produce better final drafts than professional writers and generate better art and design elements than professional human artists and graphic designers. More advanced Generative AI may also be able to entire computer applications, video games, movies and other complex elements with little or no human supervision.

Yakov Livshits

It says that the technology has value across a wide swath of industries, including finance, healthcare, automotive and transportation, information technology, telecommunications, and media and entertainment. Generative AI can transform tasks as wide ranging as marketing, image classification and quality control. At this point, artificial intelligence – particularly generative AI – is fundamentally reshaping the way people and businesses act, interact and process information. A common example of generative AI is ChatGPT, which is a chatbot that responds to statements, requests and questions by tapping into its large pool of training data that goes up to 2021.

Several companies, including Amper Music, Aiva, Amadeus Code, Google Magenta and MuseNet are capable of generating original music with multiple realistic-sounding instruments. A user can request a genre, artist genrative ai or style—say jazz, Mozart, the Rolling Stones or upbeat—and listen to the resulting AI generated composition. According to OpenAI, researchers fed more than 300 billion words into the actual ChatGPT model.

It is crucial to red-team chatbots and get ahead of risks to ensure these nascent technologies evolve ethically instead of going rogue. “Professional red teams are trained to find weaknesses and exploit loopholes in computer systems. But with AI chatbots and image generators, the potential harms to society go beyond security flaws,” said Chowdhury. Our data science team is excited about bringing the latest in machine learning to our customers to help them with real life business problems.

It has even been suggested that the misuse or mismanagement of generative AI could put national security at risk. VAEs leverage two networks to interpret and generate data — in this case, it’s an encoder and a decoder. The decoder then takes this compressed information and reconstructs it into something new that resembles the original data, but isn’t entirely the same. Dall-E, ChatGPT, and Bard are prominent generative AI interfaces that have sparked a significant interest.

When you’re asking a model to train using nearly the entire internet, it’s going to cost you. Building a generative AI model has for the most part been a major undertaking, to the extent that only a few well-resourced tech heavyweights have made an attempt. OpenAI, the company behind ChatGPT, former GPT models, and DALL-E, has billions in funding from boldface-name donors. DeepMind is a subsidiary of Alphabet, the parent company of Google, and Meta has released its Make-A-Video product based on generative AI.

Unlike other technologies that are solely cost- or revenue-focused, GenAI helps in both areas. Salesforce’s research found that 82% of business leaders said GenAI will lower overall business costs, and 80% indicated it will increase revenue. McKinsey estimates that GenAI could add $2.6 to $4.4 trillion annually to the global economy. Recognizing the unique capabilities of these different forms genrative ai of AI allows us to harness their full potential as we continue on this exciting journey. McKinsey has found that gen AI could substantially increase labor productivity across the economy. To reap the benefits of this productivity boost, however, workers whose jobs are affected will need to shift to other work activities that allow them to at least match their 2022 productivity levels.

With the improvements of AI generative technologies it’s become a serious problem. Static 2D images are the easiest to fake, but today we face the new threat of fake videos. Another website has  more than two million photos, royalty free, of people who never existed but look like real people. You can select different parameters to get images that fit the specific criteria, and all this is generated by AI; none of these people even exist. These are very useful examples, so I’ll call them passive AI – analyzing the existing data and generating output and helping to make decisions or even making them automatically.