When we think of prominent names in artificial intelligence, the company that springs to mind for many is OpenAI, the creators of the generative AI chatbot ChatGPT.
Of course the origins of generative AI can be found long before Sam Altman and Elon Musk founded OpenAI in 2015. From Alan Turing publishing the Turing Test in the 1950s, and Joseph Weizenbaum creating the first chatbot in the 1960s, through to Ian Goodfellow developing the first generative adversarial network (GAN) in 2014, many people have contributed to generative AI’s story.
But the release of ChatGPT in 2022 was certainly a turning point. It was a development that made generative AI far more accessible and acted as a catalyst for the adoption of artificial intelligence by businesses across the globe.
Read on to find out more about what OpenAI is currently doing in the generative AI space, as well as how other players in computer science and artificial intelligence are developing their own generative AI offerings.
In its Top 10 Emerging Technologies of 2023 report, the World Economic Forum describes generative AI as:
“A powerful type of AI that can create new and original content by learning patterns in data, using complex algorithms and methods of learning inspired by the human brain.”
Much of the focus is currently on generative AI chatbots that produce text, computer programming, images and sound. But the WEF report suggests that, in future, we're likely to see far wider uses for generative AI, including drug design, architecture and engineering.
The introduction of Generative Pre-trained Transformers (GPTs) by OpenAI in 2018 was a game changer for generative AI. Modeled on the human brain, GPTs are large language models (LLMs) that use deep learning and are trained on vast amounts of human-generated text to perform tasks like formulating and answering questions.
The ChatGPT chatbot is powered by OpenAI’s GPT, and when it launched in 2022 it initially used GPT-3. Now the free version runs on GPT-3.5, while the paid version runs on GPT-4, and OpenAI is in the process of developing GPT-5. ChatGPT isn’t the only AI system to use OpenAI’s GPTs however, with developers able to use them to power other applications, such as open source AI agent AutoGPT for example.
ChatGPT is already being used by businesses in a variety of ways:
At CES 2024, auto brand Volkswagen announced it is integrating the chatbot into its vehicles via the IDA voice assistant.
In another case study, software firm Freshworks is using ChatGPT to write code, with reports suggesting tasks that usually take around nine weeks are completed in just a few days.
While the OpenAI brand is currently synonymous with generative AI, there are many other businesses making great strides with new technologies. Some are well known technology leaders and household names, while others are less recognized outside of the data science and artificial intelligence industries. Here are just a few of the many generative AI model providers that are investing in AI development and making technologies available for developers to create new AI tools.
Amazon: Amazon Bedrock is a service for building generative AI applications on Amazon’s cloud computing platform, Amazon Web Services (AWS). Its aim is to provide easy access to a variety of foundational models (FMs) from other providers, so AWS customers can choose the right model for their needs. Amazon has also developed its own Titan foundational models.
Cohere: An enterprise AI solution, Cohere provides LLMs designed for real-world business applications. Its Retrieval Augmented Generation (RAG) toolkit enables these LLMs to answer questions and solve tasks using enterprise data. Products based on Cohere’s LLM include semantic search, embeddings, text generation, summarization, and classification. It has a multilingual model that supports over 100 languages.
Google: Vertex AI is Google Cloud’s machine learning platform that enables models to be designed, trained, served and monitored. Users can access Google's LLMs which include Palm (a multimodal model,) and Bard (a pure language model) and can test, tune, and deploy them in their own AI-powered applications. Google DeepMind (formerly Google Brain) is another Google initiative that functions as an AI research laboratory.
Microsoft: A long-term partner of OpenAI, Microsoft is embedding generative AI technology into many of its products. Its previous AI tool Bing Chat has been absorbed into the generative AI-driven Copilot, and this has been integrated into applications like Word, PowerPoint, Excel, OneNote and Outlook.
Hugging Face: A data science platform that helps users build, deploy and train machine learning models, Hugging Face provides a large ecosystem of open source tools for working with generative AI. It acts as a hub for artificial intelligence enthusiasts, who can create their own models or use one of the thousands of models in the Hugging Face library. The AutoTrain tool allows users to automatically train, evaluate and deploy models.
IBM: The watsonx platform from IBM is designed to help businesses deploy and embed artificial intelligence. It includes a studio for new foundation models, generative AI and machine learning, a data store built on an open data lakehouse architecture, and a toolkit to accelerate AI workflows. It also has a set of AI assistants.
Nvidia: Describing itself as “the world’s most advanced platform for generative AI”, Nvidia combines accelerated computing, AI software, pre-trained models and AI foundries to enable users to build, customize, and deploy generative AI models for a variety of applications. Nvidia’s own models include StyleGAN, GauGAN and eDiff-I.
Beyond the companies above, there are hundreds of specialists in the generative AI space creating a huge variety of solutions using new open-source models and capabilities. But there’s one thing that all these solutions have in common: they need to be enabled by the right data and intelligence. And that’s where Celonis comes into the equation.
At Celonis we focus on generating the Process Intelligence businesses need to make AI solutions work for them. By providing a structured process data foundation and the necessary understanding of business processes, Process Intelligence ensures AI understands the language of any business and can be effectively deployed across an enterprise.
Find out more about how enterprises in the technology, retail, consumer goods and logistics sectors are benefiting from a combination of generative AI and Process Intelligence with these insights from a recent panel discussion at Celophere 2023.