Top 6 Generative AI Services & Vendors in 2023
AI has been an invaluable tool in the digital realm for over a decade now. It has catapulted businesses into the future with cutting-edge solutions and innovative approaches. Among the various types of AI, one has stood out in its revolutionary capabilities—Generative AI.
Generative AI works by using deep learning techniques to create new data instances similar to the input data, giving human creativity to AI. The technology has paved the way for diverse applications in various industries and areas (Figure 1). Such as:
But to successfully leverage this technology, businesses often seek the support of dedicated services. Here, we explore 6 types of generative AI services that are instrumental in enhancing businesses’ use of generative AI technology to gain a competitive advantage.
Figure 1. Gen AI adoption in the U.S. by industry in 2022
1. Generative AI foundation model services
AI foundation models are the backbone of any generative AI system. These are complex models trained on extensive datasets and can generate outputs in a range of tasks without task-specific training data.
Two notable services in this area include:
OpenAI
Renowned for its GPT-3 and GPT-4 large language models, and Dall E image generation model, OpenAI has delivered unprecedented advances in generative AI. GPT-n models are capable of creating human-like text, making it a top choice for businesses seeking foundation models for their AI applications.
Google’s BERT model has also revolutionized the way we process languages in AI, making significant strides in search optimization, sentence prediction, and other text-processing tasks. This robust and versatile model is a stalwart for any company seeking to utilize generative AI in language-related tasks.
2. Generative AI training data collection services
Generative AI models require large amounts of data to be trained. Software developers can work with data collection services to fulfill their data needs without facing the hassle of collecting data. These services focus on data collection, preprocessing, annotation, and other services involved in preparing a training dataset for generative AI models.
Sponsored
Clickworker
Clickworker offers human-generated datasets for training generative AI models through a crowdsourcing platform. Its global team of over 4.5 million data collectors helps 4 out of 5 tech giants in the U.S. with their data needs. They can offer:
- Image datasets to train image generation models like Dall E
- Text or spoken audio datasets to train natural language processing or a Large language model
- Video datasets for video generation tools
To learn more about data collection, download our free whitepaper:
Get Data Collection Whitepaper
3. Generative AI training services
Training a generative AI model is a challenging process that requires specialized skills because it involves:
- Understanding complex algorithms
- Optimizing neural network architectures
- Handling large datasets
- Fine-tuning models to generate high-quality outputs while avoiding pitfalls such as overfitting or mode collapse.
Third-party service providers can help streamline this process.
Such services include:
H2O.ai:
H2O.ai offers an automatic machine learning platform that helps build AI models to improve business operations, including generative AI, without necessarily having an extensive background in AI.
DataRobot
DataRobot provides an enterprise AI platform that enables users to prepare data, build, train, and deploy machine learning models, including generative models.
4. Generative AI strategy services
A sound strategy is essential for any business planning to integrate generative AI into its business processes. This can be challenging because it requires a deep understanding of both AI technologies and the specific business context, including:
- Operational needs
- The skills of the existing workforce
- Ethical considerations
- The potential impacts and risks of AI deployment.
Strategy services help develop this roadmap, and top players include:
Accenture
Accenture’s AI strategy services help businesses identify and implement AI use cases, including generative AI applications.
Boston Consulting Group (BCG)
BCG’s Gamma team combines strategic thinking with powerful AI tools to help companies develop a winning generative AI strategy.
5. Generative AI hardware solutions
Generative AI systems often require high-performance computing capabilities to efficiently process and learn from massive amounts of data, necessitating specialized hardware such as GPUs or TPUs. Working with a third-party service provider can help you achieve such computational capabilities. These services provide specialized hardware to help train and run generative AI models more efficiently:
NVIDIA
NVIDIA is a leading name in AI hardware solutions, providing powerful GPUs that are crucial for training generative AI models due to their parallel processing capabilities.
Google’s Tensor Processing Units (TPUs)
Designed specifically for neural network machine learning, Google’s TPUs offer high-performance capabilities for training and deploying generative AI models.
6. Generative AI software platforms
These platforms provide the software infrastructure and tools to develop, deploy, and manage generative AI models:
Microsoft Azure
Azure’s Machine Learning service provides a suite of tools to build, train, and deploy machine learning models, including support for generative AI.
AWS SageMaker
Amazon’s SageMaker is a fully managed service that provides developers and data scientists with the ability to build, train, and deploy machine learning models, including generative AI models.
Further reading
If you need help finding a vendor or have any questions, feel free to contact us:
AI has been an invaluable tool in the digital realm for over a decade now. It has catapulted businesses into the future with cutting-edge solutions and innovative approaches. Among the various types of AI, one has stood out in its revolutionary capabilities—Generative AI.
Generative AI works by using deep learning techniques to create new data instances similar to the input data, giving human creativity to AI. The technology has paved the way for diverse applications in various industries and areas (Figure 1). Such as:
But to successfully leverage this technology, businesses often seek the support of dedicated services. Here, we explore 6 types of generative AI services that are instrumental in enhancing businesses’ use of generative AI technology to gain a competitive advantage.
Figure 1. Gen AI adoption in the U.S. by industry in 2022
1. Generative AI foundation model services
AI foundation models are the backbone of any generative AI system. These are complex models trained on extensive datasets and can generate outputs in a range of tasks without task-specific training data.
Two notable services in this area include:
OpenAI
Renowned for its GPT-3 and GPT-4 large language models, and Dall E image generation model, OpenAI has delivered unprecedented advances in generative AI. GPT-n models are capable of creating human-like text, making it a top choice for businesses seeking foundation models for their AI applications.
Google’s BERT model has also revolutionized the way we process languages in AI, making significant strides in search optimization, sentence prediction, and other text-processing tasks. This robust and versatile model is a stalwart for any company seeking to utilize generative AI in language-related tasks.
2. Generative AI training data collection services
Generative AI models require large amounts of data to be trained. Software developers can work with data collection services to fulfill their data needs without facing the hassle of collecting data. These services focus on data collection, preprocessing, annotation, and other services involved in preparing a training dataset for generative AI models.
Sponsored
Clickworker
Clickworker offers human-generated datasets for training generative AI models through a crowdsourcing platform. Its global team of over 4.5 million data collectors helps 4 out of 5 tech giants in the U.S. with their data needs. They can offer:
- Image datasets to train image generation models like Dall E
- Text or spoken audio datasets to train natural language processing or a Large language model
- Video datasets for video generation tools
To learn more about data collection, download our free whitepaper:
Get Data Collection Whitepaper
3. Generative AI training services
Training a generative AI model is a challenging process that requires specialized skills because it involves:
- Understanding complex algorithms
- Optimizing neural network architectures
- Handling large datasets
- Fine-tuning models to generate high-quality outputs while avoiding pitfalls such as overfitting or mode collapse.
Third-party service providers can help streamline this process.
Such services include:
H2O.ai:
H2O.ai offers an automatic machine learning platform that helps build AI models to improve business operations, including generative AI, without necessarily having an extensive background in AI.
DataRobot
DataRobot provides an enterprise AI platform that enables users to prepare data, build, train, and deploy machine learning models, including generative models.
4. Generative AI strategy services
A sound strategy is essential for any business planning to integrate generative AI into its business processes. This can be challenging because it requires a deep understanding of both AI technologies and the specific business context, including:
- Operational needs
- The skills of the existing workforce
- Ethical considerations
- The potential impacts and risks of AI deployment.
Strategy services help develop this roadmap, and top players include:
Accenture
Accenture’s AI strategy services help businesses identify and implement AI use cases, including generative AI applications.
Boston Consulting Group (BCG)
BCG’s Gamma team combines strategic thinking with powerful AI tools to help companies develop a winning generative AI strategy.
5. Generative AI hardware solutions
Generative AI systems often require high-performance computing capabilities to efficiently process and learn from massive amounts of data, necessitating specialized hardware such as GPUs or TPUs. Working with a third-party service provider can help you achieve such computational capabilities. These services provide specialized hardware to help train and run generative AI models more efficiently:
NVIDIA
NVIDIA is a leading name in AI hardware solutions, providing powerful GPUs that are crucial for training generative AI models due to their parallel processing capabilities.
Google’s Tensor Processing Units (TPUs)
Designed specifically for neural network machine learning, Google’s TPUs offer high-performance capabilities for training and deploying generative AI models.
6. Generative AI software platforms
These platforms provide the software infrastructure and tools to develop, deploy, and manage generative AI models:
Microsoft Azure
Azure’s Machine Learning service provides a suite of tools to build, train, and deploy machine learning models, including support for generative AI.
AWS SageMaker
Amazon’s SageMaker is a fully managed service that provides developers and data scientists with the ability to build, train, and deploy machine learning models, including generative AI models.
Further reading
If you need help finding a vendor or have any questions, feel free to contact us:
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