In the ever-evolving field of artificial intelligence (AI), Red Hat continues to offer solutions adapted to the needs of businesses. With the launch of RHEL AI 1.2, this platform offers powerful tools for the development and deployment of AI models. Let’s discover without delay the major characteristics of this new version.
What’s new in RHEL AI 1.2
Optimization of model development
Version 1.2 of RHEL AI introduces several tools aimed at facilitating the creation and deployment of AI models. With a particular focus on advanced language models, this update allows developers to focus on innovation rather than administrative tasks.
A collaborative approach
At the heart of this new version is a desire to promote collaboration between the different stakeholders. By integrating tools such as InstructLab, developers can now work together effectively on complex projects, combining expertise and creativity.
Key Technical Features
- Reminder of features: RHEL AI 1.2 makes it easier to develop and optimize AI models.
- Supported hardware: Compatibility extends to Lenovo ThinkSystem servers.
- Cloud versatility: Deployment possible on multiple clouds, including Azure and Google Cloud.
- New: Functionality of checkpointing periodically for backup during training.
Summary table of key elements
| 🚀 Characteristic | 🛠️ Description |
| 🙌 Collaboration | Collaborative approach to model development. |
| 💻 Material | Support for Lenovo servers and integration of AMD accelerators. |
| ☁️ Cloud | Support for Azure and GCP in addition to AWS. |
| ⏱️ Checkpointing | Saving models during training. |
Towards increased accessibility for users
The update of RHEL AI aims to make artificial intelligence more accessible, allowing experts from various fields to get involved in development. Joe Fernandes, vice-president of the platform, emphasizes the importance of including domain experts in the process of creating AI models on this platform.
Optimized cost management
Red Hat works tirelessly to make AI model development cost-effective and efficient. RHEL AI 1.2 emphasizes the use of techniques that can reduce the costs associated with training models, while optimizing the necessary resources.
The changes made by RHEL AI 1.2 mark a significant step forward for companies wishing to leverage artificial intelligence in their processes. What do you think? Share your thoughts in the comments below!