Discover how Together AI Models and Dell Technologies are redefining enterprise AI acceleration with cutting-edge cloud solutions.
Together AI and Dell Technologies are collaborating to expand AI’s cloud platform. An end-to-end high-performance system with cutting-edge computing and networking will be integrated through this partnership to provide scalability and efficiency to businesses, startups, and researchers creating the artificial intelligence of the future.
The Dell AI Factory with NVIDIA, which provides scalable, liquid-cooled units tailored for intricate AI and HPC activities, is utilized in this partnership. The core of the fully integrated Dell IR7000 racks is NVIDIA Blackwell accelerated computing, and Dell Professional Services supports every stage of the setup to guarantee a smooth and quick delivery.
“Dell teams collaborated closely with Together AI and NVIDIA to swiftly develop and deliver AI systems that will offer the capabilities required to propel AI innovation,” stated Arthur Lewis, president of Dell Technologies’ Infrastructure Solutions Group. “Together AI sets the standard for high-end, scalable, and effective AI with its cloud platform, which is supported by Dell infrastructure.”
“Our dedication to accelerating scalable, AI-driven advancements globally is demonstrated by the work we’re doing with Dell Technologies and NVIDIA,” said Vipul Ved Prakash, CEO of Together AI. “The performance and dependability of Dell infrastructure with NVIDIA technology, along with cloud platform, will give customers the speed and flexibility they need for the upcoming era of superintelligence and the new wave of open source reasoning models.”
High Performance AI Infrastructure
To create an AI cluster that can handle complicated AI and HPC operations, Dell and Together AI’s experts collaborated closely. NVIDIA GB200 NVL72-capable Dell PowerEdge XE9712 servers and PowerEdge XE9680 servers with NVIDIA HGX B200 platforms are part of the fully integrated Dell IR7000 racks.
Additionally, the cluster makes use of NVIDIA NVLink and NVIDIA Quantum-2 InfiniBand to facilitate fast, low-latency connection between GPUs, guaranteeing effective data transmission for workloads involving extensive AI training and inference. Bottlenecks are reduced, distributed model execution is accelerated, and smooth scalability across several GPU nodes is made possible by this architecture.
Fast Training and Inference Performance
The Together Inference & Fine-Tuning Platform and Together GPU Clusters are supported by Together AI’s infrastructure, which is accelerated by the Dell AI Factory with NVIDIA and provides quick training and inference performance. By utilizing the high-bandwidth memory of the NVIDIA Blackwell accelerated platform, NVLink for multi-GPU efficiency, and mixed-precision Tensor Cores, which are essential for optimizing Mixture of Experts architectures frequently utilized by reasoning models, AI assists businesses in implementing sophisticated reasoning models. FlashAttention-3, Speculative Decoding, and Mixture of Agents are just a few of Together AI’s research-backed optimizations that help businesses speed up the time to market for AI products while preserving high operational efficiency and dependability.
Together AI Models
Together AI gives developers and academics access to a wide variety of open-source AI models, facilitating the study of advanced machine learning. These models encompass NLP, computer vision, and other domains.
Support for Mistral, LLaMA, and GPT-like LLMs is one of its characteristics. These models excel at text generation, summarization, and code completion. In computer vision, Together AI provides segmentation and image recognition models that aid developers in creating applications for medical imaging, facial identification, and object detection.
AI as a whole also prioritizes personalization and optimization. Models can be customized by users to fit their own datasets, improving performance for specific use cases. With the use of the platform’s distributed training capability, large dataset processing times can be decreased by scaling model training across several nodes.
The real-time inference that Together AI emphasizes also guarantees that models can produce predictions instantaneously, which makes them perfect for applications like fraud detection, recommendation systems, and chatbots.
Through the provision of these varied models and strong infrastructure, Together AI enables innovators to push the limits of artificial intelligence. This platform combines cooperation with state-of-the-art technology to produce AI solutions that are quicker and more intelligent.
Together AI Features
A state-of-the-art platform, Together AI aims to improve accessibility and collaboration in artificial intelligence. In order to create, train, and implement AI models more effectively, it is intended to unite researchers, developers, and businesses. Here are some salient characteristics that distinguish Together AI:
Open-Source AI Models
With its support for numerous open-source models, Together AI provides users with strong tools without requiring proprietary licensing. AI gives you the freedom to experiment and create whether you’re working with generative AI, computer vision, or natural language processing (NLP).
Distributed Training
Distributed training is one of the platform’s best advantages. Large AI models need a lot of processing power, but Together AI lets users employ dispersed clusters to train them more quickly. As a result, managing large datasets is easier and training time is decreased overall.
Collaborative Environment
By enabling groups to work on projects concurrently, AI promotes teamwork. AI development becomes more collaborative and inclusive when teams share code, datasets, and model checkpoints. The software also integrates with Jupyter Notebooks and GitHub.
Advanced Experiment Tracking
In the development of AI, monitoring several experiments is essential. AI provides sophisticated experiment tracking capabilities that record metrics, settings, and results. Comparing various models and improving performance are made simpler as a result.
Model Customization
Together AI makes it simple to adapt pre-trained models to particular application scenarios. Teams without a lot of machine learning experience can more easily refine models using bespoke datasets because it takes less code.
Real-Time Inference
With the platform’s real-time inference capabilities, users may deploy models in production and receive predictions instantly. Real-time inference produces quick outcomes whether it is used for fraud detection, content personalization, or customer care automation.
Infrastructure Expansion and Optimization:
- Significant infrastructure expansion is a key component of Together AI’s future. This involves distributing well-optimized clusters of cutting-edge GPUs, like NVIDIA Blackwell GPUs, among data centers that are positioned strategically.
- To guarantee that users can access the processing power required for demanding AI workloads, they are making significant investments to increase the effectiveness and scalability of their AI Acceleration Cloud.
- In order to speed up and reduce the cost of running AI models, they are also concentrating on optimizing their inference engines.
