In the rapidly evolving landscape of artificial intelligence, enterprises are increasingly grappling with the challenges of deploying AI solutions while ensuring data privacy and security. As organizations turn to the cloud to leverage AI, concerns about data breaches and compliance with privacy regulations often lead them to consider private cloud or on-premises solutions. In response to these needs, Together AI has emerged as a key player, offering innovative solutions that make AI deployment both efficient and cost-effective.
Together AI recently launched its Together Enterprise Platform, designed specifically for organizations keen on deploying AI within controlled environments such as virtual private clouds (VPC) or on-premises infrastructures. This platform aims to simplify the integration of open-source large language models (LLMs) while addressing the critical issues of performance, compliance, and ownership that enterprises face in their AI initiatives.
Vipul Prakash, CEO of Together AI, emphasized the platform’s core advantages in a recent discussion. As enterprises scale their AI workloads, balancing cost efficiency with robust data privacy becomes paramount. Prakash noted that many companies have established privacy frameworks that are already integrated into their existing cloud setups, making the Together Enterprise Platform an appealing alternative. This solution allows organizations to maintain control over their data while still benefiting from advanced AI capabilities.
One of the standout features of the Together Enterprise Platform is its ability to significantly enhance the performance of AI inference workloads. According to Prakash, enterprises can expect performance improvements of two to three times, while also halving their hardware requirements for inference tasks. This not only leads to substantial cost savings but also enables teams to innovate more rapidly by launching additional products and features.
The technological prowess behind these performance gains lies in Together AI’s sophisticated approach to algorithm optimization. The company employs strategic scheduling and utilizes a combination of optimized software and hardware to maximize efficiency. Techniques such as speculative decoding allow the platform to use smaller models to predict outputs from larger, more computationally intensive models, ultimately reducing the overall workload.
A noteworthy aspect of the Together Enterprise Platform is its flexible model orchestration capabilities. In today’s AI landscape, organizations often utilize a mix of open-source, custom, and vendor-provided models. Together AI recognizes this diversity and allows for seamless orchestration of these models within a single application or workflow. This adaptability is critical, as it enables companies to scale model usage according to the specific demands of their operations.
For instance, companies can integrate technologies like LangChain to facilitate model synergy or utilize model routers to direct queries to the most suitable model for a given task. Together AI, however, introduces a unique approach called the Mixture of Agents. This methodology involves using multiple ‘weaker’ models as proposers that generate responses to prompts, which are then aggregated by a more powerful model to create a refined answer. This innovative strategy not only enhances the quality of responses but also fosters ongoing improvement in model performance.
As enterprises explore the potential of AI, they are also keen on understanding the financial implications of adopting private cloud solutions. A recent study by Gartner revealed that organizations can achieve significant cost reductions by optimizing their AI workloads and utilizing advanced platforms like Together AI. This aligns with the feedback from industry leaders who stress the importance of balancing technological advancement with financial prudence.
Social media discussions further highlight the growing interest in private cloud solutions for AI. For example, a recent tweet from AI expert Andrew Ng stated, “As AI continues to evolve, enterprises must prioritize data privacy and cost efficiency. Together AI’s approach could be a game-changer.” This sentiment resonates with the broader industry consensus that emphasizes the need for secure and adaptable AI deployment options.
In summary, Together AI’s offering stands out in a crowded marketplace, addressing the dual challenges of performance and data security. As organizations increasingly recognize the importance of maintaining control over their data while harnessing the power of AI, solutions like the Together Enterprise Platform pave the way for secure, efficient, and innovative AI deployments. The ongoing evolution of this platform signals a promising future for enterprises committed to leveraging AI responsibly and effectively.
