#USA #AI Technology #New Orleans #NOLA AI #Atomic Speed

NOLA AI Unveils Atomic Speed

At an event held in New Orleans on June 5, 2025, NOLA AI revealed a game-changing optimization technology named Atomic Speed. This innovative system aims to significantly reduce both the training time and costs associated with running AI models. The announcement was made by Scott Kauffman, the Chairman of NOLA AI, who expressed the company’s commitment to revolutionizing AI methodologies.

What is Atomic Speed?

Atomic Speed utilizes cutting-edge algorithmic processes to optimize AI model training without relying heavily on extensive data centers or expensive GPU farms. As companies have historically relied on a hardware-centric approach, NOLA AI’s solution shifts the focus to algorithmic innovation, promising a new era in artificial intelligence development.

According to NOLA AI's released data, Atomic Speed could reduce training epochs by two to four times and cut compute times per step by over 50%, all while maintaining the same model quality that industry leaders expect. This technology stands to drastically alter the economics of AI training, allowing large-scale models—like GPT-4 and Gemini Ultra—to save substantial amounts of money, potentially over $100 million apiece, when using Atomic Speed.

Economic Impact on Enterprises

The implications for businesses looking to utilize AI models are immediate. Previously extended periods required for training can now be expedited to just days, enhancing the efficiency of AI deployments. 'These findings emphasize our objective to disrupt the existing AI paradigm,' Kauffman stated. 'Atomic Speed empowers businesses of all sizes to innovate cost-effectively.' This mindset aligns well with many organizations seeking to enhance their AI capabilities without incurring massive expenses.

Private Beta Access

To facilitate the adoption of this technology, NOLA AI announced that applications for a private beta of Atomic Speed are now open. Selected participants will benefit from direct access to the framework that supports this optimization. Moreover, they will receive hands-on assistance from NOLA AI's development team, which will allow these pioneering organizations to influence future product roadmaps.

Enterprises, start-ups, and academic research teams interested in participating in the private beta can apply through the NOLA AI website. The selection process for participants will take into account the computation needs, specific use cases, and willingness to provide feedback throughout the beta phase.

Conclusion

NOLA AI represents a shift in the landscape of AI development, championing the efficiency and cost-effectiveness of its new Atomic Speed technology. With a dedicated leadership team led by Chief Scientist Correy Kowall—a renowned expert in neural networks—NOLA AI is poised to deliver enterprise-level AI solutions that redefine existing norms. For more insights into this innovative technology and information about the private beta, visit www.nola-ai.com.