SPONSORED FEATURE: Artificial Intelligence (AI) has been making waves in the business and technology sectors, especially with the rise of generative AI like ChatGPT. However, companies face significant challenges when it comes to adopting and expanding their use of AI and generative AI. These challenges include technological hurdles, training requirements, and procedural obstacles. Despite these challenges, the adoption of AI continues to grow worldwide, as revealed by the IBM Global AI Adoption Index 2022 report. According to the report, the global AI adoption rate has reached 35 percent, a four-point increase from the previous year. Additional findings show that 42 percent of respondents are exploring ways to implement AI into their operations. Assaf Katan, chief business officer at Deci, an Israel-based AI developer, describes the AI landscape as a rapidly evolving domain with both short-term and long-term challenges. In the short term, businesses must decide whether to build in-house AI capabilities, use open-source models and modify them, or work with APIs like Open AI for easier implementation but limited customization and control. Looking to the long term, companies must also consider the scalability of AI solutions and the associated costs. Katan explains that companies aiming to build generative AI services need to evaluate how scaling will impact the performance and cost of their models. Since generative models can be enormous, requiring significant computational power, organizations must find cost-effective ways to handle the growing demands. This is where the combination of generative AI and powerful server hardware, like those offered by Lenovo ThinkSystem, opens avenues for companies to design, build, and deliver AI applications and models efficiently. The IBM research further highlights the numerous ways AI benefits businesses. These advantages include addressing labor shortages by automating repetitive tasks, saving time and costs through automating IT and network processes, improving operational efficiency, enhancing IT and network performance, and ultimately, providing a superior customer experience. Katan emphasizes that the key business benefits of AI primarily revolve around efficiency. He offers examples of how AI can revolutionize customer care and support, such as using generative AI to handle a majority of customer calls, leaving complex queries for human agents.

Another example involves using AI to generate product descriptions, resulting in significant time savings for companies managing large product inventories. To facilitate the development and optimization of AI models, Deci offers the Deci deep learning platform powered by Automated Neural Architecture Construction (AutoNAC) technology. This platform consists of two main components: the neural network and the Infery inference tool. The neural network component assists users in constructing efficient neural network architectures tailored to specific use cases, hardware requirements, and key performance indicators (KPIs). AutoNAC leverages a multi-objective search within a vast search space to identify optimal architectures that balance accuracy, low latency, and high throughput. This enables users to generate AI models more quickly and cost-effectively. The Infery tool, on the other hand, optimizes the runtime performance of neural networks for specific hardware, ensuring efficient execution. This approach is particularly important for generative AI models that have unique characteristics compared to traditional static models used in tasks like object detection. Deci's partnership with Lenovo aims to simplify the AI development process by configuring the Deci AI platform and models to run efficiently on Lenovo servers. Through the Lenovo AI Innovators Program, Deci gains access to Lenovo's AI expertise and pre-configured hardware. Lenovo's global reach and support capabilities complement Deci's AI technology, creating a promising collaboration that benefits customers with streamlined AI solutions. The Deci and Lenovo partnership focuses on addressing the challenges of scaling generative AI, which often incurs substantial costs due to the computational requirements of larger models. By reducing the compute consumption, Deci and Lenovo help businesses minimize hardware expenses while maintaining optimal AI performance. This partnership began in early 2023, and Deci plans to expand their support matrix for a wider range of use cases and continue refining their technology for a stronger offering. Sponsored by Lenovo.