Mastering the Four Challenges of Generative AI: Cost, Safety, Alignment, and Latency

Manoj Saxena, CEO and founder of Trustwise

The new generative AI wave has every company racing to implement large language models (LLMs) like GPT-4, Gemini, Llama and Mistral in their processes and products. However, these models are costly, energy-inefficient, and challenging to control, with many instances of companies facing legal issues due to LLM usage.

Building and operating these systems requires navigating a complex landscape marked by four critical dimensions: cost, safety, alignment, and latency. Innovative companies can employ strategies to deploy LLMs at scale by balancing trade-offs among these four critical dimensions. However, reducing costs can compromise safety and alignment, while improving safety and alignment typically increases costs and latency. Lowering latency often leads to higher costs. Finding the right balance is an optimization problem.

Trustwise Optimize:ai API addresses these challenges head-on and helps companies innovate confidently and efficiently with generative AI without compromising on performance or compliance.

First, let’s consider cost. Each token generated by LLMs incurs a cost, and excessive token generation can result from overly verbose responses, poor context awareness, improper document chunking, and non-optimal pipeline configurations. Trustwise Optimize:ai addresses this by optimizing token consumption through intelligent model selection, evaluations caching, and dynamic scaling. Our solution uses fine-tuned cheaper models, safety and alignment evaluations pre-caching, and adjusting RAG and AI pipeline parameters to reduce tokens, substantially cutting LLM usage costs without sacrificing relevance or performance.

The second dimension, safety, is paramount in AI applications. Trustwise Optimize:ai includes a set of research-based and client-validated metrics designed to detect and fix hallucinations and data leakage, ensuring that AI outputs are accurate and secure. Our algorithmic stress-testing and red teaming engine continually evaluates and improves the safety of AI models, providing a robust defense against potential vulnerabilities and prevention of sensitive data leakage.

Alignment with company policies and regulatory requirements is another critical challenge. Trustwise Optimize:ai includes sophisticated compliance cross-walks that integrate seamlessly into the AI pipeline. This ensures that AI outputs consistently adhere to corporate AI use policies and regulatory standards, such as the NIST AI RMF, EU AI Act, and GDPR, reducing the risk of non-compliance and enhancing trust in AI applications.

Finally, latency can significantly impact the user experience and the feasibility of real-time applications. Trustwise Optimize:ai employs advanced techniques like parallelizing requests and chunking data to minimize latency. By using a hyper-parallelized architecture, we can process multiple LLM calls simultaneously, significantly reducing response times. This approach ensures that even large-scale applications can operate efficiently, providing timely and relevant outputs without excessive delays.

For instance, in a deployment for a leading global bank, Trustwise Optimize:ai optimized token consumption through intelligent model selection, safety and alignment evaluations caching, and dynamic GPU scaling. It evaluated and classified user inputs to determine the optimal response strategy by using the most cost-effective option that met safety, alignment, and latency performance requirements. In addition, sophisticated compliance cross-walks integrated into the AI pipeline ensured adherence of AI output to corporate policies and regulatory standards, such as NIST AI RMF, EU AI Act, and GDPR, reducing non-compliance risks and enhancing trust.

This deployment resulted in a reduction of token consumption by 80% and a 64% decrease in carbon emissions, while ensuring 100% of AI system outputs aligned with corporate policies and regulations. By optimizing token usage and enhancing efficiency, Trustwise Optimize:ai API not only reduced costs but also supported sustainability goals and maintained compliance.

In summary, Trustwise Optimize:ai API addresses the four critical dimensions of cost, safety, alignment, and latency by employing a combination of advanced optimization techniques and robust crosswalks. This ensures that AI solutions are efficient, secure, compliant, and responsive, helping enterprises harness the full potential of generative AI while avoiding common deployment challenges.