In this keynote, we'll explore the potential of Large Language Models (LLMs) in unlocking legacy systems and rethinking the connective tissue between legacy datasets and systems with new experiences. Traditionally, enterprises have relied on costly and time-consuming solutions to abstract legacy technology or modernize legacy systems. However, LLMs offer us the change to reimagine this enterprise architecture. By leveraging an LLMs ability to understand APIs, systems, and call tools, LLMs can generate the required structured output to interact with dozens of legacy systems. In this talk, we will discuss the ways LLMs can augment and replace enterprise gateways, reducing the need for custom software development and middleware solutions. We'll also examine the critical role of inference speed in enabling the deployment of LLMs in new and unique ways and explore the potential for LLMs to become a core tool in the enterprise.

With GenAI (Generative AI) leading the way, in today’s rapidly evolving digital landscape, the integration of Conventional and Generative AI in enterprises and businesses offers a transformative potential that can redefine how they operate, innovate, and deliver value to their customers.

Being at the forefront of this paradigm disruption, Hexaware has been empowering industry leaders to make smarter choices, radically accelerate productivity, secure organizations, maximize data potential, and revolutionize customer experiences by strategically aligning GenAI capabilities with specific business goals through a structured approach driven by feasibility, relevance, and ROI.

Join us for an insightful fireside chat which aims to demystify the complexities of implementing GenAI and AI at scale, offering a roadmap for organizations looking to leverage these technologies for competitive advantage.

In the ever-evolving generative AI landscape, GPUs have remained the dominant architecture for running large AI models. However, GPUs rely on brute force and are incredibly inefficient, not to mention increasingly unavailable. It’s clearly time for a change. It’s time for the comeback of the CPU.

You may be surprised to learn that running AI models on CPUs can bring about significant performance enhancements and incredible flexibility. By taking advantage of the rapidly evolving CPU architecture and mapping our unique neuroscience-based optimizations to it, Numenta is bringing this technological revolution to the generative AI field today. 

This presentation will explore:

1. The benefits of embracing CPU-based AI, from reducing the cost and complexities associated with GPUs to increasing flexibility and scalability. 
2. The latest advancements in Numenta’s neuroscience-based AI platform, NuPIC, the Numenta Platform for Intelligent Computing.
3. Practical applications of CPU-based generative AI through a customer success story

Artificial intelligence (AI) stands at the forefront of enterprise innovation, offering unparalleled opportunities for growth, efficiency, and competitive advantage. However, the journey toward AI optimization is fraught with challenges, from legacy infrastructures to strategic alignment and workforce readiness. This keynote speech will navigate the complex landscape of AI integration, presenting a comprehensive roadmap tailored for Fortune 500 companies ready to harness the power of generative AI.

In an era where artificial intelligence is not just an asset but a necessity, understanding the intricacies of Large Language Models (LLMs) has become paramount for enterprises. This session, 'Understanding and Mitigating Hallucinations in Large Language Models', offers a deep dive into the phenomenon of LLM hallucinations – a critical challenge in the deployment of AI technologies in business environments.

We will explore the mechanics behind LLM hallucinations, shedding light on how these AI models, despite their sophistication, can generate inaccurate or misleading information. From the subtlety of input-conflicting hallucinations to the complexity of context and fact-conflicting errors, we will dissect various types of hallucinations with real-world examples, including notable instances from prominent LLMs.

This talk will not only focus on the identification and detection of such hallucinations but will also present effective strategies for mitigation. We will discuss the role of data quality, model fine-tuning, and advanced techniques like Reinforcement Learning with Human Feedback (RLHF) in reducing the risks of inaccuracies. Furthermore, the session will highlight the importance of balancing the creative potential of LLM hallucinations with the need for factual accuracy, especially in high-stakes business decisions.

Attendees will leave with a comprehensive understanding of the challenges and opportunities presented by LLM hallucinations. This knowledge is crucial for enterprises looking to leverage AI responsibly and effectively, ensuring that their use of these powerful tools aligns with the highest standards of accuracy and reliability in the business world.

This presentation explores the integration of generative AI in healthcare and pharmacology, highlighting advancements in prompt engineering and its impact on decision-making. The session will examine the complexities and variability of AI responses and the difficulties in establishing a reliable ground truth, emphasizing the need for structured and reproducible outputs to support clinical and business processes efficiently.