Understanding large language learning models (ChatGPT),
the applications, and benefits across oil & gas operations
Wednesday, September 13 – Hilton Americas (Houston, TX)
About the Workshop
Over the last several months, Large Language Models (LLMs) like OpenAI's ChatGPT have taken the news by storm, creating a variety of solid responses across the industry ranging from concerns over data privacy and job security to excitement over impending boosts to productivity and innovation. The strength of these reactions correlates with the universally recognized capabilities of the LLMs: they can answer questions with uncanny accuracy and with a profound appeal to context. While uncertainty looms, some organizations in the industry are already using the models, building, and deploying tools to optimize processes, enhance decision-making, and make predictions.
- Demystify LLMs: Gain an in-depth understanding of large language models, breaking down the complexities of these AI tools into practical, understandable concepts.
- Industry Relevance: Discover LLMs' specific relevance and potential within the oil and gas sector, illuminating pathways to improved operational efficiency and strategic decision-making.
- Transformers Explained: Understand the evolution and functionality of transformers, which lie at the heart of modern large language models.
- Data Security: Learn strategies for leveraging the power of LLMs while maintaining data privacy and security, ensuring your organization's sensitive information is protected.
- Fine-Tuning Techniques: Acquire practical skills for fine-tuning LLMs to adapt them to specific organizational tasks or data sets, saving time and computational resources.
- Prompt Engineering: Learn the art of prompt engineering, a key technique for designing effective inputs that elicit desired responses from pre-trained models.
- Application Scenarios: Explore real-world use cases of LLMs within the oil and gas industry, gaining insights into how these models can be effectively deployed.
- Networking Opportunity: Network with industry professionals, AI experts, and peers, fostering valuable connections and collaborative opportunities for the future.
Who Should Attend:
- Geologists: Professionals in the oil and gas industry who want to understand how AI and LLMs can help in data analysis and interpretation tasks
- Engineers: Petroleum and drilling engineers looking to optimize operations, increase efficiency, and reduce risks with the help of AI and LLMs
- Field Workers: Individuals involved in on-site operations which can leverage AI for better decision-making, safety, and maintenance planning
- Operation Managers: Professionals overseeing logistics, operations, and project execution, who want to explore how LLMs can streamline processes and improve forecasting
- C-Suite Executives: CEOs, CIOs, CTOs, and other executives in the oil and gas sector interested in leveraging AI for strategic advantages and organizational growth
- Data Scientists and Analysts: Professionals in data-centric roles within the oil and gas industry looking to upskill in AI and LLMs for industry-specific applications
- IT Professionals: Those implementing, managing, or supporting AI initiatives within their oil and gas organizations
- Research and Development Professionals: Individuals involved in R&D within the oil and gas industry, particularly those exploring AI and machine learning solutions
- Consultants: Individuals or entities providing strategic or technical advice to oil and gas companies who would benefit from a deeper understanding of the capabilities of AI tools like LLMs
9:00-9:40 Section 1: LLM Relevance in the Oil & Gas Industry
- How LLMs came about
- Who are the major players are
- What is going to change
- How should we prepare for a new mainstream
- How can we be ahead of the curve
9:40-11:20 Section 2: The Inner Workings of LLMs
- A brief overview of machine learning
- History and intuitive explanation of convolutional neural networks
- Background of natural language processing and text analytics
- Intuitive description of transformers and large language models
11:20-11:40 Networking Break
11:40-12:30 Section 3: Organizational Navigation of LLMs
- What the data privacy and data security risks are
- What are the methods to overcome or circumnavigate these risks
- Different strategies for deployment and their comparative advantages
1:30-3:00 Section 4: Applications of LLMs
- How to set up and use LLM personal accounts
- How to deploy LLM models in personal applications
- Best practices for fine-tuning
- Best practices for prompt engineering
3:00 End Workshop