Session on "Use Cases and Risks of ML in Capital Markets" | 23rd Dec at 4pm Hi everyone! The AI and Risk Mitigation project is well underway and for the third session, we will be joined by Rachna Maheshwari, Associate Director at CRI… more
The 2023 Monsoon edition is curated by:
- Nischal HP, Vice President of Data Engineering and Data Science at Scoutbee. Nischal curated the MLOps conference which was held online between 23 and 27 July 2021.
- Sumod Mohan, Founder and CEO at AutoInfer. Sumod curated Anthill Inside 2019 edition, held in Bangalore on 23 November.
- AI and Research - covers research, findings, and solutions for challenges on building models in various areas such as fraud detection, forecasting, and analytics. This track delves into the latest methodologies for handling challenges such as large-scale data processing, distributed computing, and optimizing model performance.
- Industrial applications of ML - covers implementation of AI in the industry, with more focus on the AI models, the issues in training, gathering data so, and so forth. ML is being used at scale in industries such as automotive, mechanical, manufacturing, agriculture, and such domains. This track focuses on the challenges in this space, as we see innovation coming out of these industries in the pursuit of using ML on a second-to-second basis.
- AI and Product - covers strategies for building AI products to scale and mitigating challenges. This track provides insights on incorporating AI tools and forecasting techniques to improve model training, developing a working model architecture, and using data in the business context.
There are three phases in the lifecycle of an application - research, application and aftermath of the application.
- Assess capabilities, determining the new frontiers for AI.
- Find a use for the application.
- Learn how to run it, monitor it and update it with time.
The three tracks at the 2023 Monsoon edition of The Fifth Elephant will cover this lifecycle.
The Fifth Elephant 2023 Monsoon edition will be held in-person. Attendance is open to The Fifth Elephant members only. Purchase a membership to attend the conference in-person. If you have questions about participation, post a comment here.
- Data/MLOps engineers who want to learn about state-of-the-art tools and techniques, especially from domains such as automobile, agri-tech and mechanical industries.
- Data scientists who want a deeper understanding of model deployment/governance.
- Architects who are building ML workflows that scale.
- Tech founders who are building products that require AI or ML.
- Product managers, who want to learn about the process of building AI/ML products.
- Directors, VPs and senior tech leadership who are building AI/ML teams.
Sponsorship slots are open for:
- Infrastructure (GPU, CPU and cloud providers) and developer productivity tool makers who want to evangelise their offering to developers and decision-makers.
- Companies seeking tech branding among AI and ML developers.
- Venture Capital (VC) firms and investors who want to scan the landscape of innovations and innovators in AI and who want to source leads for investment in the AI and ML space.
Unlocking the Usage of ChatGPT: Simplifying with PyAIKit
I am working in ABInBev as Senior Manager – Data Science with experience in Statistical/Machine Learning and Predictive Modelling and analytics consulting. With a passion for machine learning and data-driven solutions, I have been actively involved in the development and implementation of advanced analytics frameworks. I am master’s in computer science and have 12+ years of experience in conceptualization and delivery of actionable models across Finance, Media, Retail, Wholesale and Logistics industries.
Blog post: Linkedin Post
Package url : PyAIKit
The objective of this presentation is to showcase PyAIKit, a Python package designed to simplify the usage of large language models (LLMs) like ChatGPT. This abstract highlights the purpose, value, outline, and possible use cases of PyAIKit, emphasizing its significance in making LLMs more accessible and user-friendly.
The purpose of this presentation is to demonstrate how PyAIKit simplifies the utilization of LLMs, focusing on ChatGPT API. By leveraging PyAIKit’s functionalities and pre-built components, developers can easily incorporate LLMs into their projects, reducing complexity and unlocking the full potential of these advanced language models.
Overview of the challenges and complexities associated with utilizing LLMs like ChatGPT through its API.
Explanation of the key features, functionalities, and benefits of PyAIKit in the context of LLM integration.
Exploration of possible use cases where PyAIKit can be leveraged with ChatGPT API, including:
a. Sentiment Analysis
b. Document Summarizer
d. Text Generator
PyAIKit offers some advantages to developers, including:
- PyAIKit enhances the usability and accessibility of ChatGPT API by providing a streamlined interface.
- It abstracts away complexities and handles authentication, API calls, and error handling behind the scenes.
- Developers can seamlessly integrate ChatGPT functionality without dealing with API intricacies.
- PyAIKit offers enhanced control over text generation, eliminating the need for trial and error.
- It has already been optimized with different prompts and OpenAI tokens, saving effort and cost for users.
Limitations of PyAIKit
Data Security: As PyAIKit utilizes the OpenAI API, it’s crucial to ensure the security of confidential information when transmitting data through the API.
Cost Considerations: Although the package is open-source, it relies on the ChatGPT API, which may involve charges based on usage.
Model Limitations: PyAIKit depends on the underlying ChatGPT models for text generation and NLP tasks. While ChatGPT performs impressively, it’s important to recognize that the model has some limitations.
In conclusion, PyAIKit simplifies the usage of large language models like ChatGPT for the developers.