Optimizing GenAI Performance from the Front-end layer with Lesly Sandra
Summary of episode #47 of the Angularidades podcast
Listen to the entire conversation in Spanish with Lesly Zerna on Spotify, YouTube, and other podcast platforms.
This episode welcomes Lesly Zerna, a Google Developer Expert in Machine Learning from Sucre, Bolivia. She has a solid background in Telecommunications Engineering and a Master’s in Computer Science from the Vrije Universiteit Brussel in Belgium. Lesly brings a wealth of experience as an instructor, mentor, content creator, tech entrepreneur, and innovation leader. Currently, she works as a Curriculum Developer at DeepLearning.AI.
Topics covered
- Software development process with LLMs
- Effectiveness of RAG systems in multimodal contexts
- Security and privacy considerations in AI
- Performance optimization of LLMs queries in web development
- Embedded models in the Edge and in the browser
- Recommendations for those starting in ML and GenAI
In this episode, Lesly discusses the critical considerations when selecting a machine learning tool, emphasizing compatibility, flexibility, scalability, performance, community support, and cost. She highlights the evolving landscape of AI, underscoring the importance of data security and privacy and reflecting on how essential these aspects are for delivering a better UX and ensuring the protection of sensitive information.
The conversation covers the stages of developing AI models, focusing on data preparation, model training, and evaluation. Lesly explains the significance of high-quality data and the use of neural networks and deep learning techniques. She also touches on the challenges of ensuring accurate and coherent results from AI models, acknowledging the phenomenon of AI hallucinations where models might generate incorrect or nonsensical outputs.
Leslie shares insights on the application of AI in web development, particularly for front-end developers using frameworks such as Angular. She discusses techniques like lazy loading, data compression, and caching to optimize API interactions and improve performance when handling large datasets. Additionally, she mentions the potential of embedding lightweight AI models in browsers or at the Edge to enhance real-time data processing.
The episode also covers the latest advancements in AI models from Google, including the Gemini and Gemma models. Leslie points out the community-driven projects on platforms like Kaggle that leverage these models for various applications, showcasing the collaborative nature of AI development.
For those new to the field of Machine Learning, Leslie advises starting with a strong foundation in core concepts and engaging in hands-on practice. She recommends exploring tools like TensorFlow.js for web-based AI applications and emphasizes the importance of creativity in developing innovative solutions.
Leslie concludes by stressing the ongoing need to balance technological advancements with practical considerations like cost, performance, and user experience. She envisions a future where AI and machine learning are integral to all aspects of technology, driving both professional growth and innovative product development.
Takeaways
- It is important to consider compatibility, flexibility, scalability, performance, community, and support when selecting an artificial intelligence tool.
- The development process for software dependent on LLMs involves data preparation, model training, and result evaluation.
- RAG systems are effective for analyzing multimodal contexts and generating precise responses.
- It is crucial to consider security and privacy when using artificial intelligence tools.
- Techniques like lazy loading, data compression, and caching are key to improve performance when working with LLMs in web applications.
- Models can be embedded in the Edge and in the browser to improve response time in data retrieval.
- Recommendations for those starting in the field of machine learning and GenAI include understanding the basic concepts, practicing with tools like TensorFlow.js, and leveraging creativity to develop interesting applications.
Stay tuned and check out who is being interviewed for future episode releases at x.com/angularidades or LinkedIn.
