š¤ Building AI applications involves converting text into numerical representations for similarity searches.
š” Using generative AI and large language models opens up new possibilities.
š° Over the past four months, the speaker made over $100k in revenue through AI projects.
š” Control the data input to achieve desired outputs from AI models.
š Use Azure open AI to ensure data privacy and protection.
ā” Adapt quickly to the rapidly changing world of AI and generative AI.
š” Staying up to date and being adaptable is crucial in the field of AI.
š Technology is evolving rapidly, so one must be prepared to switch to better solutions as they emerge.
š§ While pre-trained language models are useful, providing context and quality data is still essential for effective AI applications.
š A thorough assessment of data quality is important for professionals helping other companies with AI projects.
š Starting with a proof of concept and gradually scaling up is a recommended approach for AI projects.
Start small and work with proof of concepts to tackle isolated problems and add value with AI technology.
Ensure rapid feedback cycles and involve the customer in the development process.
Transitioning from proof of concept to production is challenging due to non-deterministic language models and user interactions.
š Having a solid evaluation system is critical for AI projects.
š Monitor and evaluate language models and applications for drift over time.
š»š§ Building AI applications requires both software engineering and data science skills.
š Building successful AI projects requires a team with roles including data scientists, machine learning engineers, software developers, and front-end developers.
š” Transitioning towards software engineering provides new opportunities for machine learning engineers, especially in working with large language models and generative AI.
š° To be successful in AI projects, it is important to partner up and work as a team, as custom development requires too much work for a single person alone.
š° Successfully completing AI projects can be highly lucrative for businesses, with the potential to generate significant profits.
š Even working part-time, the speaker's company was able to make a profit of $50k within four months from AI projects.
š The speaker shares lessons learned from their experience, aiming to help others interested in taking on their own AI projects.
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