After every year learning extends Data, AI, Products, and Domain. 2023 had a blend of experiences. Still figuring out answers for every dimension #2023 #Learnings
→ How you've adapted to industry shifts, and GenAI's meaningful adoption. Possible use cases vs relevant, meaningful production-ready use cases. Example - Newly launched section in Amazon reviews, What customers say.
→ How you've overcome engineering challenges balancing business goals. New ways to solve old problems with Foundation models. Time vs building a production-grade solution. Example - Moving away from custom NER vs Leveraging LLM Embeddings, Blend of both custom embedding + RAG, New ways of solving.
→ How your skills align with the company's vision, Learning to predict the future. New approaches and papers evolve faster than certifications. A blend of tech + and domain is key. Segment Anything model, Visual QnA, Intructpix2pix have made more vision use cases feasible Tryon, etc..
→ How you bridge the gap between tech and business, Fast yet impactful use cases, Get the basics right. Demos / New offerings vs making it to production need a careful selection of use cases / applying past experiences to get things right in the first iteration. Balance the tradeoff between creativity vs innovation vs build a product strategy vs solve a real need vs fancy demos. #learning #perspectives #solutions #datascience #MachineLearning #AI #DeepLearning
Keep Exploring!!!
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