{"type":"rich","version":"1.0","provider_name":"Transistor","provider_url":"https://transistor.fm","author_name":"Machine Learning Tech Brief By HackerNoon","title":"Six Lessons From Building an AI-Powered Marketplace Search Engine","html":"<iframe width=\"100%\" height=\"180\" frameborder=\"no\" scrolling=\"no\" seamless src=\"https://share.transistor.fm/e/469596fb\"></iframe>","width":"100%","height":180,"duration":470,"description":"\n        This story was originally published on HackerNoon at: https://hackernoon.com/six-lessons-from-building-an-ai-powered-marketplace-search-engine.\nA builder’s postmortem on multilingual AI marketplace search, from fake category IDs and broken price filters to caching, regex bugs, and latency.\nCheck more stories related to machine-learning at: https://hackernoon.com/c/machine-learning.\n            You can also check exclusive content about #ai-search, #multilingual-search, #ai-engineering, #search-relevance, #regex, #search-optimization, #production-ai, #query-parsing,  and more.\nThis story was written by: @ohadfarkash. Learn more about this writer by checking @ohadfarkash's about page,\n            and for more stories, please visit hackernoon.com.\nThe hardest parts of building multilingual AI search were not the LLM itself, but the system boundaries around it: API units, unvalidated IDs, bad regex assumptions, cache ordering, latency, and messy marketplace data.","thumbnail_url":"https://img.transistorcdn.com/KyA01h2FD2insgk-wX_xzV6vbJnTNl2BvPYVL-XaI9A/rs:fill:0:0:1/w:400/h:400/q:60/mb:500000/aHR0cHM6Ly9pbWct/dXBsb2FkLXByb2R1/Y3Rpb24udHJhbnNp/c3Rvci5mbS9zaG93/LzQxMjcyLzE2ODM1/ODI0ODgtYXJ0d29y/ay5qcGc.webp","thumbnail_width":300,"thumbnail_height":300}