๐๐ก ๐๐ข๐ ๐ก ๐๐๐๐๐๐๐ก๐๐ ๐ ๐ ๐๐๐ ๐กโ๐๐ ๐ ๐กโ๐๐ก ๐๐๐ ๐ ๐๐ ๐๐ก ๐๐ ๐๐๐โ๐ก ๐๐๐๐ค ๐คโ๐๐ก ๐ก๐ ๐๐ฅ๐๐๐๐ก ๐๐ ๐ฆ๐๐ข ๐๐. ๐ป๐๐๐โ๐ ๐ ๐๐ข๐๐๐ 3 ๐๐๐๐ข๐ก๐ ๐ค๐๐๐๐กโ๐๐๐ข๐โ.
The AI Summit New York has always been a space where ideas meet action, and this year was no exception. With speakers, from Coca-Cola, Google, Mastercard, META, and many more, the event in many cases showcased the forefront of AI innovation.
Yet, while walking through the event, I noticed a recurring theme: โ๐๐๐ฅ๐ค ๐ญ๐จ ๐๐จ๐ฎ๐ซ ๐๐๐ญ๐.โ Many vendors leaned heavily on Retrieval-Augmented Generation (RAG) models, emphasizing solutions that help organizations unlock value from their existing knowledge bases. While impressive, it felt like ๐๐ฬ๐๐ฬ ๐ฃ๐ข, a reflection of where we are, not where we need to go.
But amidst this familiar territory, a few standout vendors showcased something different: ๐๐ ๐๐ ๐๐ง๐ญ๐ฌ ๐๐ซ๐ข๐ฏ๐ข๐ง๐ ๐ซ๐๐๐ฅ ๐ฎ๐ฌ๐ ๐๐๐ฌ๐๐ฌ. These arenโt just tools for better conversation, theyโre autonomous problem-solvers. These systems take action, make decisions, and deliver tangible outcomes aligned with enterprise goals. Itโs here, in this leap from assistance to agency, that the future of GenAI truly lies.
Stay tuned for more insights as I share interviews with leaders who are driving this evolution forward. The conversations I had revealed an exciting shift in how AI can move beyond simply assisting to enabling enterprises to adapt and thrive in real-time.
๐๐ก๐๐ญ ๐๐ฑ๐๐ข๐ญ๐๐ฌ ๐ฒ๐จ๐ฎ ๐ฆ๐จ๐ฌ๐ญ ๐๐๐จ๐ฎ๐ญ ๐ญ๐ก๐ ๐ฌ๐ก๐ข๐๐ญ ๐๐ซ๐จ๐ฆ ๐๐ฌ๐ฌ๐ข๐ฌ๐ญ๐๐ง๐ญ๐ฌ ๐ญ๐จ ๐๐ ๐๐ง๐ญ๐ฌ? ๐๐๐ญโ๐ฌ ๐ค๐๐๐ฉ ๐ญ๐ก๐ ๐๐จ๐ง๐ฏ๐๐ซ๐ฌ๐๐ญ๐ข๐จ๐ง ๐ ๐จ๐ข๐ง๐ .
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