{"id":298163,"date":"2024-04-12T08:21:35","date_gmt":"2024-04-12T15:21:35","guid":{"rendered":"https:\/\/www.saastr.com\/?p=298163"},"modified":"2024-04-12T08:21:35","modified_gmt":"2024-04-12T15:21:35","slug":"a-technical-deep-dive-into-building-ai-products-for-the-enterprise-with-contextual-ais-ceo-douwe-kiela","status":"publish","type":"post","link":"https:\/\/www.saastr.com\/a-technical-deep-dive-into-building-ai-products-for-the-enterprise-with-contextual-ais-ceo-douwe-kiela\/","title":{"rendered":"A Technical Deep Dive Into Building AI Products for the Enterprise with Contextual AI\u2019s CEO Douwe Kiela"},"content":{"rendered":"

If you work on anything related to Artificial Intelligence<\/a>, you know we\u2019re in the age of language models. But when it comes to Enterprises specifically, language models can change the way we work, <\/span>and <\/span><\/i>they have very big issues. At SaaStr AI Day, Contextual AI\u2019s CEO, Douwe Kiela, deep dives into what it takes to build AI products for the Enterprise.
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You might be familiar with some of the common language model issues.\u00a0<\/span><\/p>\n

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    1. Hallucination with very high confidence \u2014 making up stuff that isn\u2019t true but seems true.\u00a0<\/span><\/li>\n
    2. Attribution \u2014 knowing why these language models are saying what they\u2019re saying.\u00a0<\/span><\/li>\n
    3. Data privacy \u2014 we send valuable data to someone else\u2019s data center.\u00a0<\/span><\/li>\n
    4. Staleness and compliance \u2014 language models must be up-to-date, compliant with regulations, and able to be revised on the fly without having to retrain the entire thing every time.\u00a0<\/span><\/li>\n<\/ol>\n