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    <title>DEV Community: Cesco Fors</title>
    <description>The latest articles on DEV Community by Cesco Fors (@cescofors75).</description>
    <link>https://dev.to/cescofors75</link>
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      <title>DEV Community: Cesco Fors</title>
      <link>https://dev.to/cescofors75</link>
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      <title>Esquema baco.cat</title>
      <dc:creator>Cesco Fors</dc:creator>
      <pubDate>Thu, 07 Mar 2024 08:38:55 +0000</pubDate>
      <link>https://dev.to/cescofors75/esquema-bacocat-1aic</link>
      <guid>https://dev.to/cescofors75/esquema-bacocat-1aic</guid>
      <description>&lt;p&gt;Desglosando la Tecnología detrás de las Recomendaciones Personalizadas de Alimentos y Bebidas 💡&lt;/p&gt;

&lt;p&gt;¡Hola, comunidad!&lt;/p&gt;

&lt;p&gt;Hoy, queremos sumergirnos en cómo nuestro último proyecto aprovecha la inteligencia artificial y bases de datos modernas para transformar la industria alimentaria. Con la colaboración de gigantes de IA como OpenAI y Cohere, hemos creado embeddings que nos permiten entender profundamente las preferencias y restricciones alimenticias de los usuarios.&lt;/p&gt;

&lt;p&gt;La integración con Supabase nos permite gestionar estos datos de manera eficiente, mientras que Mixtral, nuestro motor de recomendación, utiliza estos insights para sugerir opciones de alimentos y vinos personalizados, teniendo en cuenta alergias y preferencias.&lt;/p&gt;

&lt;p&gt;Este enfoque no solo personaliza la experiencia alimentaria sino que también garantiza la seguridad del consumidor, un aspecto crucial en la nutrición personalizada.&lt;/p&gt;

&lt;p&gt;A continuación, desglosaremos las tecnologías y algoritmos que hacen posible este servicio. ¡Esperamos que encuentren inspiración en nuestro trabajo para sus propios proyectos innovadores!&lt;/p&gt;

&lt;h1&gt;
  
  
  DesarrolloDeSoftware #InnovaciónTecnológica #IAenAlimentos #OpenAI #Cohere #Supabase #Vercel
&lt;/h1&gt;

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      <category>embbedings</category>
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      <title>baco.cat</title>
      <dc:creator>Cesco Fors</dc:creator>
      <pubDate>Tue, 05 Mar 2024 10:46:56 +0000</pubDate>
      <link>https://dev.to/cescofors75/bacocat-4n0o</link>
      <guid>https://dev.to/cescofors75/bacocat-4n0o</guid>
      <description>&lt;p&gt;Discover a new dimension in wine selection with Baco.cat, where technological innovation meets a passion for wine to offer you an unparalleled experience. Through the cutting-edge use of Cohere and OpenAI embeddings, coupled with the efficiency of Supabase, we've transformed the way we recommend wines, manage allergen information, and group wines by tasting notes.&lt;/p&gt;

&lt;p&gt;Wondering how we make this possible? We've implemented vector fields in Supabase, enabling us to perform advanced semantic searches using cosine similarity. This means that no matter your level of wine knowledge, we can provide recommendations that perfectly align with your tastes and preferences, simplifying your search even when you're not exactly sure what you're looking for.&lt;/p&gt;

&lt;p&gt;Our goal is to personalize your wine selection experience, making it more informative, exciting, and tailored to you. Whether you're new to the wine world or an experienced sommelier, at Baco.cat, we're committed to helping you explore new vinous wonders and enrich your palate.&lt;/p&gt;

&lt;p&gt;For developers interested in how we integrate these technologies, here's a sneak peek:&lt;/p&gt;

&lt;p&gt;Using JavaScript and Next.js for a seamless user experience: We build our platform with Next.js, ensuring a fast and efficient user experience through its Server-Side Rendering (SSR) and Static Site Generation (SSG) capabilities. This allows us to offer an interactive and dynamic interface that makes exploring our wine selection easy.&lt;/p&gt;

&lt;p&gt;Integrating Supabase for data management and semantic searches: Supabase gives us the flexibility of a relational database with the power of semantic searches, thanks to the integration of vector fields. This allows us to perform complex and precise queries based on user preferences, all in real-time.&lt;/p&gt;

&lt;p&gt;Implementing text embeddings with Cohere and OpenAI for personalized recommendations: We use text embeddings to deeply understand our users' preferences and tastes. This enables us to offer highly personalized recommendations, as we can compare wine descriptions with users' expressed preferences, ensuring a precise match.&lt;/p&gt;

&lt;p&gt;Optimizing the wine classification and recommendation process: Through the implementation of cosine similarity algorithms, we efficiently classify and recommend wines, ensuring that each recommendation is relevant and tailored to our users' interests.&lt;/p&gt;

&lt;p&gt;We invite you to join the Baco.cat community and experience wine selection in a completely new and exciting way. Explore with us and discover your next favorite wine!&lt;/p&gt;

&lt;h1&gt;
  
  
  Wine #Technology #JavaScript #NextJS #Supabase #Cohere #OpenAI #WebDevelopment #Innovation
&lt;/h1&gt;

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      <category>javascript</category>
      <category>embeddings</category>
      <category>nextjs</category>
      <category>supabase</category>
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