Sparkonomy

AI can now dream. Claude’s AutoDream is a sleep cycle for memory, built on Auto Memory. Its job is simple: clean up, merge and prune memory so it stays useful. We’re feel this at @SparkonomySays . Memory drifts, duplicates and gets expensive. AI needs to DREAM!

@I_ChunLin @everlaw Thanks for the shoutout!

• @SparkonomySays: Creator-to-brand matching with a unified “Creator Genome” from videos + images + audio (70% lower latency) • @everlaw: Legal discovery across millions of docs, diagrams, photos & exhibits (20% recall lift)

How is everyone building with @GeminiApp Embedding 2 right now… and I’m building mine for the designers? The new multimodal model (text + images + video + audio + PDFs in one space) dropped 19 days ago and builders are already shipping fast. Here’s the current wave 👇

𝗣𝗼𝗶𝗻𝘁 𝟯: 𝗠𝗮𝘀𝘀𝗶𝘃𝗲 𝗥𝗲𝘀𝘂𝗹𝘁𝘀 Sparkonomy reports text-to-video similarity scores doubled from 0.4 to 0.8. Everlaw is seeing huge jumps in precision and recall across millions of records. This is a new performance floor. #BigData #SearchEngine

@grok @mankaff_ @GoogleAIStudio Thanks for the callout!

Here are real-world use cases for Gemini Embedding 2: - Legal discovery (Everlaw): Embed docs, images & videos across millions of records for faster, precise searches in litigation. - Creator platforms (Sparkonomy): Index video/images/text to match brands with creators—doubles semantic similarity, cuts latency 70%. - Wellness apps (Mindlid): Combine conversational text with audio/visual embeddings for 20% better recall in personalized Q&A. More: Multimodal RAG for e-commerce (image+text product search), healthcare (scans+notes clustering), content recs in media apps. Try the demo!

💎İşin teknik boyutunda devasa bir yanlış fiyatlama düzeltmesi var. Sparkonomy'nin verilerine göre, LLM çıkarımının devreden çıkmasıyla gecikme %70'e kadar azalıyor. 🛡️Metin-görüntü eşleşmesinde anlamsal benzerlik skoru 0.4'ten 0.8'e sıçrıyor. Bu, veri analizindeki en büyük zamanlama uyumsuzluklarından birinin bitişidir. 👇👇👇

@inflectivAI @GoogleAIStudio Thanks for the callout!

@GoogleAIStudio The real-world results from partners like Everlaw and Sparkonomy are impressive. Seeing a 70% latency reduction and doubled similarity scores proves this isn't just a minor update, but a new baseline for multimodal RAG.

@ErickSky Thanks for the callout!

Esto es lo que usan ya Everlaw (abogados con millones de casos), Sparkonomy y Mindlid. No es magia inventada: es el flujo estándar de embeddings + búsqueda vectorial, pero ahora con TODO multimodal en un solo modelo.

Si eres abogado y te toca defender a alguien que te llega desesperado con: - Video del accidente (con audio). - Fotos de las lesiones. - Contrato del seguro. Y tienes que armar el caso YA (tienes literalmente 5 minutos antes del juicio) ¿QUÉ DEMONIOS HACES? Sigue abajo 👇

@somi_ai Thanks for the callout!

The early numbers from partners are worth noting. Sparkonomy: 70% latency reduction, semantic similarity jumping from 0.4 to 0.8 on text-image pairs. Mindlid: 20% lift in top-1 recall. Everlaw: improved precision and recall across millions of legal records. These aren't toy benchmarks. They're production workloads.

Google just shipped an embedding model that puts text, images, video, audio, and documents into a single vector space. Gemini Embedding 2 is now in public preview. Here's why this is a big deal for anyone building RAG or search systems:

@kroszborgg @ajeetunc Flattered that you love our landing page! 😅

@ajeetunc still need a landing page? im thinking somethins like this in the bg of the landing page i made sparkonomy.com

who's up?

@MustafyOf Thanks a lot for the callout!

A creator platform called Sparkonomy cut their processing time by up to 70% and nearly doubled their accuracy scores using it. A wellness app called Mindlid saw a 20% improvement in how accurately it retrieves personal memories combining text, audio and visual data together.

🚨BREAKING: Google just built an AI that understands text, images, videos and audio all at the same time. One brain. Every type of content. Zero switching between tools. Here is everything you need to know 👇👇

@Nas_tech_AI Thanks for the callout!

4. Real Results From Real Companies Already Using It A legal tech company called Everlaw is already using it to help lawyers search through millions of records including images and videos during litigation. A creator platform called Sparkonomy cut their processing time by up to 70% and nearly doubled their accuracy scores using it. A wellness app called Mindlid saw a 20% improvement in how accurately it retrieves personal memories combining text, audio and visual data together.

🚨BREAKING: Google just built an AI that understands text, images, videos and audio all at the same time. One brain. Every type of content. Zero switching between tools. Here is everything you need to know 👇👇

@jackcoder0 Thanks for the callout!

4. Real Results From Real Companies Already Using It A legal tech company called Everlaw is already using it to help lawyers search through millions of records including images and videos during litigation. A creator platform called Sparkonomy cut their processing time by up to 70% and nearly doubled their accuracy scores using it. A wellness app called Mindlid saw a 20% improvement in how accurately it retrieves personal memories combining text, audio and visual data together.

🚨BREAKING: Google just built an AI that understands text, images, videos and audio all at the same time. One brain. Every type of content. Zero switching between tools. Here is everything you need to know 👇👇

We are thrilled to be featured in @Google's launch of the new Gemini Embeddings 2 Model! It’s a major leap in how AI understands video, audio, and text - the exact fuel supercharging Sparkonomy’s proprietary Creator Genome. 🧬 @GeminiApp @googlecloud