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#multimodal

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99 sunny6d ago · 7 min read

Native multimodal still allows a separate encoder

People often treat "native multimodal" as a single architecture choice: one shared stack that eats pixels, audio and text from the first layer. When DeepSeek-V4.1-Flash still ships an independent Deep

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Ethan SteiningerOct 25 · 11 min read

Building a Multimodal Deep Research Agent

How we went from "please find me information about this image" to building an AI that can reason across documents, videos, images, and audio like a digital Sherlock Holmes When Search Gets Visual Pic

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Manu ShuklaAug 22 · 12 min read

DeepSeek shipped vision on 21 August 2026 at $0.22 per million input tokens, with a 384-token cap per image

DeepSeek shipped vision on 21 August 2026 at $0.22 per million input tokens, with a 384-token cap per image Summary. DeepSeek released deepseek-v4-flash-vision-exp on 21 August 2026, its first multimo

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Pranjal VermaAug 9 · 8 min read

Unstructured data becomes a first-class citizen: Databricks FILE type and the multimodal lakehouse

Last week Databricks announced the beta of FILE, a native column type that brings documents, images, audio, and video into your lakehouse tables with the same governance you already apply to structure

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Coding DropletsJul 5 · 12 min read

How to Build a Multimodal AI Endpoint in ASP.NET Core: Image to Structured Data

A support agent uploads a screenshot of an error dialog. A finance team drops a photo of a paper receipt into a form. A field engineer snaps a picture of a serial-number plate. In every case the busin

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SapotaCorpMay 24 · 7 min read

Multimodal RAG: when summary-based stops being enough

A SaaS founder pinged us last quarter with a complaint that sounded familiar. Their AI assistant, built on top of a research-paper knowledge base, kept giving answers like "the chart shows a positive

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Jangwook KimApr 20 · 12 min read

Meta Muse Spark Developer Guide 2026: Benchmarks, Modes, API

Meta launched Muse Spark on April 8, 2026 — the first model from Meta Superintelligence Labs (MSL), and the company's most deliberate signal yet that it is playing to win in the closed-model frontier AI race. Led by Alexandr Wang, who joined as Meta'...

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Jangwook KimApr 16 · 10 min read

Gemini 3.1 Ultra: Long Context and Multimodal Dev Guide

Google's Gemini 3.1 generation marks a turning point in how developers interact with large language models. With a 1-million-token context window, native processing of video, audio, images, and code in a single request, plus sandboxed in-session code...

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satoruApr 13 · 7 min read

Real-Time Speech, Audio, and Facial Analysis in Production AI Systems

Last post covered multimodal fusion, temporal alignment, and conflict resolution at the architecture level. This one goes into the actual modality processing — how you handle speech, audio emotion, and facial analysis in real-time production systems....

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Rahul SehrawatApr 12 · 10 min read

Multimodal AI — Models That See, Hear, and Act

Until recently, most AI systems were monolingual in a very specific sense: each system worked on one kind of input. Speech recognizers took audio and produced text. Image classifiers took pictures and produced labels. Translation systems took one lan...

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