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Meta AI Open-Sourced Perception Encoder Audiovisual (PE-AV): The Audiovisual Encoder Powering SAM Audio And Large Scale Multimodal Retrieval

Meta researchers have introduced Perception Encoder Audiovisual, PEAV, as a new family of encoders for joint audio and video understanding. The model learns aligned audio, video, and text representations in a single embedding space using large scale contrastive training on about 100M audio video pairs with text captions. From Perception Encoder to PEAV Perception Encoder, […]

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Auto Quantum Circuits

«AutoQML, self-assembling circuits, hyper-parameterized Quantum ML platform, using cirq, tensorflow and tfq. Trillions of possible qubit registries, gate combinations and moment sequences, ready to be adapted into your ML flow. Here I demonstrate climatechange, jameswebbspacetelescope and microbiology vision applications… [Thus far, a circuit with 16-Qubits and a gate sequence of [ YY ] – [ XX ] – [CNOT]

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Human Learn

Machine learning covers a lot of ground but it is also capable of making bad decision. We’ve also reached a stage of hype that folks forget that many classification problems can be handled by natural intelligence too. This package contains scikit-learn compatible tools that should make it easier to construct and benchmark rule based systems

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Google Introduces T5Gemma 2: Encoder Decoder Models with Multimodal Inputs via SigLIP and 128K Context

Google has released T5Gemma 2, a family of open encoder-decoder Transformer checkpoints built by adapting Gemma 3 pretrained weights into an encoder-decoder layout, then continuing pretraining with the UL2 objective. The release is pretrained only, intended for developers to post-train for specific tasks, and Google explicitly notes it is not releasing post-trained or IT checkpoints

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The rise of small language models for information extraction

Small language models like GLiNER provide an efficient, deterministic, and flexible solution for named entity recognition, bridging the gap between traditional NLP and large language models for enterprise information extraction. The post The rise of small language models for information extraction appeared first on SAS Blogs.

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How to Design a Gemini-Powered Self-Correcting Multi-Agent AI System with Semantic Routing, Symbolic Guardrails, and Reflexive Orchestration

In this tutorial, we explore how we design and run a full agentic AI orchestration pipeline powered by semantic routing, symbolic guardrails, and self-correction loops using Gemini. We walk through how we structure agents, dispatch tasks, enforce constraints, and refine outputs using a clean, modular architecture. As we progress through each snippet, we see how

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엔터프라이즈 합성 데이터 생성 솔루션, ‘SAS 데이터 메이커’ 공식 출시

혁신적인 합성 데이터 생성 솔루션으로 데이터 부족 문제 해결, AI 역량 강화 마이크로소프트 마켓플레이스에서 우선 공급   민감한 개인정보를 노출하지 않으면서 안전하게 합성 데이터를 생성할 수 있게 해주는 ‘SAS 데이터 메이커’가 출시되었습니다. 현재 마이크로소프트 마켓플레이스에서 제공되는 ‘SAS 데이터 메이커’는 실제 데이터의 통계적, 관계적, 시간적 특성을 그대로 재현하는 합성 데이터를 생성하며, […] The post 엔터프라이즈 합성

엔터프라이즈 합성 데이터 생성 솔루션, ‘SAS 데이터 메이커’ 공식 출시 Read More »

Mistral AI Ships Devstral 2 Coding Models And Mistral Vibe CLI For Agentic, Terminal Native Development

Mistral AI has introduced Devstral 2, a next generation coding model family for software engineering agents, together with Mistral Vibe CLI, an open source command line coding assistant that runs inside the terminal or IDEs that support the Agent Communication Protocol. https://mistral.ai/news/devstral-2-vibe-cli Devstral 2 and Devstral Small 2, model sizes, context and benchmarks Devstral 2

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AI 거버넌스, 더 늦추면 안 되는 이유

AI는 금융을 비롯한 다양한 산업에서 혁신을 가속화하고 있습니다. 하지만 그 이면에는 데이터 편향, 환각(Hallucination), 개인정보 유출 등 새로운 리스크가 빠르게 증가하고 있죠. SAS는 지난 9월 17일 ‘금융기관을 위한 AI 거버넌스 및 미래 혁신 전략 세미나’를 개최하고 AI 기본법 시행을 앞둔 현 시점에서 금융기관이 어떤 준비를 갖춰야할 지에 대한 핵심 내용을 […] The post AI 거버넌스,

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