By combining our fastRAG framework with Haystack by deepset, we’ve built a powerful multimodal agent capable of retrieving and answering questions about nutrition facts. Utilizing Microsoft's Phi-3.5-vision-instruct model, the agent relies on multi-hop reasoning and ReAct architecture to effectively handle complex queries, making it an ideal solution for real-time nutrition information retrieval. Read the blog to learn more about building a multimodal agent that can interpret both text and image data to help answer practical questions. https://intel.ly/3V4wn30 #RAG #Multimodal #Agents
关于我们
See what it means to be on the vanguard of research in computer science, academic and industry collaboration, and a leader in visionary thinking about technology, the sciences, society, and culture. Intel Labs, the research arm of Intel Corporation, is inventing tomorrow's technology to make our lives easier, more enjoyable and more productive.
- 网站
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https://intel.com/labs
英特尔研究院的外部链接
- 所属行业
- 研究服务
- 规模
- 超过 10,001 人
- 总部
- Hillsboro,OR
- 类型
- 上市公司
- 创立
- 1968
- 领域
- Research、Microprocessor、Computer Architecture、Circuits、Comms、Systems、Platforms、Energy、Nanotechnology、Ethnography、Security、Quantum Computing、Neuromorphic Computing、Artificial Intelligence和Computer Science Research
地点
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主要
2111 NE 25th Ave
US,OR,Hillsboro,97124
英特尔研究院员工
动态
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Human-inspired, Cognitive AI is the future of machine learning. Enabled with multimodal cognition, machines will continue to advance closer to human-level performance in a variety of real-world applications. Learn more about Intel Labs research aiming to bridge the gap between human and machine intelligence in this video with Vasudev Lal: https://intel.ly/40Ub5sy #Multimodal #RAG #Research
Cognitive AI: Multimodal RAG on Intel? Gaudi? Accelerators | Tech Talk
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Universal Assisted Generation (UAG) is a groundbreaking method for extending assisted generation support to small language models from any model family! Developed in collaboration with Hugging Face, UAG makes it possible to accelerate inference from any decoder or Mixture of Experts models by ~2x with almost zero overhead. Learn more from the researchers behind the method in this blog. https://intel.ly/40GwOnN Daniel Korat, Oren Pereg, Moshe Berchansky, Jonathan Mamou, Jo?o Gante, Lewis Tunstall, Nadav T. and Moshe Wasserblat #AI #AssistedGeneration #LLMs
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Maintaining data integrity, privacy, and accuracy is at the heart of our security research. From innovations that help protect sensitive workloads to the development of AI methods that will help restore the public’s trust in media, Intel Labs researchers remain at the forefront of security and privacy research and development. Learn more here: https://lnkd.in/g6Q8ik9P ? #Developer #ArtificialIntelligence #Security
The Future of Security and Privacy
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LLMs are all the rave - but scaling foundation models in a computationally and memory efficient manner is critical to enabling disruptive applications on consumer grade hardware.? Learn how Intel Labs researchers are tackling these challenges in this video with Somdeb Majumdar, Director of the AI Lab. https://intel.ly/3BZUY25 #LLMs #LCLMs #Innovation
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The Intel Rendering Toolkit libraries are now open for community contribution! With the internal development and feature branches now hosted directly on GitHub under Apache 2.0, they're fully open and always up to date. Along with improved features and functionality, we hope these changes bring increased development transparency and cross-platform CI for validation of contributors. You can see the full list of libraries here: https://intel.ly/3Aki8je #Graphics #Research #OpenSource
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While quantum computing holds promise for breakthroughs in drug discovery, materials design, and more, it also poses a threat to current cryptography. Classical public-key algorithms must be replaced by the National Institute of Standards and Technology (NIST) post-quantum cryptography (PQC) standards to stay secure. In support of this, Intel Labs research scientist Christoph Dobraunig, together with collaborators from industry and academia, developed the SLH-DSA (SPHINCS+) algorithm for digital signatures. Learn about this new standard and the role it plays in helping the industry prepare for the future. https://intel.ly/3NCa4gT #Research #CyberSecurity #QuantumComputing
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Tackle the key challenges in long-context model evaluation with HELMET (How to Evaluate Long-Context Models Effectively and Thoroughly). This comprehensive new benchmark, created in collaboration with Princeton Language and Intelligence, supports ≥128K token lengths across 7 diverse applications, offering more reliable and consistent rankings of frontier LCLMs. Get the code here. https://intel.ly/3YDt19v Minmin Hou, Ke Ding, Daniel Fleischer, Peter Izsak, Moshe Wasserblat, Howard Yen, Tianyu Gao, Danqi Chen #MachineLearning #NLP #LCLMs
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Through collaboration, anything is possible. Learn more about the innovative research happening with partners such as the National Science Foundation (NSF) and the Defense Defense Advanced Research Projects Agency (DARPA). Learn more: https://intel.ly/3YkSkgo #AI #CyberSecurity #HPC #Research