Congrats to JQI Fellow, UMD Adjunct Professor, and Amazon Scholar Alexey Gorshkov, who supports our team at the AWS Center for Quantum Computing, for being honored with the IEEE Photonics Society Quantum Electronics Award for his research contributions in the areas of understanding, designing, and controlling interacting quantum systems. Learn more about the award: amzn.to/3z6UaHw Amazon Web Services (AWS), UMIACS, National Institute of Standards and Technology (NIST), Joint Quantum Institute #QuantumComputing #AWS
Amazon Science
Research Services
Seattle, Washington 357,770 followers
The latest news and research from Amazon’s science community. #AmazonScience
About us
Amazon Science gives you insight into the company’s approach to customer-obsessed scientific innovation. Amazon fundamentally believes that scientific innovation is essential to being the most customer-centric company in the world. It’s the company’s ability to have an impact at scale that allows us to attract some of the brightest minds in artificial intelligence and related fields. Our scientists continue to publish, teach, and engage with the academic community, in addition to utilizing our working backwards method to enrich the way we live and work. Follow us on LinkedIn and visit our website to get a deep dive on innovation at Amazon, and explore the many ways you can engage with our scientific community. #AmazonScience
- Website
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https://www.amazon.science
External link for Amazon Science
- Industry
- Research Services
- Company size
- 10,001+ employees
- Headquarters
- Seattle, Washington
- Founded
- 2020
- Specialties
- Artificial Intelligence, Machine Learning, Computer Vision, Cloud, Economics, Sustainability, AI, ML, Conversational AI, Natural Language Processing, NLP, Robotics, Security, Privacy, Information, Knowledge Management, Operations, Scientific Research, Search, Amazon, and Alexa
Updates
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The approach utilizes modality-specific encoders and task-specific decoders to create a shared diffusion space. In experiments, Amazon researchers demonstrate improved performance compared to single-purpose models, highlighting the potential of multimodal and multitask training in diffusion models. #ComputerVision #GenerativeAI
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Amazon Science reposted this
🚀 Claude 3.5 Sonnet, Anthropic’s newest and most intelligent model is available to customers today on Amazon Bedrock: https://lnkd.in/gSdBKk8s This model leads the frontier of general intelligence—it is awesome at completing complex tasks, context-sensitive customer support, orchestrating multi-step workflows, streamlining code translations, and creating revenue-generating user-facing applications. Other Claude 3.5 Sonnet strengths include: 📊 Data science & analysis: Enhancing human expertise in data science by navigating unstructured data, and leveraging multiple user provided tools to generate insights. When given access to a coding environment, it produces high-quality statistical visualizations and actionable predictions, ranging from business strategies to real-time product trends. 🔍 Vision capabilities: Processing images, particularly when interpreting charts and graphs that require visual understanding. It can accurately transcribe text from imperfect images—a core capability for industries such as retail, logistics, healthcare, and financial services, where AI may be able to garner more insights from an image, graphic or illustration than from text alone, for use cases like trend analysis, patient triage, and research summaries. Claude 3.5 Sonnet outperforms Anthropic’s previously most capable model, Claude 3 Opus, at one-fifth the cost. Already, AWS customers across industries—from DoorDash to WPP to Swindon Borough Council—are enjoying the speed they can test, build, and deploy GenAI applications on Bedrock with Anthropic’s Claude models. See what you can build with us on #AWS ⬆️ (link above).
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At this week’s CVPR, Swami Sivasubramanian, VP of AI and Data at Amazon Web Services (AWS), will present a keynote on ‘Computer vision at scale: Driving customer innovation and industry adoption’, where he will share his insights on how the company is leveraging AI and data to solve urgent needs through the newest Amazon engines, managed services, and applications. Find our team at booth 1525 to see demos, learn more about our research, and discuss career opportunities: amzn.to/3xlCg3a #CVPR2024
Amazon Science at CVPR 2024
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Thank you to everyone who visited our booth at SIGMOD last week. Learn more about the papers Amazon researchers presented and our career opportunities here: amzn.to/45soSGV
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Retrieval-augmented generation (RAG) is a leading way to curb "hallucination" in large language models. At this year's ICML, Amazon researchers will show how to leverage item response theory to automatically generate "exams" for evaluating RAG approaches. #ICML2024 #LLMs #ConversationalAI
Automated evaluation of RAG pipelines with exam generation
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At this year's CVPR, Amazon's 20+ papers deal with vision-language models, visual question answering, hallucination mitigation, retrieval-aided generation, and more. Explore the full list: amzn.to/3VhrR0i #CVPR2024 #ComputerVision
A quick guide to Amazon's papers at CVPR 2024
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Amazon researchers' papers at NAACL predominately focus on LLMs. This paper guide sorts them by those that deal explicitly with LLMs or not, although in many cases, the ones that don’t present general techniques or datasets that could be used with either LLMs or more-traditional models. #NAACL2024 #LLMs
A quick guide to Amazon's 30+ papers at NAACL 2024
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We're proud to be a diamond sponsor of this year's ACM SIGMOD/PODS conference, taking place this week in Santiago, Chile. Explore the list of papers below, and read them on our website: amzn.to/3Vh0HXi • Amazon MemoryDB: A fast and durable memory-first cloud database • Automated multidimensional data layouts in Amazon Redshift • COSMO: A large-scale e-commerce common sense knowledge generation and serving system at Amazon • Intelligent scaling in Amazon Redshift • Predicate caching: Query-driven secondary indexing for cloud data warehouses • Stage: Query execution time prediction in Amazon Redshift #SIGMOD2024 #AmazonScience #CloudComputing
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In our latest newsletter we cover Amazon's open-source model for time series forecasting, a new knowledge graph framework that uses #LLMs to discern commonsense relationships, research collaborations with UW and Columbia, new features for Amazon Bedrock, and more.
May 2024
Amazon Science on LinkedIn