Top Tweets for #Amazonscience
Evaluating agents with agents. The DREAM framework tackles one of the trickiest meta-problems in deep research right now. Check this out 👇 #AmazonScience
Excited to share our latest work—DREAM: Deep Research Evaluation with Agentic Metrics
TL;DR: How do you reliably evaluate Deep Research Agents (DRAs)? With another agent. We introduce a framework that makes evaluation itself agentic.
Preprint: https://t.co/ybNPAYu2fz
🧵
Excited to be at #NeurIPS2025 in San Diego this week!
Our Applied AI team @ Amazon is hiring Applied Scientist Interns for Spring/Summer.
Stop by the Amazon Science booth on Dec 3 to chat about Agentic AI — or DM to connect!
#AgenticAI #AmazonScience
Very excited to share our work on "Science in the Age of Foundation Models", where we discuss applications of foundation models in time series forecasting and PDEs including weather forecasting and aerodynamics.
#sciml #pdes #cfd #amazonscience
Foundation models show promise for scientific computing, but adoption lags behind language and vision applications. Amazon researchers reveal what’s needed: physical-constraint satisfaction, uncertainty quantification, and specialized forecasting techniques.
@CVUTPraha je mezi 10 univerzitami, které se účastní prestižní výzvy Amazon Nova AI Challenge. Tým AlquistCoder tvoří vědci, vědkyně a studenti z @CVUTFEL a @CIIRCCTU. Držíme palce!
👀https://t.co/zB9mI7JvGX
📸Amazon Nova AI Challenge
#AmazonScience
My latest blog on improving code LLMs’ ability to debug and generate accurate code. https://t.co/rd2vaffk4y #neurips2024 #amazonscience https://t.co/GlObKOxPvz
Ideally, using LLMs for code generation also means using them to debug the generated code. Specializing LLMs for debugging using synthetic training data and both fine tuning and reinforcement learning improves the success rate of code generation by 39%. https://t.co/yoWo09ATFI #LLMs
Our most-viewed papers of 2024 span cloud databases, anomaly detection on graphs, recession prediction, and Amazon's Nova foundation models. Explore the most popular publications authored by Amazon scientists and collaborators from the year: https://t.co/IDpZievZgE #AmazonScience
As 2024 comes to a close, we've rounded up our 10 most-viewed blog posts. Explore the scientific advances that shaped our year including large language models, cryptography, automated reasoning, and more: https://t.co/YVYcFvcVeI #AmazonScience
We're at @kdd_news! Find the Amazon team at booth 19 to hear from our scientists and learn about career opportunities, and visit our website to view accepted publications and workshops: https://t.co/19QEyczGeB #KDD2024 #AmazonScience
Next week we're in Washington, D.C. for the 47th International @SIGIRConf on Research and Development in Information Retrieval. Learn more about Amazon's accepted publications and workshops below. #SIGIR2024 #AmazonScience https://t.co/aHyK7XQPt2
🌟Excited to announce that I will be joining the Amazon Q team as a research intern. Starting this July, I’ll be working on a research about LLM applications for real-world business. Since I’m now in New York City🗽🇺🇸, feel free to reach out for a coffee chat!
#AmazonScience
Just attempted the test for Amazon ML Summer School 2024 and I'm feeling confident! 🎉
Excited about the chance to learn from @Amazon Scientists and dive deep into the world of ML.
Who else took the test today?
#MachineLearning #ML #AmazonScience #STEMEducation #AWS
Come see the work of our summer intern @oriolbarbany on multimodal search with large language models at poster 202. Presented by Michael Huang and Arnab Dhua at #CVPR2024 Fine-grained Visual Categorization workshop. #AmazonScience
A massive thanks to my colleagues at AWS AI (including Amy!) who helped the paper come together.
You can learn more about the paper on the #AmazonScience website: https://t.co/E7UWQuucPT
Human annotation can be costly, tedious, and time-consuming. I'm excited to share our forthcoming #IUI2024 paper on 🫰Snapper 🫰, an AI-assisted annotation tool for facilitating lazy annotation in object detection tasks.
#Annotation #ComputerVision #AmazonScience
🆕 Sharing two multimodal models: CaMML-7B and CaMML-13B, which achieve state-of-the-art performance across various multimodal benchmarks, outperforming llava-v1.5 without using additional training data.
Paper: https://t.co/LKMWF7oS9Q
Code/checkpoints coming soon.
Congratulations to the Amazon researchers who have been honored for their contributions to the scientific community in 2023. #AmazonScience https://t.co/x17RkFRJnh
Congrats to Mihalis Yannakakis and Christos Papadimitriou, both of whom received funding from Amazon��s Automated Reasoning group and the Amazon - Columbia Center of AI Technology, respectively. #AmazonScience
Congratulations to @ColumbiaCompSci faculty Christos Papadimitriou and Mihalis Yannakakis for recieving the John von Neumann Theory Prize for their research in computational complexity theory, which explores the boundaries of efficiently solving decision & optimization problems crucial to operations research and management sciences.
read more: https://t.co/JKf85cKw3W
Had a great time in Brazil 🇧🇷 for this year's sampling campaigns and for the #ATTO workshop in Manaus. Many thanks to @ATTOresearch and the @MPI_BGC for making it all possible!
🌳🗼🌳
#IMPRSabroad
#rainforestmicrobiology
#soilmicrobiology
#amazonresearch
#amazonscience
#AmazonScience blog post: Making deep learning practical for Earth system forecasting with Earthformer
Blog: https://t.co/bq7SCH1mev
Python package: https://t.co/RCo0pxrt2Q
#python #deeplearing #geospatial
New methods from @awscloud researchers promise better Earth-system forecasting: “cuboid attention” makes transformers practical for complex Earth system data, and diffusion models enable probabilistic prediction and conformity to prior-knowledge constraints. #MachineLearning
Congratulations to the following Amazon researchers who have been recently recognized for their contributions, innovations, and leadership to the scientific research community: Rahul Urgaonkar, @YizhouSun, @PooyanAA, @apotam, and Alexandre Belloni. #AmazonScience
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