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
🧵
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
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.
Congratulations to the Amazon researchers who have been honored for their contributions to the scientific community in 2023. #AmazonScience https://t.co/x17RkFRJnh
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 the year comes to a close, we’ve highlighted some of the recent honors and awards Amazon researchers have received for their contributions to the scientific community. Learn more about their recognitions and role at the company in our roundup. #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
#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
@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
We're proud to be a platinum sponsor of this year's @ieee_slt, taking place this week in Doha, Qatar. Learn more about our presence at the conference, including our organizing committee and accepted publications. #AmazonScience
At our London and Cambridge offices, Amazon scientists are working across research areas such as image quality, algorithm design, robotics and depth sensing, and photogrammetry. Learn more about the location, and our available career opportunities in the UK. 🇬🇧 #AmazonScience
Subscribe to our monthly newsletter today and get an in-depth look at the groundbreaking research and applied science being conducted at Amazon, including the scientists and scholars doing that work, and much more! #AmazonScience https://t.co/SINixFFIEa
🔎 Are Toxicity Predictors robust toward adversarial attacks?
📚 Check out this paper from #AmazonScience that proposes a suite of ToxicTrap attacks to identify weaknesses in state-of-the-art toxicity language predictors that could potentially be exploited by attackers. 💥
The study also evaluates the effectiveness of adversarial training in improving the model's robustness against both seen and unseen attacks. 🛡️
Link: https://t.co/35GBLPUOZs
😄Enjoying the great vibes at #ICML2023! Epic to meet all the Amazonians here and connect with the #AmazonScience crew. 🤙
Interested in making Amazon Echo more intuitive? We're hiring a senior science lead to mentor our SpeakerID teams, and help our scientists make Alexa personalized to each of our customers. Apply here: https://t.co/qPJwQ62fcL #AmazonScience #SciComm
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
The team around @alves_eg measured #isoprene emissions at ATTO to better understand how these emissions vary seasonally, under extreme climatic conditions & which factors regulate them. #AmazonScience
📑Summary: https://t.co/stUIyHW0BJ
📚Paper: https://t.co/Pmvj3YgSnN
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