Codeforces Round 1122 (Div. 3)
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Trusted aggregation · Built for university students
Explore open-source projects, competitions, internships, and AI updates with traceable sources. Then turn them into a path that fits your foundation, devices, time, and budget.
Sample path
Generated live from the verified catalog for a second-year beginner with 4 hours a week, no budget, AI track. Your own conditions produce a different path.
Week 1 · Prepare
Read the verified entry “Hugging Face Datasets”, list its prerequisites, and write down three terms to clarify.
Week 2 · Practice
Use “Hugging Face Datasets” to complete one smallest reproducible exercise and record every step.
Week 3 · Practice
Change one variable or implementation detail in the previous “Hugging Face Datasets” exercise, compare the result, and explain the difference.
Week 4 · Act
Choose one realistically scoped issue in “Hugging Face Datasets”, reproduce it, and prepare or submit one minimal contribution.
Week 5 · Deliver
Turn the work based on “Hugging Face Datasets” into one shareable result with a short README or application note.
Week 6 · Review
Review the evidence from “Hugging Face Datasets”, note one obstacle, one improvement, and the next concrete action.
Start with a direction
Time-sensitive
Competitions and internships are the only dated items here — miss one and you wait for the next round. Undated ones stay open.
Join real collaboration
AI updates
We include updates that clarify a direction, tool choice, or learning priority—not hype without an actionable takeaway.
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A four-to-six-month on-site research internship in Okinawa for late-stage bachelor’s students, master’s students, and recent graduates worldwide, with no required IELTS or TOEFL score.
在线编程竞赛,比赛时长约 2 小时。开始后不能再报名。
A worldwide computer-science research internship for bachelor’s, master’s, and doctoral students, with projects matched across AI, data, systems, and software research.
A free global 24-hour student datathon using IBM Z and LinuxONE for real-time AI, privacy-preserving AI, open innovation, and AI-for-good prototypes.
Student role at Scale AI in London, UK. Check the official listing for responsibilities and eligibility.
A global student challenge for runnable AI applications, developer tools, or verifiable contributions built with open-source software, models, and data.
Student role at Scale AI in Doha, Qatar. Check the official listing for responsibilities and eligibility.
2.9.1 We are experiencing an issue with Stackdriver Logging with Airflow. As changelog suggests, with Airflow 2.9.1 version Google provider is updated to 10.17.0 and solves the bugs with Stackdriver logging. We tested with the latest version. However, we cannot configure remote logging with Stackdriver. As an initial…
3.0.3 After upgrading Airflow from version 3.0.2 to 3.0.3 sensitive data in extra fields and extra fields JSON is visible in edit connection page. Sensitive data should be masked with Enter Edit Connection window in Airflow UI. Ubuntu 24.04 Other Docker-based deployment Airflow deployed with Docker Swarm. Settings in…
This issue is for keeping track of the recurrent Whisper asks as well as the linked on-going efforts to support that feature, if any. When a feature request has no linked PR, feel free to claim the work here if you want to help! - Related issues: https://github.com/vllm-project/vllm/issues/19556, https://github.com/vl…
These enhancements are to have a better UX when using foreach_map, suggested in a few places, but most recently, https://github.com/pytorch/pytorch/issues/158371#issuecomment-3088757068 These enhancements should allow easier compiler-first custom optimizer implementations. cc @chauhang @penguinwu @voznesenskym @EikanW…
OpenAI and GSA will offer eligible federal, state, local, and tribal governments $0 license fees, 50% off usage, and expanded cyber defense support.
Chris Lehane argues that stronger AI capabilities require stronger safety evidence, shared standards, and durable policy action while the policy window remains open.
That is embarrassing onstage. In production, it is a reliability problem: a workflow that succeeded once may fail the next time a user makes the same request. For mission-critical work, such as reconciling a financial transaction or checking a contract for an obligation, that can be a showstopper.
Structured output is one of the most common real-world tasks for LLMs, yet most benchmarks fold it into broader reasoning or extraction scores rather than measuring it on its own. Whether a model reliably returns valid, parseable output in the requested format and shape — schema compliance — is often what decides whet…