Educational Codeforces Round 196 (Rated for Div. 2)
在线编程竞赛,比赛时长约 2 小时。所列时间为开赛时间,报名安排以官方页面为准。
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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
From Python and data basics to model applications, evaluation, and portfolio projects.
View skill map →From web fundamentals to modern frameworks, engineering, and shipping real products.
View skill map →From programming and databases to APIs, system design, and reliable services.
View skill map →From data handling and statistics to analysis, modeling, and business insight.
View skill map →Time-sensitive
Competitions and internships are the only dated items here — miss one and you wait for the next round. Undated ones stay open.
在线编程竞赛,比赛时长约 2 小时。所列时间为开赛时间,报名安排以官方页面为准。
Student role at Databricks in Belgrade, Serbia. Check the official listing for responsibilities and eligibility.
在线编程竞赛,比赛时长约 336 小时。所列时间为开赛时间,报名安排以官方页面为准。
Student role at Databricks in San Francisco, California; Seattle, Washington. Check the official listing for responsibilities and eligibility.
Official entry for a national student competition spanning software, visualization, AI, and digital media.
Student role at Scale AI in London, UK. Check the official listing for responsibilities and eligibility.
Official portal for the Ministry of Education interdisciplinary student innovation competition, whose projects may span multiple technical fields.
Student role at Scale AI in Doha, Qatar. Check the official listing for responsibilities and eligibility.
Join real collaboration
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…
Reporter: NHAM QUOC HUAN · NLP Labs Vietnam NLP Labs Vietnam builds a RAG-based solar PV advisory using LlamaIndex. Our pipeline ingests Vietnamese solar technical documents (PDFs, Word files from MOIT/EVN). We want to contribute a Vietnamese document processing example. 1. PDF font handling for Vietnamese diacritics…
Reporter: NHAM QUOC HUAN · NLP Labs Vietnam We ingest Vietnamese solar technical PDFs (MOIT/EVN) for our RAG advisory pipeline. Key insight: word-segmenting Vietnamese text before chunking improves retrieval precision by ~15% vs raw chunking. Also important: Vietnamese PDFs with tone marks require pypdf (not pdfminer)…
AI updates
We include updates that clarify a direction, tool choice, or learning priority—not hype without an actionable takeaway.
Google DeepMind and UK government work together to reduce planning assessment times
Genie 4: our new world model unlocking unprecedented realism in real-time simulation.
The torch-neuronx model support Space answers that question for the most popular models on the Hub. It tells you whether a model runs unmodified on Trainium, and gives you the script to run it yourself.
Just over a week ago, we released Granite Switch 4.1 , showing that our modular Switch architecture lets you configure a language model with specialized, cache-efficient adapters — adding new expertise on a single endpoint.