Codeforces Integrations

Gmail is an AI-powered email platform designed to help individuals and businesses communicate securely, efficiently, and professionally. The platform includes intelligent features such as Gemini AI assistance, Smart Compose, Smart Reply, and automated Nudges that help users draft messages, respond faster, and stay organized. Gmail integrates seamlessly with Google Workspace applications including Google Meet, Calendar, Chat, and Tasks, allowing users to manage communication and collaboration from one centralized interface. Businesses can create custom email addresses using their own domain names, helping organizations establish a more professional and trustworthy brand presence. The platform is backed by enterprise-grade security with advanced spam filtering, phishing protection, malware detection, encryption, and compliance-focused infrastructure. Accessible across desktops, smartphones, tablets, and smartwatches, Gmail helps users stay connected and productive from anywhere.

CodeQwen is the code version of Qwen, the large language model series developed by the Qwen team, Alibaba Cloud. It is a transformer-based decoder-only language model pre-trained on a large amount of data of codes. Strong code generation capabilities and competitive performance across a series of benchmarks. Supporting long context understanding and generation with the context length of 64K tokens. CodeQwen supports 92 coding languages and provides excellent performance in text-to-SQL, bug fixes, etc. You can just write several lines of code with transformers to chat with CodeQwen. Essentially, we build the tokenizer and the model from pre-trained methods, and we use the generate method to perform chatting with the help of the chat template provided by the tokenizer. We apply the ChatML template for chat models following our previous practice. The model completes the code snippets according to the given prompts, without any additional formatting.

Creating solutions to unforeseen problems is second nature in human intelligence, a result of critical thinking informed by experience. The machine learning community has made tremendous progress in generating and understanding textual data, but advances in problem-solving remain limited to relatively simple maths and programming problems, or else retrieving and copying existing solutions. As part of DeepMind’s mission to solve intelligence, we created a system called AlphaCode that writes computer programs at a competitive level. AlphaCode achieved an estimated rank within the top 54% of participants in programming competitions by solving new problems that require a combination of critical thinking, logic, algorithms, coding, and natural language understanding. AlphaCode uses transformer-based language models to generate code at an unprecedented scale, and then smartly filters to a small set of promising programs.