Latest news with #AmericanInvitationalMathematicsExamination
South China Morning Post
25-03-2025
- Business
- South China Morning Post
DeepSeek's upgraded foundational model excels in coding and maths
Chinese artificial intelligence (AI) star DeepSeek has upgraded its open-source V3 large language model by adding parameters and improving capabilities in coding and solving mathematical problems. Advertisement The DeepSeek-V3-0324, named after its predecessor and the launch date, has 'enhanced reasoning capabilities, optimised front-end web development and upgraded Chinese writing proficiency', according to a notice on the company's website. The new version and DeepSeek V3 are both foundation models trained on vast data sets that can be applied in different use cases, including that of a chatbot. DeepSeek R1, the reasoning model, is based on DeepSeek V3. The updated foundation model has made improvements in several benchmarks, especially the American Invitational Mathematics Examination (AIME), where it scored 59.4 compared with 39.6 for its predecessor, while achieving an increase of 10 points on LiveCodeBench to achieve 49.2, DeepSeek data showed. This illustration photograph taken on January 29, 2025 shows screens displaying the logos of DeepSeek and OpenAI's AI chatbot ChatGPT. Photo: AFP Compared with DeepSeek V3, which has 671 billion parameters and adopts the company's own commercial license, the new 685-billion-parameter model uses the MIT software licence that is the most popular on developer platform GitHub. Advertisement Launched on AI community Hugging Face as well as the company's own website, DeepSeek-V3-0324 is now the top trending model on Hugging Face, receiving positive comments on its performance.
South China Morning Post
21-03-2025
- Business
- South China Morning Post
ByteDance advances DeepSeek work in AI reasoning with open-source project led by intern
TikTok owner ByteDance, which has invested heavily in artificial intelligence (AI), has unveiled a new system that claims to improve on the work done by DeepSeek in training AI reasoning models. Advertisement DAPO, or Decoupled Clip and Dynamic Sampling Policy Optimisation, is a scalable reinforcement learning algorithm that helps a large language model (LLM) achieve better complex reasoning behaviour such as self-verification and iterative refinement, according to a research paper published earlier this week by ByteDance and Tsinghua University's Institute for AI Industry Research. The algorithm outperformed the reinforcement learning approach in DeepSeek's R1 reasoning model, scoring 50 points in the American Invitational Mathematics Examination (AIME) 2024 using Alibaba Group Holding's Qwen2.5-32B base model, compared with 47 points attained by R1 when applying the same Alibaba model, the paper showed. Alibaba owns the South China Morning Post. Notably, DAPO achieved the better result with 50 per cent fewer training steps. TikTok owner ByteDance has invested heavily in artificial intelligence. Photo: Digitimes The achievement drew positive academic and industry comments. Google DeepMind engineer Philipp Schmid, who shared the project on X, said the new method was 'better than' DeepSeek's 'group relative policy optimisation (GRPO)' in reinforcement learning. GRPO is one of DeepSeek's training methods that enables a model to learn by comparing different actions and making updates with a 'group' of observations.
