Recently, an advanced hybrid inference model, Qwen 3 235B, was officially launched on the Together Chat platform. Developed by AliCloud, the model has performed excellently in multiple benchmarks and has met or exceeded the performance of the top big models in the market today, such as DeepSeek-R1, o1, o3-mini, Grok-3 and Gemini-2.5.
The Qwen 3 235B demonstrates strong reasoning capabilities when handling complex tasks, and is capable of processing and analyzing multimodal data for a wide range of application scenarios including, but not limited to, natural language processing, image recognition and generation, and speech synthesis. In addition, it has excellent dialog comprehension and generation capabilities, making it ideal for enterprise-level applications.
Key Features:
- Leading edge reasoning
- Multimodal data processing
- Wide range of application scenarios
By introducing Qwen 3 235B, Together Chat will provide a more efficient and smarter service experience for users.
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The team recently released the Advanced Edge Healthcare Model, one of the most advanced open source healthcare models available. The model is trained by reinforcement learning with carefully selected data and DAPO (Data Augmented Policy Optimization) and is designed to provide personalized healthcare to users.
This breakthrough will not only improve the healthcare industry, but will also have far-reaching implications in a variety of fields, including education, government, and finance. As technology continues to advance, it is expected that this model will be rapidly iterated, ultimately making open and high-quality healthcare available to everyone.
future plans
- A detailed whitepaper will be released soon and waiting list registration is now open.
- The II-Medical-7B-Preview model is now online, marking a major milestone for the Smart Internet.
We look forward to the rapid diffusion of this innovative technology to realize the vision of open healthcare on a global scale.
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Building a robust multilingual multimodal retrieval augmentation generation (RAG) system capable of handling multiple languages and modalities.
By using LlamaIndex and @qdrant_engine, you can achieve the following:
- **Multi-language support**: Ingestion and retrieval of documents in English, Spanish, Chinese, as well as domain-specific documents.
- **multimodal processing**: Seamlessly process and search text and images.
- **high performance**: Enables rapid response and reduces user waiting time.
Key components of the system include:
- **LlamaIndex**: Provide flexible agent-based workflows.
- **@qdrant_engine**: for high performance vector storage.
- **@langfuse**: Provide observability and analytical capability.
This multilingual and multimodal RAG system has a wide range of applications in several fields, such as cross-language information retrieval, multimodal content generation and intelligent customer service. By integrating these advanced technological tools, organizations can dramatically improve their information processing and generation capabilities to provide more efficient and accurate services to users.
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Meta Chief Product Officer Chris Cox opened LlamaCon 2025 by reflecting on the company's long history of contributions to open source.
Cox said, "We're built on open source ......", a statement that not only summarizes Meta's evolution, but also emphasizes the centrality of open source technology in its ecosystem. Open source technology allows Meta to rapidly develop and iterate on its products and services, such as social platforms like Facebook and Instagram.
open source technologyThe strength of Meta is its transparency and community support, which allows developers around the world to work together to improve and innovate. Through open source projects, Meta not only enhances its own technological prowess, but also promotes the progress of the industry as a whole.
LlamaCon 2025 brings together developers and technologists from around the world to discuss future technology trends and best practices for open source projects. The conference is not only a platform for technical exchanges, but also an important opportunity to showcase Meta's continued dedication and commitment to open source.
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latest versionDeepSeek Prover V2Now available directly on the model page byNovita LabsProviding support. This update marks another significant advancement of open source technology in the field of artificial intelligence.
With this update, users can more easily access and use this powerful verification tool to improve development efficiency and verification accuracy.DeepSeek Prover V2 not only provides richer functionality, but also enhances its ability to be used in complex models.
- Multiple programming languages are supported, including Python, Java and C++.
- Efficient data processing and analytical skills.
- Integrate advanced machine learning algorithms to improve the accuracy of model validation.
In addition, community feedback shows that the tool performs particularly well in real-world projects, especially in demanding fields such as finance, healthcare, and autonomous driving, greatly improving the reliability and safety of the models.
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GitHub has officially announced that its Copilot feature now supports large windows of 200,000 Token, marking a significant improvement in code generation capabilities.
This update introduces OpenAI's o3 and o4-mini models, and these new models are in public beta in GitHub Copilot and GitHub Models. Users can experience these new features by visiting the GitHub Copilot page.
Key Highlights:
- A window of 200,000 Tokens dramatically extends the code's processing power.
- Introducing OpenAI's o3 and o4-mini models.
- Currently in public beta, developers are welcome to try it out and provide feedback.
This update not only improves the quality of code automation, but also provides developers with more flexibility and creativity. Whether it's a large project or a complex task, the new Token window and model will lead to a more efficient and smarter programming experience.
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Recently, DeepSeek released its latest Prover-V2 model, which has 671 billion parameters and is based on DeepSeekMath-Base for reinforcement training, optimized specifically for mathematical theorem proving tasks.
Prover-V2 not only solves complex mathematical problems, but also automatically generates complete mathematical proofs, which greatly improves the efficiency and accuracy of mathematical research.
In traditional mathematical research, the validation of the correctness of theorems is highly dependent on manual logical reasoning, and formal proofs, although they can improve mathematical rigor, are inefficiently written by hand and have a high threshold. In addition, existing AI models, although capable of generating answers, lack verifiable logical deduction.
DeepSeek-Prover-V2 aims to address these pain points:
- Building a system based on logic rules, language modeling and search strategies
- Automatically gives "verifiable" mathematical proof of process
- Reducing manual workload and increasing research efficiency in math research
This breakthrough is expected to be widely used in the fields of mathematics education and research, and to propel mathematics research into a new phase.
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Attention New York area professionals! Our co-founder and CEO @jerryjliu0 will lead a workshop on building intelligent solutions for financial applications.
In this workshop, you will have the opportunity to learn directly from industry experts:
- How to Apply Artificial Intelligence to Financial Challenges and Solve Complex Data Processing Problems
- Use the LlamaParse tool to process complex documents containing charts and tables to improve the accuracy and efficiency of data extraction
- Utilizing RAG (Retrieval-Augmented Generation) technology to process large amounts of financial data and enhance data analysis capabilities
- Explore and implement smart strategies to improve accuracy, gain insight, and optimize the decision-making process
Space is limited, so please register as soon as possible: https://t.co/tWgTUUoW7j
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Qwen recently announced its latest Qwen Omni 3B end-to-end speech-to-speech conversion model. This innovative technology marks an important breakthrough in speech processing.
The Qwen Omni 3B model utilizes an advanced deep learning architecture that is capable of directly converting input speech into speech output in the target language without the need for an intermediate text transcription step. This not only improves processing efficiency, but also significantly improves the quality of the conversion, resulting in a more natural and smooth output.
Key features include:
- High-precision speech recognition and synthesis
- Multi-language support
- Low-latency real-time processing
The model performs well in several real-world application scenarios, such as cross-language conferencing, online education, virtual assistants, etc. The release of Qwen Omni 3B provides users with a more efficient and convenient speech processing solution.
As artificial intelligence technology continues to advance, the Qwen Omni 3B is expected to further drive technological innovation and development in the field of speech processing in the future.
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Scalable and Performant Data Loading (SPDL) is an open-source and framework-agnostic library designed for efficiently loading arrays of data to the GPU. In the field of deep learning and high performance computing, data loading is one of the key steps that directly affects the speed of model training and inference.
Based on the benchmarking results, theSPDL741 TP3T faster than PyTorch DataLoader while processing ImageNet datasets with 381 TP3T less CPU usage and 50 GB lower memory footprint.This makes SPDL ideal for large-scale data processing and high-performance computing scenarios.
- **Open source nature**: the community can participate in improvements and optimizations.
- **Framework-agnostic**: supports multiple deep learning frameworks such as TensorFlow, PyTorch, etc.
- **EFFICIENCY**: Significantly faster data loading and reduced resource consumption.
For researchers and developers who need to work quickly with large-scale datasets, theSPDLIt is a very valuable tool.
