HPC-AI.COM Blog

Latest insights, updates, and stories on AI & compute.

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Interactively Boost Your Model Performance with Reinforcement Fine‑Tuning

In December of last year, at its product launch, OpenAI first introduced the concept of Reinforcement Fine‑Tuning (RFT), bringing policy‑optimization methods from reinforcement learning into the training of large‑scale language models. Unlike traditional Supervised Fine‑Tuning (SFT), which relies on vast amounts of labeled data, RFT uses reward functions or a verifier to score model outputs in real time and provide feedback, driving the model to iteratively refine its answers and strengthen its reasoning ability.

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NVIDIA B200 vs H200: When to choose which?

We’ve deployed NVIDIA Blackwell GPU servers on HPC-AI Cloud Platform with optimized AI-stacks for real-world AI projects. Start now to enjoy the performance gain!

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Explore 2:4 Semi-Structured Sparsity with 1.27x Inference Speedup on NVIDIA GPUs

At HPC-AI Research Team, we often explore ways to make deep learning models more efficient. One fundamental insight is that deep learning models are inherently sparse—many weights can be safely neglected and zeroed out without significant accuracy loss. This idea, known as model pruning, was first introduced by Yann LeCun in the 1980s through the pioneering work Optimal Brain Damage.

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OpenAI GPT-OSS 120B & 20B is Live on HPC-AI.COM!

OpenAI has launched gpt-oss-120b and gpt-oss-20b—powerful open-weight language models optimized for reasoning, tool use, and efficient deployment on consumer hardware. These models are released under the Apache 2.0 license, one of the most flexible open-source licenses available, so you can integrate and scale your projects freely.

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Building a PDF-Based RAG Workflow: Step-by-Step Guide

Although current pre-trained large language models (LLMs) have demonstrated strong generalizability across various tasks, they often underperform downstream natural language processing (NLP) tasks due to the lack of domain-specific knowledge. Retrieval-augmented generation (RAG) [1] emerges to address this challenge by retrieving relevant data from a knowledge base to augment the input prompts of LLMs, thereby enhancing their performance on specific tasks.

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How We Made Reinforcement Learning More Efficient with a New Method

Reinforcement Learning (RL) was originally developed for sequential decision-making tasks such as control systems and game strategies, where agents learn by interacting with their environment to maximize long-term rewards.Large Language Models (LLMs) have transformed natural language understanding and generation, yet they still struggle with complex reasoning and multi-step thought processes.

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🚀 New: RUNRL JOB Is Live on HPC-AI.COM

Reinforcement learning fine-tuning (RFT) is powerful — but let’s face it: it used to be a pain to run. Dual networks, huge memory needs, tons of config files... That’s why we built RUNRL JOB — the easiest way to run RFT workloads like GRPO directly on HPC-AI.COM. No complicated setup. Just pick your model, launch your job, and go.

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GRPO vs Other RL Algorithms: A Simple, Clear Guide

Reinforcement learning (RL) has transformed how we fine‑tune language models. Traditional approaches like Proximal Policy Optimization (PPO) and Trust Region Policy Optimization (TRPO) use a ‘critic’ value network—doubling model size, memory requirements, and complexity. Meanwhile, human‑alignment methods like Direct Preference Optimization (DPO) optimize for preference, not reasoning.

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Run Any AI Model in Second with HPC-AI.com

In 2025, open-source AI is exploding. Meta’s LLaMA 4, the latest in the LLaMA series, is setting new benchmarks for reasoning, multilingual fluency, and tool use. From chatbots to copilots, it's already powering the next wave of AI apps. However, running LLaMA 4 — or any large model at scale often requires time-consuming setup, infrastructure engineering, and DevOps.

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Train and Run Open-Sora 2.0 on HPC-AI.COM: State-of-the-Art Video Generation at a Fraction of the Cost

We're thrilled to introduce Open-Sora 2.0, a cutting-edge open-source video generation model trained with just $200,000 — delivering 11B parameter performance on par with leading closed-source models like HunyuanVideo and Step-Video (30B). And now, you can fine-tune or run inference with Open-Sora 2.0 instantly — on the HPC-AI.COM GPU cloud, with no contracts, global coverage, and prices starting at just $1.99/GPU hour.

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Shocking Release! DeepSeek 671B Fine-Tuning Guide Revealed—Unlock the Upgraded DeepSeek Suite with One Click

DeepSeek V3/R1 is a hit around the world, with solutions and API services based on the original model becoming widely available, leading to a race to the bottom in pricing and free offerings. How can we stand on the shoulders of the giant and leverage post-training with domain-specific data to build high-quality private models at low cost, enhancing business competitiveness and value?

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DeepSeek-R1 671B Deployment: How to Maximize Performance

DeepSeek-R1 is the most popular AI model nowadays, attracting global attention for its impressive reasoning capabilities. It is an open-source LLM featuring a full CoT (Chain-of-Thought) approach for human-like inference and an MoE design that enables dynamic resource allocation to optimize efficiency. It substantially outperforms other closed-source models in a wide range of tasks including coding, creative writing, and mathematics.

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Discover HPC-AI.COM at NeurIPS 2024 – Cutting-Edge GPUs, Demos, and More!

We’re thrilled to announce that HPC-AI.COM will be at NeurIPS 2024, and we can't wait to meet you at Booth 55! Whether you're a researcher, developer, or AI enthusiast, we have something exciting for everyone, including cutting-edge GPU solutions, exclusive promotions, and insightful demos.

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How to build a low-cost Sora-like app? Solutions for you

Recently, the free video generation platform Video Ocean went live, attracting widespread attention and praise. It supports generating videos with any character, in any style, from text, images, or roles. How did Video Ocean achieve rapid updates at low cost? What cutting-edge technologies are behind it?

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AWS and Google Fund Colossal-AI with Startup Cloud Programs

We are thrilled to announce that we have been selected for the AWS Activate and Google Startup Cloud Program, and have received support including cloud computing resources, AWS/Google Cloud Community, and co-marketing opportunities, etc. This recognition is a huge milestone for us, which will be invaluable to our continued growth and success.

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HPC-AI Tech Joins NVIDIA Inception

HPC-AI Tech today announced it has joined NVIDIA Inception, a program designed to nurture startups revolutionizing industries with technology advancements. HPC-AI Tech is focused on increasing AI productivity and building a world-class distributed AI development and deployment platform that enables supercomputers and cloud platforms to serve AI at a much lower cost.