Samsung Electronics today announced it has entered into a strategic partnership with Mistral AI to enhance its semiconductor engineering and manufacturing capabilities that will reinforce its leadership in AI chip technologies. The announcement of the partnership was made during the state summit held in Paris between South Korea and France. Under the agreement, Samsung will integrate Mistral's AI services and solutions—including its flagship large language model, Mistral Large—across its semiconductor operations to develop customized on-premises AI models optimized for intelligence-driven infrastructure.

Mistral's powerful AI platform is expected to provide Samsung with a unique stack of tools that will transform how semiconductors are designed and manufactured. The on-premises enterprise solutions will especially ensure security and flexibility required to process highly sensitive technologies and operational data entirely within the boundaries of Samsung's semiconductor infrastructure, maintaining total control over its mission-critical technologies.

A look under the hood of virtually any frontier model today will reveal a mixture-of-experts (MoE) model architecture that mimics the efficiency of the human brain. Just as the brain activates specific regions based on the task, MoE models divide work among specialized "experts," activating only the relevant ones for every AI token. This results in faster, more efficient token generation without a proportional increase in compute. The industry has already recognized this advantage. On the independent Artificial Analysis (AA) leaderboard, the top 10 most intelligent open-source models use an MoE architecture, including DeepSeek AI's DeepSeek-R1, Moonshot AI's Kimi K2 Thinking, OpenAI's gpt-oss-120B and Mistral AI's Mistral Large 3.

However, scaling MoE models in production while delivering high performance is notoriously difficult. The extreme codesign of NVIDIA GB200 NVL72 systems combines hardware and software optimizations for maximum performance and efficiency, making it practical and straightforward to scale MoE models. The Kimi K2 Thinking MoE model—ranked as the most intelligent open-source model on the AA leaderboard—sees a 10x performance leap on the NVIDIA GB200 NVL72 rack-scale system compared with NVIDIA HGX H200. Building on the performance delivered for the DeepSeek-R1 and Mistral Large 3 MoE models, this breakthrough underscores how MoE is becoming the architecture of choice for frontier models—and why NVIDIA's full-stack inference platform is the key to unlocking its full potential.

Yesterday, Mistral AI announced the Mistral 3 family of open-source multilingual, multimodal models, optimized across NVIDIA supercomputing and edge platforms. Mistral Large 3 is a mixture-of-experts (MoE) model—instead of firing up every neuron for every token, it only activates the parts of the model with the most impact. The result is efficiency that delivers scale without waste, accuracy without compromise and makes enterprise AI not just possible, but practical. Mistral AI's new models deliver industry-leading accuracy and efficiency for enterprise AI. It will be available everywhere, from the cloud to the data center to the edge, starting Tuesday, Dec. 2.

With 41B active parameters, 675B total parameters and a large 256K context window, Mistral Large 3 delivers scalability, efficiency and adaptability for enterprise AI workloads. By combining NVIDIA GB200 NVL72 systems and Mistral AI's MoE architecture, enterprises can efficiently deploy and scale massive AI models, benefiting from advanced parallelism and hardware optimizations. This combination makes the announcement a step toward the era of—what Mistral AI calls 'distributed intelligence,' bridging the gap between research breakthroughs and real-world applications.

Today, leading semiconductor equipment manufacturer ASML Holding NV (ASML) and France-based AI leader Mistral AI announced a strategic partnership based on a long-term collaboration agreement to explore the use of AI models across ASML's product portfolio as well as research, development and operations, to benefit ASML customers with faster time to market and higher performance holistic lithography systems. In addition, ASML is investing 1.3 billion EUR in Mistral AI's Series C funding round as lead investor, in order to support its development and reinforce the long-term partnership benefits. This results in ASML holding an approximately 11 percent share on a fully diluted basis in Mistral AI.

"The collaboration between Mistral AI and ASML aims to generate clear benefits for ASML customers through innovative products and solutions enabled by AI, and will offer potential for joint research to address future opportunities," said ASML President and Chief Executive Officer Christophe Fouquet. "We believe that this strategic partnership with Mistral AI, which goes beyond a traditional vendor-client relationship, is the best way to capture this significant opportunity. We also believe that this collaboration is value enhancing to Mistral AI."

CoreWeave today became one of the first cloud providers to bring NVIDIA GB200 NVL72 systems online for customers at scale, and AI frontier companies Cohere, IBM and Mistral AI are already using them to train and deploy next-generation AI models and applications. CoreWeave, the first cloud provider to make NVIDIA Grace Blackwell generally available, has already shown incredible results in MLPerf benchmarks with NVIDIA GB200 NVL72 - a powerful rack-scale accelerated computing platform designed for reasoning and AI agents. Now, CoreWeave customers are gaining access to thousands of NVIDIA Blackwell GPUs.

"We work closely with NVIDIA to quickly deliver to customers the latest and most powerful solutions for training AI models and serving inference," said Mike Intrator, CEO of CoreWeave. "With new Grace Blackwell rack-scale systems in hand, many of our customers will be the first to see the benefits and performance of AI innovators operating at scale."

Intel has announced the release of an updated version of its AI Playground application, now optimized for the new Intel Core Ultra 200V "Lunar Lake" series of processors. This latest iteration, version 1.21b, brings a host of new features and improvements designed to make AI more accessible to users of Intel's AI-enabled PCs. AI Playground, first launched earlier this year, offers a user-friendly interface for various AI functions, including image generation, enhancement, and natural language processing. The new version introduces several key enhancements. These include a fresh, exclusive theme for 200V series processor users, an expanded LLM picker now featuring Phi3, Qwen2, and Mistral models, and a conversation manager for saving and revisiting chat discussions. Additionally, users will find adjustable font sizes for improved readability and a simplified aspect ratio tool for image creation and enhancement.

One of the most significant aspects of AI Playground is its ability to run entirely locally on the user's machine. This approach ensures that all computations, prompts, and outputs remain on the device, addressing privacy concerns often associated with cloud-based AI services. The application is optimized to take advantage of the Xe Cores and XMX AI engines found in the Intel Core Ultra 200V series processors, allowing even lightweight devices to perform complex AI tasks efficiently. Intel has also improved the installation process, addressing potential conflicts and providing better error handling. The company encourages user engagement through its Intel Insiders Discord channel, helping the community around AI Playground's development and use. Although the models users can run locally are smaller in size, usually up to 7 billion parameters with 8/4-bit quants, having a centralized application to help run them locally is significant for slowly embedding AI in all aspects of personal computing.

According to The Information, Microsoft is developing a new AI model, internally named MAI-1, designed to compete with the leading models from Google, Anthropic, and OpenAI. This significant step forward in the tech giant's AI capabilities is boosted by Mustafa Suleyman, the former Google AI leader who previously served as CEO of Inflection AI before Microsoft acquired the majority of its staff and intellectual property for $650 million in March. MAI-1 is a custom Microsoft creation that utilizes training data and technology from Inflection but is not a transferred model. It is also distinct from Inflection's previously released Pi models, as confirmed by two Microsoft insiders familiar with the project. With approximately 500 billion parameters, MAI-1 will be significantly larger than its predecessors, surpassing the capabilities of Microsoft's smaller, open-source models.

For comparison, OpenAI's GPT-4 boasts 1.8 trillion parameters in a Mixture of Experts sparse design, while open-source models from Meta and Mistral feature 70 billion parameters dense. Microsoft's investment in MAI-1 highlights its commitment to staying competitive in the rapidly evolving AI landscape. The development of this large-scale model represents a significant step forward for the tech giant, as it seeks to challenge industry leaders in the field. The increased computing power, training data, and financial resources required for MAI-1 demonstrate Microsoft's dedication to pushing the boundaries of AI capabilities and intention to compete on its own. With the involvement of Mustafa Suleyman, a renowned expert in AI, the company is well-positioned to make significant strides in this field.

IBM announced the availability of the popular open-source Mixtral-8x7B large language model (LLM), developed by Mistral AI, on its watsonx AI and data platform, as it continues to expand capabilities to help clients innovate with IBM's own foundation models and those from a range of open-source providers. IBM offers an optimized version of Mixtral-8x7B that, in internal testing, was able to increase throughput—or the amount of data that can be processed in a given time period—by 50 percent when compared to the regular model. This could potentially cut latency by 35-75 percent, depending on batch size—speeding time to insights. This is achieved through a process called quantization, which reduces model size and memory requirements for LLMs and, in turn, can speed up processing to help lower costs and energy consumption.

The addition of Mixtral-8x7B expands IBM's open, multi-model strategy to meet clients where they are and give them choice and flexibility to scale enterprise AI solutions across their businesses. Through decades-long AI research and development, open collaboration with Meta and Hugging Face, and partnerships with model leaders, IBM is expanding its watsonx.ai model catalog and bringing in new capabilities, languages, and modalities. IBM's enterprise-ready foundation model choices and its watsonx AI and data platform can empower clients to use generative AI to gain new insights and efficiencies, and create new business models based on principles of trust. IBM enables clients to select the right model for the right use cases and price-performance goals for targeted business domains like finance.

Tech giant Microsoft and Paris-based startup Mistral AI, an innovator in open-source AI model development, have announced a new multi-year partnership to accelerate AI innovation and expand access to Mistral's state-of-the-art models. The collaboration will leverage Azure's cutting-edge AI infrastructure to propel Mistral's research and bring its innovations to more customers globally. The partnership focuses on three core areas. First, Microsoft will provide Mistral with Azure AI supercomputing infrastructure to power advanced AI training and inference for Mistral's flagship models like Mistral-Large. Second, the companies will collaborate on AI research and development to push AI model's boundaries. And third, Azure's enterprise capabilities will give Mistral additional opportunities to promote, sell, and distribute their models to Microsoft customers worldwide.

However, an investment in a European startup can not go smoothly without the constant eyesight of the European Union authorities and regulators to oversee the deal. According to Bloomberg, an EU spokesperson on Tuesday claimed that the EU regulators will perform an analysis of Microsoft's investment into Mistral after receiving a copy of the agreement between the two parties. While there is no formal investigation yet, if EU regulators continue to probe Microsoft's deal and intentions, they could launch a complete formal investigation that could lead to the termination of Microsoft's plans. Of course, the formal investigation is still on hold, but investing in EU startups might become unfeasible for American tech giants if the EU regulators continue to push the scrutiny of every investment made in companies based on EU soil.