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DeeperML - #reasoningmodel
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@www.analyticsvidhya.com
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MiniMaxAI, a Chinese AI company, has launched MiniMax-M1, a large-scale open-source reasoning model, marking a significant step in the open-source AI landscape. Released on the first day of the "MiniMaxWeek" event, MiniMax-M1 is designed to compete with leading models like OpenAI's o3, Claude 4, and DeepSeek-R1. Alongside the model, MiniMax has released a beta version of an agent capable of running code, building applications, and creating presentations. MiniMax-M1 presents a flexible option for organizations looking to experiment with or scale up advanced AI capabilities while managing costs.
MiniMax-M1 boasts a 1 million token context window and utilizes a new, highly efficient reinforcement learning technique. The model comes in two variants, MiniMax-M1-40k and MiniMax-M1-80k. Built on a Mixture-of-Experts (MoE) architecture, the model is trained on 456 billion parameters. MiniMax has introduced Lightning Attention for its M1 model, dramatically reducing inference costs and only consumes 25% of the floating point operations (FLOPs) required by DeepSeek R1 at a generation length of 100,000 tokens. Available on AI code sharing communities like Hugging Face and GitHub, MiniMax-M1 is released under the Apache 2.0 license, enabling businesses to freely use, modify, and implement it for commercial applications without restrictions or payment. MiniMax-M1 features a web search functionality and can handle multimodal input like text, images, and presentations. The expansive context window allows the model to exchange information equivalent to a small collection or book series, far exceeding OpenAI's GPT-4o, which has a context window of 128,000 tokens. Recommended read:
References :
Mark Tyson@tomshardware.com
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OpenAI has launched O3 PRO for ChatGPT, marking a significant advancement in both performance and cost-efficiency for its reasoning models. This new model, O3-Pro, is now accessible through the OpenAI API and the Pro plan, priced at $200 per month. The company highlights substantial improvements with O3 PRO and has also dropped the price of its previous o3 model by 80%. This strategic move aims to provide users with more powerful and affordable AI capabilities, challenging competitors in the AI model market and expanding the boundaries of reasoning.
The O3-Pro model is set to offer enhanced raw reasoning capabilities, but early reviews suggest mixed results when compared to competing models like Claude 4 Opus and Gemini 2.5 Pro. While some tests indicate that Claude 4 Opus currently excels in prompt following, output quality, and understanding user intentions, Gemini 2.5 Pro is considered the most economical option with a superior price-to-performance ratio. Initial assessments suggest that O3-Pro might not be worth the higher cost unless the user's primary interest lies in research applications. The launch of O3-Pro coincides with other strategic moves by OpenAI, including consolidating its public sector AI products under the "OpenAI for Government" banner, including ChatGPT Gov. OpenAI has also secured a $200 million contract with the U.S. Department of Defense to explore AI applications in administration and security. Despite these advancements, OpenAI is also navigating challenges, such as the planned deprecation of GPT-4.5 Preview in the API, which has caused frustration among developers who relied on the model for their applications and workflows. Recommended read:
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Carl Franzen@AI News | VentureBeat
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Mistral AI has launched its first reasoning model, Magistral, signaling a commitment to open-source AI development. The Magistral family features two models: Magistral Small, a 24-billion parameter model available with open weights under the Apache 2.0 license, and Magistral Medium, a proprietary model accessible through an API. This dual release strategy aims to cater to both enterprise clients seeking advanced reasoning capabilities and the broader AI community interested in open-source innovation.
Mistral's decision to release Magistral Small under the permissive Apache 2.0 license marks a significant return to its open-source roots. The license allows for the free use, modification, and distribution of the model's source code, even for commercial purposes. This empowers startups and established companies to build and deploy their own applications on top of Mistral’s latest reasoning architecture, without the burdens of licensing fees or vendor lock-in. The release serves as a powerful counter-narrative, reaffirming Mistral’s dedication to arming the open community with cutting-edge tools. Magistral Medium demonstrates competitive performance in the reasoning arena, according to internal benchmarks released by Mistral. The model was tested against its predecessor, Mistral-Medium 3, and models from Deepseek. Furthermore, Mistral's Agents API's Handoffs feature facilitates smart, multi-agent workflows, allowing different agents to collaborate on complex tasks. This enables modular and efficient problem-solving, as demonstrated in systems where agents collaborate to answer inflation-related questions. Recommended read:
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Mark Tyson@tomshardware.com
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OpenAI has launched o3-pro, a new and improved version of its AI model designed to provide more reliable and thoughtful responses, especially for complex tasks. Replacing the o1-pro model, o3-pro is accessible to Pro and Team users within ChatGPT and through the API, marking OpenAI's ongoing effort to refine its AI technology. The focus of this upgrade is to enhance the model’s reasoning capabilities and maintain consistency in generating responses, directly addressing shortcomings found in previous models.
The o3-pro model is designed to handle tasks requiring deep analytical thinking and advanced reasoning. While built upon the same transformer architecture and deep learning techniques as other OpenAI chatbots, o3-pro distinguishes itself with an improved ability to understand context. Some users have noted that o3-pro feels like o3, but is only modestly better in exchange for being slower. Comparisons with other leading models such as Claude 4 Opus and Gemini 2.5 Pro reveal interesting insights. While Claude 4 Opus has been praised for prompt following and understanding user intentions, Gemini 2.5 Pro stands out for its price-to-performance ratio. Early user experiences suggest o3-pro might not always be worth the expense due to its speed, except for research purposes. Some users have suggested that o3-pro hallucinates modestly less, though this is still being debated. Recommended read:
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@www.marktechpost.com
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DeepSeek, a Chinese AI startup, has launched an updated version of its R1 reasoning AI model, named DeepSeek-R1-0528. This new iteration brings the open-source model near parity with proprietary paid models like OpenAI’s o3 and Google’s Gemini 2.5 Pro in terms of reasoning capabilities. The model is released under the permissive MIT License, enabling commercial use and customization, marking a commitment to open-source AI development. The model's weights and documentation are available on Hugging Face, facilitating local deployment and API integration.
The DeepSeek-R1-0528 update introduces substantial enhancements in the model's ability to handle complex reasoning tasks across various domains, including mathematics, science, business, and programming. DeepSeek attributes these improvements to leveraging increased computational resources and applying algorithmic optimizations in post-training. Notably, the accuracy on the AIME 2025 test has surged from 70% to 87.5%, demonstrating deeper reasoning processes with an average of 23,000 tokens per question, compared to the previous version's 12,000 tokens. Alongside enhanced reasoning, the updated R1 model boasts a reduced hallucination rate, which contributes to more reliable and consistent output. Code generation performance has also seen a boost, positioning it as a strong contender in the open-source AI landscape. DeepSeek provides instructions on its GitHub repository for those interested in running the model locally and encourages community feedback and questions. The company aims to provide accessible AI solutions, underscored by the availability of a distilled version of R1-0528, DeepSeek-R1-0528-Qwen3-8B, designed for efficient single-GPU operation. Recommended read:
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@www.marktechpost.com
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DeepSeek has released a major update to its R1 reasoning model, dubbed DeepSeek-R1-0528, marking a significant step forward in open-source AI. The update boasts enhanced performance in complex reasoning, mathematics, and coding, positioning it as a strong competitor to leading commercial models like OpenAI's o3 and Google's Gemini 2.5 Pro. The model's weights, training recipes, and comprehensive documentation are openly available under the MIT license, fostering transparency and community-driven innovation. This release allows researchers, developers, and businesses to access cutting-edge AI capabilities without the constraints of closed ecosystems or expensive subscriptions.
The DeepSeek-R1-0528 update brings several core improvements. The model's parameter count has increased from 671 billion to 685 billion, enabling it to process and store more intricate patterns. Enhanced chain-of-thought layers deepen the model's reasoning capabilities, making it more reliable in handling multi-step logic problems. Post-training optimizations have also been applied to reduce hallucinations and improve output stability. In practical terms, the update introduces JSON outputs, native function calling, and simplified system prompts, all designed to streamline real-world deployment and enhance the developer experience. Specifically, DeepSeek R1-0528 demonstrates a remarkable leap in mathematical reasoning. On the AIME 2025 test, its accuracy improved from 70% to an impressive 87.5%, rivaling OpenAI's o3. This improvement is attributed to "enhanced thinking depth," with the model now utilizing significantly more tokens per question, indicating more thorough and systematic logical analysis. The open-source nature of DeepSeek-R1-0528 empowers users to fine-tune and adapt the model to their specific needs, fostering further innovation and advancements within the AI community. Recommended read:
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@www.artificialintelligence-news.com
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ServiceNow is making significant strides in the realm of artificial intelligence with the unveiling of Apriel-Nemotron-15b-Thinker, a new reasoning model optimized for enterprise-scale deployment and efficiency. The model, consisting of 15 billion parameters, is designed to handle complex tasks such as solving mathematical problems, interpreting logical statements, and assisting with enterprise decision-making. This release addresses the growing need for AI models that combine strong performance with efficient memory and token usage, making them viable for deployment in practical hardware environments.
ServiceNow is betting on unified AI to untangle enterprise complexity, providing businesses with a single, coherent way to integrate various AI tools and intelligent agents across the entire company. This ambition was unveiled at Knowledge 2025, where the company showcased its new AI platform and deepened relationships with tech giants like NVIDIA, Microsoft, Google, and Oracle. The aim is to help businesses orchestrate their operations with genuine intelligence, as evidenced by the adoption from industry leaders like Adobe, Aptiv, the NHL, Visa, and Wells Fargo. To further broaden its reach, ServiceNow has introduced the Core Business Suite, an AI-driven solution aimed at the mid-market. This suite connects employees, suppliers, systems, and data in one place, enabling organizations of all sizes to work faster and more efficiently across critical business processes such as HR, procurement, finance, facilities, and legal affairs. ServiceNow aims for rapid implementation, suggesting deployment within a few weeks, and integrates functionalities from different divisions into a single, uniform experience. Recommended read:
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