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NishMath - #aimodel
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@www.marktechpost.com
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Google has unveiled a new AI model designed to forecast tropical cyclones with improved accuracy. Developed through a collaboration between Google Research and DeepMind, the model is accessible via a newly launched website called Weather Lab. The AI aims to predict both the path and intensity of cyclones days in advance, overcoming limitations present in traditional physics-based weather prediction models. Google claims its algorithm achieves "state-of-the-art accuracy" in forecasting cyclone track and intensity, as well as details like formation, size, and shape.
The AI model was trained using two extensive datasets: one describing the characteristics of nearly 5,000 cyclones from the past 45 years, and another containing millions of weather observations. Internal testing demonstrated the algorithm's ability to accurately predict the paths of recent cyclones, in some cases up to a week in advance. The model can generate 50 possible scenarios, extending forecast capabilities up to 15 days. This breakthrough has already seen adoption by the U.S. National Hurricane Center, which is now using these experimental AI predictions alongside traditional forecasting models in its operational workflow. Google's AI's ability to forecast up to 15 days in advance marks a significant improvement over current models, which typically provide 3-5 day forecasts. Google made the AI accessible through a new website called Weather Lab. The model is available alongside two years' worth of historical forecasts, as well as data from traditional physics-based weather prediction algorithms. According to Google, this could help weather agencies and emergency service experts better anticipate a cyclone’s path and intensity. Recommended read:
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Mark Tyson@tomshardware.com
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OpenAI has recently launched its newest reasoning model, o3-pro, making it available to ChatGPT Pro and Team subscribers, as well as through OpenAI’s API. Enterprise and Edu subscribers will gain access the following week. The company touts o3-pro as a significant upgrade, emphasizing its enhanced capabilities in mathematics, science, and coding, and its improved ability to utilize external tools.
OpenAI has also slashed the price of o3 by 80% and o3-pro by 87%, positioning the model as a more accessible option for developers seeking advanced reasoning capabilities. This price adjustment comes at a time when AI providers are competing more aggressively on both performance and affordability. Experts note that evaluations consistently prefer o3-pro over the standard o3 model across all categories, especially in science, programming, and business tasks. O3-pro utilizes the same underlying architecture as o3, but it’s tuned to be more reliable, especially on complex tasks, with better long-range reasoning. The model supports tools like web browsing, code execution, vision analysis, and memory. While the increased complexity can lead to slower response times, OpenAI suggests that the tradeoff is worthwhile for the most challenging questions "where reliability matters more than speed, and waiting a few minutes is worth the tradeoff.” Recommended read:
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@medium.com
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DeepSeek's latest AI model, R1-0528, is making waves in the AI community due to its impressive performance in math and reasoning tasks. This new model, despite having a similar name to its predecessor, boasts a completely different architecture and performance profile, marking a significant leap forward. DeepSeek R1-0528 has demonstrated "unprecedented levels of demand" shooting to the top of the App Store past closed model rivals and overloading their API with unprecedented levels of demand to the point that they actually had to stop accepting payments.
The most notable improvement in DeepSeek R1-0528 is its mathematical reasoning capabilities. On the AIME 2025 test, the model's accuracy increased from 70% to 87.5%, surpassing Gemini 2.5 Pro and putting it in close competition with OpenAI's o3. This improvement is attributed to "enhanced thinking depth," with the model using significantly more tokens per question, engaging in more thorough chains of reasoning. This means the model can check its own work, recognize errors, and course-correct during problem-solving. DeepSeek's success is challenging established closed models and driving competition in the AI landscape. DeepSeek-R1-0528 continues to utilize a Mixture-of-Experts (MoE) architecture, now scaled up to an enormous size. This sparse activation allows for powerful specialized expertise in different coding domains while maintaining efficiency. The context also continues to remain at 128k (with RoPE scaling or other improvements capable of extending it further.) The rise of DeepSeek is underscored by its performance benchmarks, which show it outperforming some of the industry’s leading models, including OpenAI’s ChatGPT. Furthermore, the release of a distilled variant, R1-0528-Qwen3-8B, ensures broad accessibility of this powerful technology. 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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