Artificial Intelligence thread

Eventine

Junior Member
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This isn't "news" as Google has had this technology for over a year without releasing anything to the public:
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Google claims:

To investigate AlphaEvolve’s breadth, we applied the system to over 50 open problems in mathematical analysis, geometry, combinatorics and number theory. The system’s flexibility enabled us to set up most experiments in a matter of hours. In roughly 75% of cases, it rediscovered state-of-the-art solutions, to the best of our knowledge.

And in 20% of cases, AlphaEvolve improved the previously best known solutions, making progress on the corresponding open problems. For example, it advanced the
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. This geometric challenge has
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and concerns the maximum number of non-overlapping spheres that touch a common unit sphere. AlphaEvolve discovered a configuration of 593 outer spheres and established a new lower bound in 11 dimensions.

Granted, there's more hype than substance in the claim as most of the algorithms Alpha Evolve invented were specializations of existing, human invented algorithms to limited domain problems. Still, one can't wonder if it has been critical to their blazing fast achievements in recent months.

I also wonder if Deep Seek may have run into issues with their latest batch of models. There were rumors that they were going to release the next iteration of their thinking series in May, or even earlier. But there's no such release in sight.

Of course, these are just rumors. But the fact that they released a theorem prover in lieu of a major new model would indicate that they are not satisfied with the current performance of whatever general model that they trained.

But releasing a theorem prover also indicates Deep Seek is investing in foundational tools (much like Google has with Alpha Evolve, Alpha Fold, etc.), which seems to be the key to pushing past the current wall facing most other AI companies outside of Google and Open AI.

Times like these also cause one to hate the fact that China has no equivalent to Google (e.g. a huge, global tech. company built around search and foundational AI research) due to the shameful failure that is Baidu.
 
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BillRamengod

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China, Huawei and more in Malaysia. kind of expected for China to train local AI talents in ASEAN countries.
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Malaysia Launches Region’s First Sovereign Full-Stack AI Infrastructure​

May 19, 2025 7:15 pm

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KUALA LUMPUR, May 19 — Malaysia has officially launched the Strategic Artificial Intelligence (AI) Infrastructure, becoming the first in the region to activate a sovereign, full-stack artificial intelligence (AI) ecosystem.
Ministry of Communications Deputy Minister Teo Nie Ching said the move marks an important step in the country’s AI development, as localising large language models like DeepSeek and hosting servers domestically would enhance AI sovereignty by ensuring data is processed locally, thus safeguarding user privacy and data security.
“The special thing about this project is that the data will be stored in Malaysia, it will be managed by Malaysians, and it will be used by Malaysians as well, so this is how we can actually safeguard our AI sovereignty.
“(With this) now it’s no longer like the cloud or the data centre is overseas, but it’s now purely in Malaysia — server also in Malaysia, managed by Malaysia, and the AI agents will also be developed by Malaysians. I think this is how we can localise the AI application in Malaysia,” she said.
Teo was speaking at a press conference after officiating the launch of the Strategic AI Infrastructure: Trusted, Sovereign and Global, here today.
Teo also noted that the project marks the first deployment of chips and servers, along with the DeepSeek large language model, outside of China, making it a regional first.
“So this is first of the kind outside China, we are very proud, meaning that in terms of AI adoption and AI application, Malaysia indeed truly will be the leader in ASEAN, in terms of AI application and adoption,” she said.


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In Chinese page is 'Chips and Severs from Huawei'
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tokenanalyst

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Xiamen University uses machine learning methods to explore the key factors affecting the lifespan of perovskite solar cells​



Recently, Professor Li Lin, Assistant Professor Chen Mengyu, Professor Li Cheng and others from the School of Electronic Science and Technology of Xiamen University published a research result titled "Machine Learning-assisted Analysis of Perovskite Solar Cell Long-term Stability under Multiple Environmental Factors" in the top journal "ACS Sustainable Chemistry & Engineering". They proposed a machine learning-based method to analyze the key factors affecting the long-term stability of perovskite solar cells (PSCs).

PSCs have made significant progress in the past decade. However, poor long-term stability is a major challenge facing PSCs, which has hindered their large-scale commercialization. Traditionally, the optimization of complex parameters affecting lifetime mainly relies on trial-and-error experimental methods, which are time-consuming and resource-intensive. Considering the complexity of these influencing factors, from the perspective of the huge parameter space and mutual coupling characteristics, effective research strategies and methods are urgently needed to optimize the long-term stability of PSCs and accelerate their commercialization. Many studies have demonstrated the use of machine learning (ML) to analyze the performance and behavior of perovskite materials through a large amount of experimental and simulation data, improving speed and accuracy.

Professor Li Cheng, Professor Li Lin, Assistant Professor Chen Mengyu from the School of Electronic Science and Technology of Xiamen University proposed an ML-based method to analyze the key factors affecting the long-term stability of PSC. This method introduces a multi-head attention mechanism to effectively mine the intrinsic connections between multiple input data, including external environmental parameters and internal structural parameters. The entire study is mainly divided into four parts:

First, the research team proposed an ML method based on the Multi-Head mechanism to simultaneously process multiple external and internal parameters that affect the stability of PSC. Combined with the Squeeze-Excited Residual Network (SEResNet), this method achieved high prediction accuracy, with a correlation coefficient (R²) of 0.972 and a Pearson correlation coefficient (r) of 0.986.
Secondly, the research team applied the SHapley Additive exPlanations (SHAP) algorithm to identify the key factors affecting the stability of PSCs, namely external environmental parameters and internal structural parameters. Based on high-throughput predictions of about 2,000 PSC devices, the interaction between these key factors was deeply analyzed, which helped to show their impact on device stability in multiple dimensions.

Subsequently, the research team conducted device life experiments to verify the reliability of the model's prediction results. Through the preparation and performance testing of a series of PSC devices, it was verified that the PSC life trend predicted by the model was highly consistent with the experimental results, further confirming the effectiveness and accuracy of the ML model in practical applications.
Finally, the research team predicted the PSC architecture with the best long-term stability at 85 ºC and 85% relative humidity. The innovation of this study lies not only in demonstrating the great potential of ML in predicting device stability and extracting key parameters, but also in significantly improving the accuracy of PSC performance prediction by integrating advanced ML technology, providing new design ideas and research paths for achieving long-term stable PSC devices.

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vincent

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China, Huawei and more in Malaysia. kind of expected for China to train local AI talents in ASEAN countries.
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Malaysia declared it'll build a first-of-its-kind AI system powered by Huawei Technologies Co. chips, only to distance itself from that statement a day later, underscoring the Asian nation's delicate position in the US-Chinese AI race.

Deputy Minister of Communications Teo Nie Ching said in a speech Monday her country would be the first to activate an unspecified class of Huawei "Ascend GPU-powered AI servers at national scale."

Malaysia would deploy 3,000 units of Huawei's primary AI offering by 2026, she said in prepared remarks reviewed by Bloomberg News. Chinese startup DeepSeek would also make one of its AI models available to the Southeast Asian country, the official added.

...

When reached for comment by Bloomberg News on Tuesday, Teo's office said it's retracting her remarks on Huawei without explanation. It's unclear whether the project will proceed as planned.
 
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