Artificial Intelligence thread

Coalescence

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Just wanted to share this article here, because I've been paying attention to open source projects in Github lately and there's a lot of LLM AIs popping up lately. There's a possibility that open source LLM will be good enough or even better than OpenAI's ChatGPT in the future, allowing consumers and business to have similar capabilities without the data privacy risk and lower cost.
 

tphuang

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Huawei unveiled updates to fully domestic Ascend platform (w/ Atlas-900 AI cluster) including MindSpore2.0 ML framework, Ascend C language & Atlas 200I developer kit

Ascend platform supports 30+ big models, representing > 50% of native models in China. It supports 25 stable days training with 200 billion parameters. This is quite the market share

Currently, 25 smart cities have been built using Ascend w/ 14 of them launched & fully operational According to HW, more than 3.5m Kunpeng/Ascend developers, > 5600 partners & 15500 certficiations

他进一步表示:“鲲鹏本身是生态性的产业,在四年前基于鲲鹏的软件应用是非常少的,我们做的是鲲鹏计算,其实做的是鲲鹏的软件生态,从软件生态的迁移开始,当前有许多新应用已经是基于鲲鹏原生的。鲲鹏正在从‘迁移’走向‘原生’,从‘可用’走向‘好用’。”

华为昇腾芯片是华为公司发布的两款人工智能处理器 ,包括昇腾910和昇腾310处理器 ,昇腾910支持全场景人工智能应用,而昇腾310主要用在边缘计算等低功耗的领域 。采用自家的达芬奇架构,该架构有极致功耗和散热,可以全场景覆盖。

鲲鹏处理器和昇腾芯片都是为鲲鹏计算产业服务的。

鲲鹏计算产业(鲲鹏生态)是基于鲲鹏处理器的基础软硬件设施、行业应用及服务,涵盖从底层硬件、基础软件到上层行业应用的全产业链条。纵观鲲鹏计算产业生态全景,硬件方面,围绕鲲鹏处理器,涵盖包括昇腾AI芯片、智能网卡芯片、底板管理控制器(BMC)芯片、固态硬盘(SSD)、磁盘阵列卡(RAID卡)、主板等部件以及个人计算机、服务器、存储等整机产品。基础软件方面,涵盖操作系统、虚拟化软件、数据库、中间件、存储软件、大数据平台、数据保护和云服务等基础软件及平台软件。行业应用方面,鲲鹏计算产业生态覆盖政府、金融、电信、能源、大企业等各大行业应用,提供全面、完整、一体化的信息化解决方案。
Things to consider about Kunpeng & Ascend. They really built this up over a few years. They have a fully ecology behind it with hardware Atlas-900 which was state of art back in 2020 when it first came out, but is now even better hardware wise with greater computation, better supporting infrastructure and software integration and such.

Kunpeng is used everywhere now with wide spread software support.

另一方面,华为已经从单点创新走向系统级架构创新,即从计算、存储、交换一体化的设计。比如构建了全液冷多样式算力平台,相比传统机柜实现4-8倍的算力密度提升,但机房面积节省超过70%。
There are also things like this that by using liquid cooling, they can 4 to 8x computation density and decrease size of datacenter space by 70%

One example of big model is 紫东太初(Omni-Perception Pre-Trainer)by CAS. Can learn from text, pictures, voice, video, 3D point cloud, and sensor signals,
 

tphuang

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Huawei unveiled Atlas 200i DK A2 Ascend AI developer's kit valued at just 1999 RMB, offering 8 TOPS * 4GB storage with RJ45 network port, HDMI & USB 3.0. It uses 4 core CPU

Looks like a great way to train developers to the real thing which is Atlas 900
 

tphuang

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Even better article here on what was unveiled at the Ascend/Kunpeng developer conference
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My guess is that the developer kit uses some nerfed version of Ascend-310 that probably can be manufactured by SMIC's 12/14nm process and then paired that up with a 4-core Kunpeng-920 CPU

openGauss database and mindspore AI framework all sound pretty well developed now. That's kind of HW's advantage over other Chinese tech firms. They've just been doing this for longer and also have more R&D resources to through at it.
 

Franklin

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There are plenty of countries in the world that do not feel comfortable with a (politically) free weelding AI Chatbot. If China can create a 'politically reliable' AI Chatbot it will be a huge growth industry. The only way for the Americans to compete against that is to censor their own versions for the export market.
 

luminary

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Why AI ghostwriting is another doomed fad:
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  1. Media outlets based on advertising need clicks to sell.
  2. But clicks are in short supply, and a few huge web platforms (especially Google) control most of them
  3. This forces journalism platforms to embrace gimmicky clickbait strategies that are doomed to failure—and are unlikely to deliver quality writing.
  4. That’s because gimmicks are just that—and they eventually get exposed. But as one clickbait strategy dies, another one replaces it—in an unending cycle.
  5. The latest (and probably the final act) in this farce is the AI-generated article, which reduces the cost of clickbait articles to almost zero. This is the endgame—the most brutal trick of them all.
  6. It will lead to a proliferation of garbage articles like you’ve never seen before. Media platforms will churn them out as fast as they can to grab those last remaining clicks from easily deceived readers.
  7. But this is a fool’s game. Meanwhile, there’s a better strategy in town—namely the subscription model for quality journalism.
  8. All the success stories in media right now are funded by subscriptions. The business model changed while the experts weren’t looking, and went back to basics. We don’t need to worry about gimmicks—we’ve returned to selling writing, not ads.
  9. As final proof of this, note how many of these success stories (especially on Substack, but elsewhere too) are built on individual writers, not media brands. This alone tells you how central writing has now become in the growing sector of American journalism.
 

Michaelsinodef

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Baidu AI smartphone.
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Feels like a mistake, instead of trying to squeeze themselves into the market, they could have tried to partner up with all the current big chinese players.

Not only might it actually try to stiffle their AI developments, but also avoid in having to engage in actual competition, not to mention competition in phone making, which Baidu should be new compared to the already big players.
 

tphuang

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btw, from that wsj article again
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In a paper in March, Huawei researchers demonstrated how they could use such techniques to train its latest-generation large language model using only the company’s Ascend chips and without Nvidia chips. Despite some shortcomings, the model, known as PanGu-Σ, reached state-of-the-art performance on a few Chinese-language tasks, including reading comprehension and grammar challenges, the researchers wrote in the paper.
Dylan Patel, chief analyst at semiconductor research and consulting firm SemiAnalysis, said Chinese researchers’ pain points will only exacerbate without access to the new Nvidia H100, which includes an extra performance-boosting feature especially helpful for training ChatGPT-like models.
But a paper last year from Baidu and Peng Cheng Laboratory, a Shenzhen-based research institute, showed researchers were training large language models in a way that would make the feature unnecessary. Mr. Patel said it looked promising even though the research was in its early stages.
“If it works well, they can effectively circumvent the sanctions,” he said

i must stress again, that 1999 RMB developer kit is a big deal. Great & cheap way for new developers to setup and train on their own GPU hardware. Training software developers is more critical than anything else. HW appears to have a leg up here with over 3.5 million developers in its community already. Also probably why all the independent smart city projects use HW products. Because that's what all the developers are using
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