Despite Chinese cloud companies investing heavily in AI development, the uptake among Chinese businesses has not been as high as the industry would like it to be. While there could be many reasons for this, Chinese cloud companies are hoping 2024 will see better growth opportunities and more firms taking up their products and services.

Chinese cloud companies like Alibaba Cloud, Huawei and Tencent have each released AI models and products this year. Chinese tech company Baidu as well as several other Chinese companies have also developed and released more AI models.

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According to a report by Canalys released in December 2023, Alibaba Cloud, Huawei Cloud and Tencent Cloud are the top three cloud vendors in Mainland China in Q3 2023. The Chinese cloud companies collectively grew 22% to account for a combined 73% share of customer spending. In Q3 2023, cloud revenue generated via channels in the Chinese market accounted for 25% of total revenue, against 23% in the previous quarter.

But the report also stated that the Chinese cloud services market remains conservative, relying heavily on government and state-owned enterprises to drive growth.

“The innate complexity of AI technology presents challenges in terms of adoption and deployment,” Canalys said, “yet simultaneously unlocks opportunities for a broader AI ecosystem.”

Alibaba Cloud has slashed the prices of its cloud services by up to 55%.

Alibaba Cloud slashes pricing

Given the slow adoption of AI among Chinese businesses, Alibaba Cloud has cut the prices of its cloud services by up to 55%. According to a report by Bloomberg, the company will be slashing its prices by as much as 55%. The price reductions are expected to span over 100 products offered by the Chinese cloud provider.

The price cut is one of the most aggressive moves taken by Alibaba. While there have been price cuts announced in the past by other cloud service providers, none have ever reached a cut as high as the Chinese cloud company.

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Alibaba Cloud is probably hoping the price cuts will make its product not only more affordable to Chinese businesses but will also allow them to stay ahead of rivals Tencent and Baidu.

The price slashing is expected to cause a ripple effect in the cloud services industry, which could trigger a price war. Reports by Bloomberg are already indicating that rivals JD.com responded within the same day of Alibaba’s announcement by unveiling its own round of price cuts as well.

Analysts from Bloomberg Intelligence also stated that the price cuts are pretty much a declaration of a cloud price war. Alibaba has struggled over the past year to revamp its vast e-commerce, logistics and cloud empire in the face of fierce competition and geopolitical risks. The company is looking to revive growth after two years of regulatory scrutiny and Covid-era economic turbulence.

It remains to be seen if Huawei, Tencent and other Chinese cloud companies will reduce their prices for their services. However if Alibaba Cloud is capable of doing so and capturing a larger market size in China, the competitors would need to join in or find other ways to boost their customer base.

Has Alibaba Cloud started a price war with other Chinese cloud companies? (Image by Shutterstock).

Chinese cloud companies kick off the global price war?

In 2024, Canalys expects global cloud infrastructure services spending to increase by 20%, compared with 18% in 2023. Currently, the biggest cloud companies in the world are AWS, Microsoft Azure and Google Cloud.

“The integration of generative AI into mainstream software products is accelerating, potentially leading to quicker commercialization of generative AI applications. Google recently introduced its rebranded Gemini large language model into Workspace applications, such as Gmail and Docs. At the same time, Microsoft launched Copilot for Microsoft 365 last November, embedding its generative AI platform into Word, Excel and other office applications,” said Yi Zhang, Analyst at Canalys.

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However, could the price slashes in China have an impact on the global cloud services pricing? Given the weakening currencies in Asia Pacific, businesses in the region could opt for a cloud service provider that is capable of giving them the best value they can get.

Alibaba Cloud has a strong presence in APAC, especially in Southeast Asia. A similar price reduction in the region could trigger a price war not just from Chinese cloud companies but global companies as well.

While AWS, Google Cloud and Microsoft remain strong in the region, Chinese cloud companies have a soft spot as well among some businesses. Should the company decide to make a similar move here, businesses will be tempted to pick the cheaper option as well.

For now, though, the price cuts seem to be only in China. Perhaps in the future, if the move seems to be beneficial for the company, they could spread to services outside China as well.

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When it comes to harnessing generative AI capabilities for enterprises, investing in the right infrastructure is crucial to ensure the best results are achieved. While technology has let businesses decide if they want to work on physical or virtual infrastructure for their AI workloads, there are still some challenges for them.

For example, scalability, cost and flexibility are some of the challenges organizations face when it comes to working on their generative AI solutions. Often, businesses want quick deployments, and while the infrastructure caters to speed, it still requires several rounds of testing to ensure the applications work properly.

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One way of speeding up the process is by relying on serverless technology. Serverless computing is a cloud computing model that allows developers to run code without having to manage servers, provision resources, or worry about scalability.

Serverless computing can be used to run AI workloads. But the workloads need to be compatible with the serverless model and the limitations set by the cloud provider. Only then can businesses enjoy the advantages of using serverless computing for AI.

Zhou Jingren, chief technology officer (CTO), Alibaba Cloud, speaks at Alibaba Cloud AI & Big Data Summit in Singapore.

Alibaba Cloud and serverless computing for AI

Alibaba Cloud recently unveiled a serverless version of its Platform for AI (PAI)-Elastic Algorithm Service (EAS) at the inaugural AI & Big Data Summit in Singapore. The PAI-EAS is designed to offer a cost-efficient solution for model deployment and inference to individuals and enterprises.

The PAI-EAS platform allows users to tap into computing resources as needed, eliminating the need to oversee the management and upkeep of physical or virtual servers. What’s more, users will be billed only for the computing resources they employ, which could mean a 50% reduction in inference costs when compared with the traditional pricing model.

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Currently in beta testing, the serverless offering is accessible for image generation model deployment. In March 2024, the serverless version is scheduled to expand its capabilities to support the deployment of prominent open-source LLMs and models from Alibaba’s AI model community, ModelScope. This includes models tailored for tasks such as image segmentation, summary generation, and voice recognition.

Alibaba Cloud also announced the latest integration of its vector engine technology into more product offerings, including its data warehouse Hologres, search services Elasticsearch and OpenSearch. The integration is designed to make it easier for enterprises to access various LLMs and build customized generative AI applications.

With LLMs serving, training services and the vector engine technology, Alibaba Cloud is able to support a Retrieval-Augmented Generation (RAG) process, letting enterprises enhance LLMs with their knowledge bases for improved outcomes. This translates to improved accuracy, accelerated retrieval of relevant information, and more nuanced insights for enterprises, contributing to heightened efficiency and decision-making capabilities across a wide range of applications.

 “Our technology updates underscore our commitment to empowering enterprises with the latest intelligence-driven solutions for heightened efficiency and performance. This marks a significant stride in our mission to provide innovative solutions that redefine the possibilities of artificial intelligence in diverse applications,” Zhou Jingren, chief technology officer, of Alibaba Cloud, commented during the summit.

Selina Yuan, president of international business at Alibaba Cloud, speaks at the Alibaba Cloud AI & Big Data Summit in Singapore.

Make model training easier

Training your LLM is critical for AI workloads. During the summit, Alibaba Cloud also announced an upgrade to its big data service, called MaxCompute MaxFrame. A distributed Python data processing framework, the service taps into the growing demand for data preprocessing and data offline or online analysis in AI-related computing tasks. It allows users to process massive amounts of data more efficiently and flexibly while launching AI tasks such as LLM training.

For image generation, Alibaba Cloud has introduced PAI-Artlab, to foster enhanced creativity among designers. The comprehensive platform for model training and image generation empowers designers to quickly produce professional-grade designs and unlock greater creative potential.

With PAI-Artlab, designers can generate design images for a variety of applications, including interior home design, product promotional posters, gaming character creation, and gaming scene development. While it is only available in China currently, it will be available in Singapore soon. The platform also provides a rich ecosystem of ready-to-use tools to enable designers with no coding background to develop and train custom models that generate images tailored to their specific requirements.

Last year, Alibaba Cloud elevated its entire range of database solutions, including the cloud-native database PolarDB, cloud-native data warehouse AnalyticDB, and cloud-native multi-model database, Lindorm. The solutions integrated proprietary vector engine technology to significantly enhance performance and capabilities.

Vector engines transform text and data into a high-dimensional space, optimizing AI performance by embedding large volumes of structured and unstructured context in a complex yet efficient manner. This facilitates and streamlines tasks like similarity comparisons and semantic analysis, particularly benefiting LLMs and advancing various advanced AI functionalities.

“There is an increasing demand for AI technologies among our global customers. By open-sourcing our proprietary language models, we are well-equipped to offer powerful computing solutions and cutting-edge AI innovations to support clients in developing customized generative AI applications, addressing their unique challenges and positioning them to harness the wave of opportunities emerging from the dynamic generative AI sector”, commented Selina Yuan, president of international business at Alibaba Cloud.

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In 2023, Alibaba Cloud has been a key player in Malaysia’s journey towards digital transformation, significantly enhancing the technology landscape across multiple industries. This involvement has led to modernizing sectors like logistics, automotive, and financial services. By implementing Alibaba Cloud’s technology solutions, Malaysian businesses and public institutions have experienced a marked improvement in operational efficiency and customer engagement, strengthening their competitive stance in the digital world.

This year, Alibaba Cloud has bolstered various Malaysian businesses across industries such as logistics, automotive, and financial services, helping them in their digital transformation endeavors. These efforts have streamlined operations and spawned innovation, contributing to the digital advancement of these sectors.

Malaysian enterprises and public institutions have benefited from the partnership with Alibaba Cloud, achieving enhanced logistics efficiency, innovative financial services, and a boost in digital capabilities across sectors. Alibaba Cloud’s technology has been instrumental in optimizing business operations and elevating customer experiences, giving these entities a competitive advantage in the rapidly-evolving digital arena.

Kun Huang, the general manager of Malaysia at Alibaba Cloud Intelligence, expressed satisfaction with the impact of their advanced technologies on Malaysian businesses. Huang said that Alibaba Cloud was spearheading a shift towards digital excellence through strategic partnerships and innovative solutions. The company’s unwavering commitment to empowering Malaysian enterprises is central to its strategy, as it continues to contribute to building a digitally resilient and globally competitive business environment in Malaysia.

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Alibaba Cloud pioneering digital solutions

In 2023, Alibaba Cloud expanded its reach in East Malaysia by partnering with two public service organizations, Sabah Credit Corporation (SCC) and SAINS.

Alibaba Cloud – transforming Malysia.

SCC, a statutory body under the Sabah State Government, has enhanced its operations by adopting Alibaba Cloud’s enterprise mobile application studio (EMAS) superapp solution. This integration has streamlined SCC’s various applications, including YONO Finance, Sabah Pay, and YONOPay, into a unified mobile platform named YONO. This consolidation has helped SCC overcome technical challenges, accelerate its superapp development, and efficiently manage app lifecycles at a reduced cost through centralized management.

On the other hand, SAINS has initiated Malaysia’s first Alibaba Cloud private cloud program, significantly propelling digital transformation in East Malaysia. This initiative brings advanced cloud computing and innovative technology to various sectors in the region. Alibaba Cloud’s Apsara Stack solution, which provides flexible and reliable hosting services, is central to this development,  improving system recovery times after disruptions.

Alibaba Cloud accelerates SAINS’ mission. (Source – Alibaba Cloud).

SAINS has always been at the forefront of application development since its inception. With advancements in mobile and cloud technologies, SAINS is adapting to increasing customer demands for application reliability and swift disaster recovery. To meet these expectations, SAINS is focusing on quick auto-recovery for client applications.

The infrastructure developed by Alibaba Cloud is tailored for hyperscaling and top-tier disaster recovery, aligning with SAINS’s growth objectives and stringent security protocols. A vital feature of this deployment is the establishment of two availability zones in Sarawak for disaster recovery, letting SAINS and the Sarawak Government run applications across these zones simultaneously, thus ensuring enhanced operational resilience and efficiency.

Driving automotive innovation: the Agmo EV superapp

Agmo Holdings Berhad, a Malaysian digital solutions leader, has collaborated with Alibaba Cloud to create the Agmo electric vehicle (EV) superapp. This innovative platform has transformed the EV user experience, offering real-time charging status monitoring and personalized energy consumption insights. The superapp has reshaped the user interface for EV enthusiasts, setting new standards in smart technology integration within the automotive industry.

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The Agmo and Alibaba Cloud partnership combines local innovation and global technology expertise. This collaboration has positioned the Agmo EV superspp as a frontrunner in sustainable and connected mobility solutions in the region.

Alibaba Cloud digitally transforming financial services

Alibaba Cloud has significantly helped digitally transform Malaysia’s financial services industries (FSI), encompassing banking, insurance, securities, and fintech. Its services align with the Malaysian government’s Financial Sector Blueprint 2022-2026, catalyzing the nation’s digital transformation and financial sector innovation.

A notable example is Alibaba Cloud’s Infrastructure as a Service (IaaS) solutions, particularly supporting Malacca Securities’ M+ global app. This digital trading platform offers Malaysians an intuitive and interconnected trading experience, enabling them to make informed decisions in the global markets.

Additionally, Alibaba Cloud’s financial solutions have significantly benefited major Malaysian clients like Permodalan Nasional Berhad (PNB) and Touch’n Go Digital. Adopting these solutions ensures adherence to rigorous security standards crucial for Financial Services Institutions.

Elevating logistics with cutting-edge AI

Alibaba Cloud has been instrumental in advancing Malaysia’s logistics industry, as evidenced by the success stories of EasyParcel and Global Track. EasyParcel, an online delivery service, has enhanced its operations through Alibaba Cloud’s AI technology. This has led to optimized delivery routes and improved overall logistics efficiency, improving EasyParcel’s customers’ experience.

Alibaba Cloud to help elevate Malaysia’s logistics industry. (Source – Alibaba Cloud).

Global Track, a smart logistics service provider in Malaysia, has effectively implemented real-time tracking systems using Alibaba Cloud’s AI capabilities. This technology has provided unparalleled visibility into the movement and security of goods, enhancing the security of the supply chain and offering valuable insights for optimizing business operations.

These success stories from EasyParcel and Global Track testify to Alibaba Cloud’s ability to combine global technological expertise with local innovation. This collaboration underscores Alibaba Cloud’s commitment to fostering a digitally resilient and efficient business landscape in Malaysia, enhancing customer experiences across various sectors.

Sustainability goals: Alibaba Cloud’s green initiatives

Alibaba Cloud supports various Malaysian industries in their sustainability efforts, including asset management, manufacturing, and the internet sector. This support centres around their energy expert platform, a Software-as-a-Service solution for sustainability and carbon management. This initiative aligns with Malaysia’s goal to achieve carbon neutrality by 2050.

The AI-driven energy expert platform enables enterprises to efficiently track, analyze, and manage carbon emissions from daily business activities. This collaboration between Alibaba Cloud and local enterprises accelerates business innovation, focusing on sustainable growth and helping companies manage their carbon neutrality strategies through data intelligence and AI technologies.

Key Malaysian companies are utilizing Alibaba Cloud’s energy expert solutions to advance their sustainability goals. UEM Edgenta Bhd has integrated this solution into its Edgenta NXT platform, automating the carbon emission calculation and certification process.

Meanwhile, Hond Tat Industries Sdn Bhd, a manufacturer of disposable hygiene products and polyethylene packaging, uses the platform to provide clearer information about carbon footprint reduction in its manufacturing processes. These efforts are part of a broader movement towards sustainable development in the Malaysian business landscape.

Overall, Alibaba Cloud’s contributions in 2023 have been pivotal in shaping a digitally advanced and sustainable future for Malaysia, demonstrating the company’s ability to blend global technological expertise with local innovation and commitment to fostering a digitally resilient business landscape.

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Last week, Singapore announced plans to develop Southeast Asia’s first large language model (LLM) ecosystem which it hopes can cater to the region’s diverse culture and languages. The concern was that most of the LLMs currently available had values and norms that catered more towards Western countries.

Just as Singapore’s LLM plans get into development, China’s Alibaba DAMO Academy has also unveiled SeaLLMs. Alibaba SeaLLMs is a pioneering LLM that comes with 13 billion parameter and 7 billion parameter versions that are specifically designed to cater to Southeast Asia’s diverse languages as well.

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While English is still widely spoken in the region, most countries still have their native languages that remain an important communication tool. For example, in Malaysia, while English is predominantly spoken, Malay is still the language used by government agencies for official communications. The same applies to Thailand, Indonesia, Cambodia, Laos, Vietnam and Myanmar. In the Philippines, English is a major language, but Tagalog is mostly used in communication.

The models are expected to offer optimized support for several local languages in the region. They include Vietnamese, Indonesian, Thai, Malay, Khmer, Lao, Tagalog and Burmese. SeaLLM-chat, the conversation model, shows adaptability to the unique cultural fabric of each market, aligning with local customs, styles, and legal frameworks, working as a chatbot assistant for businesses engaging with Southeast Asia markets.

“In our ongoing effort to bridge the technological divide, SeaLLMs is a series of AI models that not only understand local languages but also embrace the cultural richness of Southeast Asia. This innovation is set to hasten the democratization of AI, empowering communities historically underrepresented in the digital realm,” said Lidong Bing, director of the language technology lab at Alibaba DAMO Academy.

Echoing this sentiment, Luu Anh Tuan, Assistant Professor in the School of Computer Science and Engineering (SCSE) at Nanyang Technological University, commented, “Alibaba’s strides in creating a multilingual LLM are impressive. This initiative has the potential to unlock new opportunities for millions who speak languages beyond English and Chinese.”

The models help to reflect Southeast Asia’s diverse linguistic and cultural landscape.

Trying out Alibaba SeaLLMs

MABA, IndoBERT, and ThaiBERT are all examples of Southeast Asian large language models. They are trained on large corpora of texts from various sources, such as Wikipedia, news articles, social media posts, and books. They can perform various natural language processing tasks, such as text classification, sentiment analysis, question answering, and text summarization.

Alibaba explained that the SeaLLMs are open-sourced on Hugging Face, with released check point and available for research and commercial use. As such, Tech Wire Asia decided to try several prompts on the Malay and Tagalog language versions of the chat.

For Malay, a basic conversation with the chatbot seemed the same as what several Malay-speaking chatbots in Malaysia are already capable of. In fact, the conversation did not feel as natural as it would, but the model is still learning and is definitely able to improve. We also prompted a few Malay slang terms to the model to see if it could understand the local dialect. Unfortunately, the LLM is – at least for you – unable to do so.

For example, we prompted in a local dialect on where a good place would be to get “satay” in Kajang (a town famous for the dish in Malaysia). The LLM was unable to provide information about the restaurant but instead wanted to give directions to the restaurant – something could have gone wrong with the translation. Again, the model is still learning and we believe it will only get better over time.

TWA tried some Malay prompts.

Meanwhile, for Tagalog, while none of us at TWA speak the language, we used Google Translate to get some prompts and the results were interesting. Overall, Alibaba may have a solution that could be a game-changer, especially for businesses looking to utilize chatbots. The responses were generated rather fast and even though some prompts were not entirely accurate, the LLM could still get the gist of the message.

TWA also prompted Tagalog.

How does SeaLLM work?

According to a report by Alibaba DAMO researchers, SeaLLM-base models underwent pre-training on a diverse, high quality dataset inclusive of the languages from the region. This is to ensure a nuanced understanding of local contexts and native communication.

“The pre-training dataset of SeaLLMs is formed by documents from diverse public sources, including web texts (eg, Common Crawl), news documents (eg, CC-News), academic articles, and texts with expert knowledge (eg, Wikipedia). We first employ FastText language identifier to filter out the documents that do not belong to SEA languages. To further remove harmful or undesirable content, we develop a pipeline with various data cleaning and filtering modules to preprocess the collected data. Meanwhile, to maintain the English performance of SeaLLMs, we also introduce a set of high-quality English texts sampled from RedPajama-Data into pre-training,” researchers said.

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This foundational work lays the groundwork for chat models like SeaLLM-chat models, which benefit from advanced fine-tuning techniques and a custom-built multilingual dataset. As a result, chatbot assistants based on these models can not only comprehend but respect and accurately reflect the cultural context of these languages in the region, such as social norms and customs, stylistic preferences and legal considerations.

A notable technical advantage of Alibaba SeaLLMs is their efficiency, particularly with non-Latin languages. They can interpret and process up to nine times longer text (or fewer tokens for the same length of text) than other models like ChatGPT for non-Latin languages such as Burmese, Khmer, Lao, and Thai. That translates into more complex task execution capabilities, reduced operational and computational costs, and a lower environmental footprint. Note: TWA is unable to verify this but native speakers are welcome to give it a try and see how it works.

SeaLLM can interpret and process up to nine times longer text.

Alibaba also boasts SeaLLM’s 13 billion parameters. It claimed that SeaLLM-13B outshines comparable open-source models in a broad range of linguistic, knowledge-related, and safety tasks, setting a new standard for performance. When evaluated through the M3Exam benchmark (a benchmark consisting of exam papers from primary school to university entrance examination), SeaLLMs display a profound understanding of a spectrum of subjects, from science, chemistry, and physics to economics, in Southeast Asia languages, outperforming its contemporaries.

“SeaLLM-13b models exhibit superior performance across a wide spectrum of linguistic tasks and assistant-style instruction-following capabilities relative to comparable open-source models. Moreover, they outperform ChatGPT-3.5 in non-Latin languages such as Thai, Khmer, Lao, and Burmese,” the report said.

The SeaLLMs also excel in the FLORES benchmark. The FLORES benchmark assesses machine translation capabilities between English and low-resource languages—those with limited data for training conversational AI systems, such as Lao and Khmer. They surpass existing models in these low-resource languages and deliver performances on par with state-of-the-art (SOTA) models in most high-resource languages, such as Vietnamese and Indonesian.

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Alibaba Cloud has recently marked a significant achievement in the AI industry by becoming the first Chinese company to support Meta’s open-source AI model, Llama. This integration allows businesses using Alibaba Cloud in China to harness the capabilities of the Llama model for program development.

Expanding the LLM frontier: Alibaba Cloud’s new releases

Further expanding its footprint in the large language model (LLM) domain, Alibaba Cloud has announced the open sourcing of its own LLMs, Qwen-72B and Qwen-1.8B. Derived from its foundational model, Tongyi Qianwen, these versions feature 72 billion and 1.8 billion parameters, respectively. Now available on platforms like ModelScope and Hugging Face, these releases significantly widen the accessibility to advanced AI technologies.

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The company has further expanded its range of AI offerings by introducing additional multimodal LLMs, such as Qwen-Audio and Qwen-Audio-Chat. These are pre-trained and conversationally fine-tuned models focused on audio understanding, catering to research and commercial applications.

Alibaba Cloud’s contributions to AI are extensive, ranging from LLMs of various sizes – 1.8B to 72B parameters – to multimodal models equipped with audio and visual comprehension. Jingren Zhou, CTO of Alibaba Cloud, emphasizes the significance of an open-source ecosystem for the growth of LLMs and AI applications. “We aspire to become the most open cloud and make generative AI capabilities accessible to everyone. To achieve that goal, we’ll continue to share our cutting-edge technology and facilitate the development of the open-source community together with our partners,” Zhou said.

The 72-billion-parameter model, which has been pre-trained on more than 3 trillion tokens, is noted for outperforming other major open-source models across ten benchmarks. These include the Massive Multi-task Language Understanding (MMLU) benchmark, HumanEval for code generation, and GSM8K for arithmetic problems. The model is also proficient in complex tasks like role-playing and language style transfer, enhancing its suitability for various AI applications, such as personalized chatbots.

05122023_Qwen-72B outperforms other major open-source models in ten benchmarks. (Source – Alibaba Cloud).

The Qwen-72B model’s resources, including its code, model weights, and documentation, are freely available for research. Companies with less than 100 million monthly active users can also use the models without charge for commercial purposes.

Alibaba Cloud has made its 1.8-billion-parameter LLM available for edge computing, tailored for devices with limited computational capacity like smartphones. This more compact and efficient model, aimed at providing a cost-effective solution, is currently offered only for research purposes.

Diversifying AI: Multimodal LLMs and audio capabilities

In its commitment to offer LLMs capable of processing diverse input formats, Alibaba Cloud has also released Qwen-Audio and Qwen-Audio-Chat. These models boast enhanced audio understanding capabilities and are designed for research and commercial use. Qwen-Audio can interpret a variety of audio inputs, including human speech and natural sounds, and perform over 30 audio processing tasks. Its fine-tuned version, Qwen-Audio-Chat, is adept at conversational applications, including emotion and tone detection in human speech.

This latest initiative is part of Alibaba Cloud’s ongoing efforts to provide the open-source community with multimodal LLMs beyond text understanding. The company recently launched Qwen-VL and Qwen-VL-Chat, models skilled in visual information processing.

The open sourced models, including Qwen-7B, Qwen-14B, and Qwen-VL, have been downloaded over 1.5 million times on Alibaba Cloud’s ModelScope and Hugging Face since August. ModelScope has grown to be the largest AI model community in China, with many active developers and an impressive download count.

Developers are showing interest with the announcement made from Alibaba Cloud. (Source – X).

Alibaba International’s AI vision and Aidge’s launch

Leaders in AI, like Alibaba International, acknowledge the potential of these technologies. Jiang Fan, CEO of Alibaba International, remarks on AI’s transformative role: ” The use of AI has revolutionized everything from product development and management to market insights analysis and customer service.” Alibaba International plans to increase its AI investment to support global commerce, aiming to enhance merchant efficiency and customer satisfaction.

The launch of Aidge, Alibaba International’s AI-powered suite, exemplifies this commitment. Aimed at SMEs, Aidge – an acronym for “AI for Digital and Global Entrepreneurship” – utilizes Alibaba’s proprietary LLMs and computer vision technologies. It addresses market entry challenges for SMEs, helping them create localized marketing content, improve customer service, perform analytical tasks, and optimize search results without language barriers.

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Aidge promises to alleviate talent shortages and facilitate international growth for businesses of all sizes. It enables even small companies to explore new markets effortlessly with features that support smooth business adaptation.

Alibaba International is rolling out Aidge services to merchants on its e-commerce platforms, with plans to expand its reach through industry partnerships. Global SaaS providers and ISVs are invited to participate in pilot testing, with a regional rollout expected by year’s end.

The global AI market, set to exceed US$300 billion by 2026, underscores businesses’ need to embrace and capitalize on AI. Aidge empowers SMEs worldwide to conduct business in their native languages, leveraging advanced technology to compete in the global market.

The pilot launch of Aidge is just the beginning of Alibaba International’s AI journey. The company aims to collaborate with industry stakeholders to explore and define AI use cases, focusing on simplifying global business operations for SMEs and unlocking new growth opportunities with AI. This initiative reflects Alibaba International’s dedication to leveraging AI technologies to address the unique challenges SMEs face in the global marketplace.

As Alibaba International continues to pioneer in the AI space, its commitment to AI-driven solutions like Aidge represents a significant stride in enhancing the operational efficiency of SMEs. This approach helps small and medium-sized enterprises overcome language and cultural barriers and positions them competitively in the global market.

The global AI market’s rapid growth highlights the importance of such technological advancements for businesses looking to expand internationally. Alibaba International’s efforts to provide SMEs access to AI tools and technologies are crucial in driving the development of the global e-commerce industry.

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The pilot launch of Aidge by Alibaba International is a strategic move in AI aimed at empowering SMEs with advanced, accessible AI tools.

By making advanced LLMs like Qwen-72B and Qwen-1.8B more available, along with introducing multimodal models, the boundaries of AI are being expanded, paving the way for more innovative and inclusive AI solutions. These developments are crucial in a world increasingly reliant on AI, offering new opportunities for businesses, developers, and researchers to leverage AI in varied and impactful ways.

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At the recent annual Apsara Conference, Alibaba Cloud, the cloud computing arm of Alibaba Group Holding, announced several vital advancements, affirming its integral role in powering a vast majority of China’s tech enterprises and AI innovations.

Alibaba Cloud is the backbone for 80% of China’s technology companies, including half of the organizations working on AI and large language models (LLMs). This deep integration into China’s tech landscape highlights Alibaba Cloud’s vital position in national technological progress and AI strategy.

Joe Tsai, Alibaba Group Holding’s co-founder, underscored the strategic vision for Alibaba Cloud. He envisions it as the most user-centric and inclusive cloud platform in the AI epoch. Tsai’s statement, “We hope that through this cloud, it will become easier and affordable for everyone to develop and use AI,” reflects a broader commitment to democratizing AI technology. His words resonate with the company’s mission to simplify AI applications and make them financially accessible, marking a paradigm shift in the technological landscape.

AI innovations at the forefront: Alibaba Cloud’s strategic vision

Tsai’s remarks also reveal Alibaba Cloud’s ambition to dominate China’s cloud infrastructure sector, using AI to enhance productivity tools. This approach mainly aims to empower small and medium-sized enterprises (SMEs), letting them use AI to reap the rewards of innovation as competitive advantages in their business sector.

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A pivotal highlight of the conference was the introduction of Tongyi Qianwen 2.0, Alibaba Cloud’s advanced LLM, and several new industry-focused AI models. This move signals Alibaba Cloud’s direct competition with global giants such as Amazon and Microsoft. Tongyi Qianwen 2.0 embodies a significant leap forward in AI, reinforcing Alibaba Cloud’s commitment to pioneering AI research and facilitating business digitization.

The release of Tongyi Qianwen 2.0 demonstrates significant progress from its previous iteration. This model now sets new benchmarks, excelling in comprehensive tasks from language understanding to complex problem-solving and question-answering scenarios. Its enhancements lie in both its sheer size and in nuanced areas like interpretation accuracy, content generation, logical reasoning, memory retention, and error minimization.

By making Tongyi Qianwen 2.0 available to the public and to developers, Alibaba Cloud is pushing the boundaries of AI accessibility and practical application.

In line with the launch, Alibaba Cloud unveiled various industry-specific AI models designed to transform core business processes and decision-making across healthcare, finance, legal, and customer service sectors. These models aim to help businesses embrace generative AI, optimizing performance, and fostering innovative applications tailored to sector-specific needs.

Tongyi Qianwen 2.0 surpassed some leading large language models. (Source – Alibaba Cloud)

AI innovations: new training platforms and cloud products

Recognizing the explosive demand for powerful and versatile AI infrastructures, Alibaba Cloud announced an AI model training platform and a suite of novel cloud products. These platforms are intended to fully equip customers, developers, startups, and the broader community to leverage generative AI’s transformative potential.

With its new AI innovations, could Alibaba Cloud launch an assualt on other cloud-focused AI leaders?

The AI model training platform and cloud products underscore Alibaba Cloud’s resolve to support the burgeoning generative AI ecosystem. They offer state-of-the-art tools for AI development, spanning from data management to model training and prompt engineering. These innovations are geared to streamline AI integration across enterprise landscapes, meaning companies can construct and deploy bespoke AI solutions effortlessly.

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The new models and platforms are set to revolutionize how industries operate and innovate. With these tools, businesses – and particularly businesses in China – can unlock new levels of productivity and creativity, utilizing AI to gain insights, automate processes, and create novel customer experiences.

Jingren Zhou, CTO of Alibaba Cloud, gave some deeper insights into the company’s strategic direction. “To help businesses better reap the benefits of generative AI in a cost-effective way, we are launching a more powerful foundation model as well as industry-specific models to tackle domain-specific challenges,” he said. These initiatives aim to translate proprietary models into tangible value for clients, optimizing operations, and ensuring competitiveness in a rapidly evolving digital era.

Jingren Zhou, CTO of Alibaba Cloud, unveiled Tongyi Qianwen 2.0 at Apsara Conference. (Source – Alibaba Cloud)

Transforming enterprises and data management

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The launch of an array of pioneering cloud products further shows Alibaba Cloud’s commitment to facilitating generative AI development. These products include enhanced machine learning capabilities, container technology, and advanced database systems:

• Upgraded platform for artificial intelligence (PAI): this enhanced platform boosts the efficiency of training and deploying LLM models. It integrates increased computing power and improved storage and networking capabilities, positioning it as an ideal solution for AI and metaverse enterprises like Futureverse, which leverages PAI for developing its text-to-music generation models.
• Enhanced database solutions: Alibaba Cloud has fortified its range of database solutions, including PolarDB, AnalyticDB, and Lindorm, with a proprietary vector engine. The introduction of LLM-powered database ecosystem tools like the data management service (DMS) Data Copilot is a stride towards intelligent, analytics-assisted data handling.
• Alibaba cloud container compute service (ACS): unveiled as a pioneering serverless solution, ACS integrates container services with Alibaba Cloud’s computing resources. This innovative service allows businesses and developers to deploy Kubernetes resources cost-effectively and in user-friendly ways, supporting a scalable and efficient cloud infrastructure for application development.

Alibaba Cloud’s announcements at the Apsara Conference show a clear intention to lead the AI revolution. Through strategic innovations and enhanced offerings, the company is advancing technological capabilities and reshaping the future landscape of business and industry with AI.

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When it comes to technology, Alibaba Cloud has always made it clear that its technology is available for all. Given the pace of generative AI technology, the open-source community has also been working to develop new use cases and improve the capabilities of the technology.

While there are some concerns about how open-source code materials are being utilized by some generative AI tools, the general understanding is that everyone can still benefit from and contribute to the technology.

ALIBABA CLOUD TRANSFORMS ENTERPRISES WITH UNLIMITED COMPUTING POWER THROUGH CLOUD INNOVATIONS

Muhammad Zulhusni | 3 November, 2022

As such, Alibaba Cloud has launched two open-source large vision language models (LVLM). The models, Qwen-VL and Qwen-VL-Chat, can comprehend images, texts, and bounding boxes in prompts. The LVLM models can also facilitate multi-round question-answering in both English and Chinese.

What are large vision language models?

Similar to large language models (LLM), an LVLM is trained extensively on massive datasets containing images and corresponding textual descriptions. The model understands the relationship between visual content and natural language expressions. An extension of computer vision and natural language processing techniques, LVLMs facilitate tasks that involve processing and generating information in both visual and textual forms.

Hugging Face, an AI platform, breaks down LVLM into three key elements—an image encoder, a text encoder, and a strategy to fuse information from the two encoders. These essential components are intricately interconnected. LVLM continues to undergo significant changes. Prior approaches have utilized manually crafted image descriptors along with pre-trained word vectors or frequency-based TF-IDF features.

“LLMs have notably accelerated progress towards artificial general intelligence (AGI), with their impressive zero-shot capacity for user-tailored tasks, endowing them with immense potential across a range of applications. However, in the field of computer vision, despite the availability of numerous powerful vision foundation models (VFMs), they are still restricted to tasks in a pre-defined form, struggling to match the open-ended task capabilities of LLMs,” explain researchers on using LLM for vision-centric tasks.

In a research paper, researchers point out that an LLM-based framework for vision-centric tasks treats images as a foreign language and aligns vision-centric tasks with language tasks that can be flexibly defined and managed using language instructions.

The researchers also highlight that “an LLM-based decoder can then make appropriate predictions based on these instructions for open-ended tasks. Extensive experiments show that the proposed VisionLLM can achieve different levels of task customization through language instructions, from fine-grained object-level to coarse-grained task-level customization, all with good results.”

A Tweet on the new release by Alibaba Cloud.

Qwen-VL and Qwen-VL-Chat

Qwen-VL is the multimodal version of Qwen-7B, Alibaba Cloud’s 7-billion-parameter model of its large language model, Tongyi Qianwen. Qwen-VL is also available on ModelScope as open-source. It is capable of understanding both image inputs and text prompts in English and Chinese. Qwen-VL can perform various tasks such as responding to open-ended queries related to different images and generating image captions.

The features of Qwen-VL include:

• Strong performance – It significantly surpasses existing open-source LVLMs under similar scale settings on multiple English evaluation benchmarks, including Zero-shot caption, VQA, DocVQA, and Grounding.
• Multi-lingual LVLM supports text recognition – Qwen-VL naturally supports multi-lingual conversations and promotes end-to-end recognition of bilingual text in images in both Chinese and English.
• Multi-image interleaved conversations – This feature allows for the input and comparison of multiple images, as well as the ability to specify questions related to the images and engage in multi-image storytelling.
• First generalist model supports grounding in Chinese – Detecting bounding boxes through open-domain language expressions in both Chinese and English.
• Fine-grained recognition and understanding – Compared to the 224 resolution currently used by other open-source LVLMs, the 448 resolution promotes fine-grained text recognition, document QA, and bounding box annotation.

A demo of Qwen-VL. (Source – Alibaba Cloud)

Compared to other open-source large vision language models that can process and understand images in 224×224 resolution, Qwen-VL can handle image input at a resolution of 448×448, resulting in better image recognition and comprehension. Qwen-VL also recorded outstanding performance on several visual language tasks, including zero-shot captioning, general visual question-answering, text-oriented visual question-answering, and object detection.

Additionally, Qwen-VL-Chat caters to more complex interactions, such as comparing multiple image inputs and engaging in multi-round question-answering. The AI assistant leverages alignment techniques and exhibits a range of creative capabilities. This includes writing poetry and stories based on input images, summarizing the content of multiple pictures, and solving mathematical questions displayed in images.

In the benchmark test of Alibaba Cloud, Qwen-VL-Chat has also achieved leading results in both Chinese and English for text-image dialogue and alignment levels with humans. This test involved over 300 images, 800 questions, and 27 categories.

Multi-round question answering via the Qwen-VL-Chat model. (Source – Alibaba Cloud)

Alibaba Cloud and open source

In an interesting move by Alibaba Cloud, the tech company has shared the model’s code, weights, and documentation with academics, researchers, and commercial institutions worldwide. With democratizing AI technology on the agenda for most AI companies, the code is available to the open-source community via ModelScope and Hugging Face.

The introduction of these models, with their ability to extract meaning and information from images, holds the potential to revolutionize interactions with visual content. For instance, leveraging their image comprehension and question-answering capabilities, these models could provide informational assistance to visually impaired individuals during online shopping in the future.

Since these models have been open-sourced, the two models have garnered over 400,000 downloads within a month of their launch. For commercial uses, companies with over 100 million monthly active users can request a license from Alibaba Cloud.

The official repo of Qwen-VL (通义千问-VL) chat & pretrained large vision language model proposed by Alibaba Cloud.

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While Open AI’s ChatGPT and Google’s Bard dominate the news on generative AI chatbots, Chinese tech companies have also been developing their versions. In March 2023, Chinese search engine giant Baidu unveiled its Ernie Bot version. However, the excitement of Ernie Bot was short-lived as the technology could not cope at the same level as ChatGPT or Bard.

A month later, Alibaba Cloud unveiled its version of a ChatGPT-style product called Tongyi Qianwen. Compared to Ernie Bot, Tongyi Qianwen was more like ChatGPT and was quick to gain praise for its capabilities on Chinese social media.

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Now, Alibaba Cloud has announced that Tongyi Qianwen will be integrated into a digital assistant called Tingwu. Tingwu is an AI-powered meeting assistant developed by the Speech Lab of Alibaba DAMO Academy. The technology converts spoken meeting content into written minutes in real-time.

In a media statement, Alibaba Cloud stated that Tongyi Qianwen would enable Tingwu to comprehend and analyze multimedia content with high levels of accuracy and efficiency, such as generating summary text from video and audio files, capturing key talking points for each speaker, and creating a timeline of multimedia files with a summary of each section.

Additional AI features are expected to be available later this year. These features include automatically compiling text answers to address user queries across audio or video files, generating a summary based on PowerPoint slides extracted from videos, and providing real-time translation between English and Chinese for multimedia content with Tingwu as a Chrome plugin.

Available for public beta testing, the large language model (LLM) powered Tingwu called Tongyi Tingwu will also be integrated into DingTalk. DingTalk is Alibaba’s digital collaboration workspace application development platform, supporting users’ AI demands at work. The general public can access the upgraded AI-powered assistant online (tingwu.aliyun.com) to experience its capabilities through their Alibaba Cloud accounts.

“We live at a time when a growing amount of video and audio content is consumed in various formats daily. In line with this, Tongyi Tingwu aims to use the large language model to facilitate faster and better comprehension and easier multimedia content sharing,” said Jingren Zhou, CTO of Alibaba Cloud Intelligence.

Large language models are the core technology of generative AI. Conversational chatbots using LLM like Tingwu, ChatGPT, and Bard can generate better results based on the information they provide. As such, there has been some criticism of some of the results provided by these chatbots. This includes providing outdated information as well as generating results that are outside the prompt.

The US and China continue to compete with each other on technology supremacy. Chinese tech giants are investing heavily in improving their AI capabilities, especially after the government imposed stricter regulations and limits on the use of technology in some industries.

Apart from Alibaba and Baidu, Tencent also wants its own ChatGPT-style products. However, the company is in no hurry to develop the technology which could be embedded into its super app – WeChat. Huawei has also registered several patents that show the company’s interest in developing a human-to-AI conversation system.

The post Alibaba Tingwu in public beta after LLM integration appeared first on Tech Wire Asia.

New implementation models and best practices are developing as cloud technologies get better and are more frequently used. And more and more people believe that cloud computing is essential for businesses looking to operate wisely, focus on what they do best, and complete tasks more quickly. Alibaba Cloud is one of several companies advancing cloud computing as part of business innovations.

According to Gartner, global spending on public digital services will climb by 47% over 2020 to $397.5 billion in 2022. IDC, a market research company, projects that by 2024, total worldwide cloud computing spending will reach $1 trillion. Other emerging themes include new cloud delivery methods, technologies, operational models, security, and app development.

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At their annual Apsara Conference, Alibaba Cloud, the digital technology and intelligence core of the Alibaba Group, unveiled ModelScope, an open-source Model-as-a-Service (MaaS) platform with big pre-trained models for global developers and researchers. To further help customers achieve business innovation through cloud technologies, the world’s top cloud provider enhanced its integrated data analytics and intelligent computing platform and unveiled a variety of serverless database solutions during its flagship conference.

According to Jeff Zhang, President of Alibaba Cloud Intelligence, cloud computing has accelerated the integration of the cloud and endpoint terminals and caused a fundamental change in how computer resources are produced, structured, and used for commercial purposes.

“As more customers are speeding up with their cloud adoption, we have been upgrading our cloud-based resources, services and tools to become serverless, more intelligent and digitalized in order to lower the barrier for companies to adopt new technology and capture more opportunities in the cloud era,” explained Jeff.

What is MaaS?

For those unfamiliar with the concept, MaaS can be described as a “Software-as-a-Service” variation that addresses the requirement to make (environmental) models accessible as a web service. This method enables a model “service provider” to significantly reduce the workload for model users by providing model input data with the service and a suitable execution environment.

MaaS provides the ability to run simulation models as a service. MaaS concentrates on the model’s application to data. There are two principal usage styles: The model has a well-known service endpoint, may be pre-deployed, and may be supported by additional data services.

Over 300 ready-to-deploy AI models have been developed using the ModelScope platform by the Alibaba DAMO Academy (DAMO), Alibaba’s global research program, in the past five years. These models span a number of disciplines, including audio, computer vision, and natural language processing (NLP). The platform also has more than 150 state-of-the-art (SOTA) models known worldwide as the finest in their industries at completing a certain task.

Alibaba’s proprietary large pre-trained models, including Tongyi, a model with five billion parameters that can convert text into images, and OFA (One-For-All), a model with six billion parameters that excels at cross-modal tasks like captioning images and responding to visual questions, are also made available on the platform. The open-source platform has so far received dozens of models from independent developers.

ModelScope is an open-source community that strives to make developing and utilizing AI models simpler and more affordable. The models can easily be tested online for free by developers and researchers, who can quickly review the results. They can also create customized AI applications by optimizing pre-existing models, running them on Alibaba Cloud’s online platform, or deploying them locally or on other cloud platforms.

Alibaba Cloud boosts computing performance for business innovations

Alibaba Cloud is making its core cloud products serverless in order to keep up with the growing trend of serverless software development. This will allow customers to focus on product deployment and development without worrying about infrastructure management.

Examples are PolarDB, a cloud-native database, AnalyticDB (a cloud-native data warehouse), and ApsaraDB for Relational Database Service (RDS). Customers can benefit from extreme elasticity, automatic scalability, and a pay-as-you-go payment model using serverless technologies offered by Alibaba Cloud.

With a display of its applications on the Wuying Cloudbook, Alibaba Cloud has announced the debut of the Wuying Architecture to encourage workload collaboration between cloud and local hardware. The Cloudbook’s dedicated architecture is intended to make it easier for users to access limitless computing capacity in the cloud more securely and quickly, promoting workplace flexibility and collaboration.

The post Alibaba Cloud’s Model-as-a-Service platform to shape up business innovations appeared first on Tech Wire Asia.

Alibaba Cloud is one of the market’s most well-known cloud computing players, along with many other tech giants like Microsoft and Amazon. Although cloud innovations play a small part in Alibaba Cloud’s overall business, the company sees it as a crucial part of future growth and profitability.

In fact, Alibaba is ranked as the third largest Infrastructure-as-a-Service (IaaS) provider in the world and the biggest in Asia Pacific in 2021 by revenue, according to Gartner. The business was able to increase its individual worldwide market share across verticals including transportation, banking and investment services, insurance, manufacturing and natural resources, and wholesale trade, with revenue growth between 49-67.5% for these sectors from a year earlier.

As such, the company recently announced the latest additions to its cloud computing services at the Apsara Conference. The Wuying Cloudbook, powered by Wuying Architecture, offers businesses unlimited computing power while helping them improve cost effectiveness, data security, and collaboration in various hybrid office scenarios.

ALIBABA CLOUD PICKS KUALA LUMPUR AS CUSTOMER SERVICE CENTRE FOR REGIONAL SERVICES

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The Wuying Cloudbook draws on the high levels of security, scalability, and compatibility that define the cloud to enable users to fully utilize cloud computing while reducing the workload on local devices. Users are free from the capacity constraints of running large-scale applications, such as video-rendering software, and can have a real-time interactive experience with low latency and high-quality images by scaling processing power and storage up or down to meet their demands as and when they require.

Accelerating cloud innovations

By centralizing and controlling organizational resources in the cloud, Wuying Cloudbook enables the safe transmission and storage of large amounts of data. While enabling users to access organizational resources from any location, it solves common security issues in enterprise environments, such as data loss and local device vulnerabilities.

Alibaba Cloud Showcases Wuying Cloudbook at Apsara Conference 2022 (Source – Alibaba Cloud)

Wuying Cloudbook expands the possibilities for teamwork by enabling users to run different operating systems simultaneously, such as Windows, Linux, or Android. There is no need to download and install software on local devices because it is already deployed and running in the cloud, which reduces the need for storage space and battery usage of local devices. The Wuying Cloudbook is the best option for modern working practices like remote work, outsourcing, and collaboration among geographically dispersed teams.

Wuying Architecture, according to Jiangwei JIANG, Senior Researcher and General Manager of Infrastructure Products at Alibaba Cloud Intelligence, is a powerful development and extension of the workplace. It helps businesses in increasing their operational effectiveness and flexibility.

“Taking advantage of cloud-based data security capabilities and tools, Wuying provides additional assurance to safeguarding corporate information security,” said JIANG. “Thanks to its compatibility, Wuying Architecture brings the benefits of cloud computing to hardware brands, software vendors and enterprises, as well as individual users.”

A comeback from the flat revenue?

The Wuying Cloudbook’s sales will be interesting to see in light of the recent disclosure that Alibaba underwent a crazy downside correction and has been fluctuating in the $80-$120 range lately.

The Chinese regulator, who expressed concerns about a potential delisting and increased military activity in Taiwanese waters, was one of the headwinds that led to all of this. Additionally, a COVID-19 “comeback” in China resulted in the locking down of major cities, which evidently reduced high two-digit revenue levels to flat. In FY 2022, 90.7% of Alibaba’s income came from China, while just 9.3% came from elsewhere.

This does not, however, negate Alibaba Cloud’s strong cloud market commitment. The Chinese e-commerce behemoth has pledged to invest $1 billion over the next three fiscal years to support its cloud computing customers as it attempts to resurrect growth following a period of decline.

This has already shed some positive light on how Wuying can help Alibaba Cloud’s customers. The first automaker to use Wuying in product design in China is an intelligent electric car company called IM Motors. Teams from many places must work closely together during the R&D stage. Wuying allows several teams located in various places to access the design documents.

According to Jiao XIANG, Executive Director of Intelligence Research Center, IM Motors, the automobile industry has historically relied significantly on offline collaboration because many work procedures require large-scale workstations.

“Wuying is a dream come true for our sector. Not only does it offer the necessary computing power to support the intense workload, but it also eases our anxiety around data security when transmitting and sharing confidential design files, allowing us to focus our attention on the design itself,” he added.

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