Recently, as Indian media cited anonymous sources, that the Indian law enforcement agency arrested three executives of Vivo India Company on charges of alleged involvement in a money laundering case.

As per The Times of India, the individuals arrested by the Indian law enforcement agency in this case are Hong Xuquan, the interim CEO of vivo India, along with Harinder Dahiya, the CFO of Vivo India, and the company consultant Hemant Munjal.

The three have been taken into custody under the provisions of the Prevention of Money Laundering Act (PMLA). Reportedly, an ED spokesperson did not immediately respond to a request for a comment. Furthermore, the Vivo employees is said to be appear in court on December 26.

Vivo spokesperson has responded accordingly that, “We are deeply alarmed by the current action of the authorities. The recent arrests demonstrate continued harassment and as such induce an environment of uncertainty amongst the wider industry landscape. We are resolute in using all legal avenues to address and challenge these accusations.”

According to The Times of India, in October of this year, the Indian law enforcement agency arrested four individuals, including Vivo’s chartered accountant Nitin Garg.

The report further states that from 2014 to the present, Vivo India has been allegedly probing suspicious transactions, which were remitted by the company to China from Rs 1.25 lakh crore of receipts from its Indian operations since 2014

“Various Chinese nationals have been traveling across India, including sensitive places of Jammu and Kashmir and Ladakh, in gross violation of Indian visa conditions.” the agency added.

Previously, as per  Hindustan Times, the Indian government banned numerous Chinese apps, accusing them of being “prejudicial to the sovereignty and integrity of India, defence of India, security of the state and public order.” Since June 2020, more than 200 Chinese apps, including popular ones such as TikTok, WeChat, and UC Browser, have been banned.

The government has also stated in its parliament indicating that, Chinese smartphone makers, including Xiaomi, Realme, Oppo, and Vivo, have been found evading taxes to the tune of Rs 9,000 crore in India.

(Photo credit: Vivo)

In the episode of CCTV’s “Face to Face” program aired on the evening of December 17, Xiaomi Group’s founder and chairman, Lei Jun, was interviewed and discussed Xiaomi’s efforts in the high-end and automotive sectors.

Lei Jun told reporters that he believes Xiaomi has many natural advantages in entering the automotive industry. He emphasized that the essence of smart electric vehicles today lies in the integration of the automotive and consumer electronics industries, constituting a significant convergence. Therefore, entering the automotive sector poses challenges for Xiaomi, but overall, the difficulty is manageable.

Lei Jun mentioned that three years ago, he thought making cars was a challenging endeavor. After conducting user research, they established the principle of adhering to conventions while introducing surprises: fully respecting the norms of the automotive industry, using mature industry technologies to ensure the quality of the first car, and innovating within this overarching framework.

Lei Jun stated, “For our first car, we’ve invested more than 3,400 engineers, and the entire research and development expenditure has exceeded RMB 10 billion. We’ve used more than ten times the investment. With this level of confidence, I approached it with a ‘must-win’ attitude.”

When discussing expectations for the first car, Lei Jun mentioned that there is definitely an expectation, but he acknowledges the complexity of the automotive industry. He expressed concerns, particularly fearing that the car might not gain immediate popularity, and people may not buy it initially.

However, he is even more worried that if everyone rushes to buy, there might be a wait of one or two years, which would undoubtedly lead to severe criticism.

Previous reports indicated that Xiaomi’s inaugural car aims to deliver 300 units in December, with preparations currently in progress for exhibition vehicles.

Earlier on December 12, information about Xiaomi’s car model SU7 battery appeared in the latest catalog of new energy vehicle models exempt from vehicle purchase tax released by the Ministry of Industry and Information Technology.

The information shows that Xiaomi’s car model SU7 has two battery versions with capacities of 101kWh and 73.6kWh, respectively. Depending on the specific model, the corresponding CLTC (China Light-Duty Vehicle Test Cycle) range for the 101kWh version is 800km and 750km, while for the 73.6kWh version, it is 668km and 628km.

(Photo credit: China’s Ministry of Industry and Information Technology)

This year, BYD, a notable figure in the global automotive market, has recently faced a downturn. The extensive price reductions initiated on November 24th have raised concerns, as it is perceived to contradict the company’s earlier commitment to avoid participating in price wars. BYD is now under pressure to intensify its efforts to reach its annual sales target of 3 million vehicles.

According to multiple reports from Chinese media on November 25th, in an attempt to overcome this challenging situation, BYD has been taking frequent actions. Following a wave of promotional activities in early November, on 24th, dealers reportedly implemented large-scale price reductions, expanding cash discounts to various models such as Qin, Han, Tang, and Song, ranging from CNY 3,000 to 10,000.

The discounts on models like Qin PLUS DM-i and Qin PLUS EV are particularly significant, reaching up to CNY 10,000, with the starting price of Qin PLUS DM-i dropping to CNY 89,800.

BYD Chairman Wang Chuanfu emphasized at the end of August that he was confident in achieving the annual sales target of 3 million vehicles and would not engage in intense price wars within the industry.

The recent measures of BYD, involving two price reductions within a month, have sparked discussions. BYD stated on November 25th that this promotion is limited to the month and is not an official price reduction activity. Its purpose is to accelerate the transition from gasoline-powered cars to electric vehicles.

The market is closely watching whether BYD can achieve its annual target. BYD’s official Weibo account stated on November 24th that it took just over three months to go from 5 million to 6 million units of EVs, marking another milestone. Moreover, in October, the sales of new energy vehicles exceeded 300,000 vehicles for the first time, setting a new monthly record.

However, while BYD’s monthly sales continue to grow, the year-to-date sales growth has significantly declined. In the next two months, BYD’s sales still need to climb above the 300,000 mark to achieve the 3 million annual target. Industry insiders suggest that BYD’s recent price reductions may boost its sales target but are also expected to intensify market price competition.

In addition, BYD faces threats from local competitors. Recently, various forces in the Chinese auto market have made significant deployments. The Huawei Luxeed S7 is set to be launched on November 28, and Huawei showcased a video on the 24th demonstrating the autonomous parking function of the Luxeed S7, highlighting its powerful technological capabilities.

Furthermore, Xiaomi’s progress in the car manufacturing sector continues to advance, with its new car expected to debut in the first quarter of 2024. The competition in the Chinese new energy vehicle market is, without a doubt, increasing.

Read more

• [News] Amid Chinese Car Price War, Tesla Takes a Step Back, while BYD Secures Sales Crown

Xiaomi’s venture into automotive industry takes a significant stride as the company’s latest models, SU7 and SU7 Max, makes its debut in the latest catalog from China’s Ministry of Industry and Information Technology. The listed entity is Beijing Automotive Group Co., Ltd. (BAIC), marked by the distinctive “Beijing Xiaomi” emblem on the rear.

Sources from Xiaomi’s car supply chain suggest an imminent small-scale trial production phase, hinting at the first model’s market introduction in February 2024, reported by UDN News.

As per the disclosure, the cars boast a 3,000mm wheelbase. SU7 will feature Fdbatt’s lithium iron phosphate batteries, and SU7 Max is complemented by CATL’s ternary lithium batteries. Interestingly, the smart driving features will not include an optional optical radar package.

The catalog showed Xiaomi’s car brand as Xiaomi, while the declared corporate entity is Beijing Automotive Group Off-Road Vehicle Co., Ltd. (BAIC ORV). The product’s rear proudly displays “Beijing Xiaomi.”

Despite leveraging BAIC’s production qualifications, Xiaomi’s car has its declared production address at the site of its self-established factory.

The car factory’s construction unfolds in two phases, with the first, covering approximately 720,000 square meters, achieving an annual capacity of 150,000 vehicles by June 2023. The second phase is slated to commence in 2024, concluding in 2025. Public records confirm the successful acceptance inspection of Xiaomi’s car first phase factory workshops on June 12.

Xiaomi Group Chairman Jun Lei’s October announcement highlighted smooth progress, anticipating an official launch in the first half of 2024.

Since Lei’s announcement of Xiaomi’s foray into smart cars, industry observers have closely monitored Xiaomi’s car dynamics. Internal sources reveal that Xiaomi’s car will leverage ICT industry experience to enhance operational efficiency across research, production, supply, and sales.

Xiaomi plans a US$10 billion investment in the automotive sector over the next decade. Operating in a wholly-owned model, Xiaomi aims to provide users with a comprehensive smart ecosystem and enrich their smart living experiences.

At the October Xiaomi product launch, the introduction of the HyperOS was a highlight, applicable not only to mobile devices but also set to feature in Xiaomi’s cars.

A notable addition revealed by National Business Daily, citing a supplier who visited Xiaomi’s car factory, is that the four major manufacturing process production lines (stamping, welding, painting, and final assembly) in Xiaomi’s car first phase factory are operational, engaging in small-scale trial production. With mass production scheduled to commence in December, Xiaomi’s car is poised for market launch in February next year.

(Image: China’s Ministry of Industry and Information Technology)

The fusion of AIGC with end-user devices is highlighting the importance of personalized user experiences, cost efficiency, and faster response times in generative AI applications. Major companies like Lenovo and Xiaomi are ramping up their efforts in the development of edge AI, extending the generative AI wave from the cloud to the edge and end-user devices.

On October 24th, Lenovo hosted its 9th Lenovo Tech World 2023, announcing deepening collaborations with companies like Microsoft, NVIDIA, Intel, AMD, and Qualcomm in the areas of smart devices, infrastructure, and solutions. At the event, Lenovo also unveiled its first AI-powered PC. This compact AI model, designed for end-user applications, offers features such as photo editing, intelligent video editing, document editing, and auto task-solving based on user thought patterns. 

Smartphone manufacturers are also significantly extending their efforts into edge AI. Xiaomi recently announced their first use of Qualcomm Snapdragon 8 Gen 3, significantly enhancing their ability to handle LLMs at the end-user level. Xiaomi has also embedded AI LLMs into their HyperOS system to enhance user experiences.

During the 2023 vivo Developer Conference on November 1st, vivo introduced their self-developed Blue Heart model, offering five products with parameters ranging from billions to trillions, covering various core scenarios. Major smartphone manufacturers like Huawei, OPPO, and Honor are also actively engaged in developing LLMs.

Speeding up Practical Use of AI Models in Business

While integrating AI models into end-user devices enhances user experiences and boosts the consumer electronics market, it is equally significant for advancing the practical use of AI models. As reported by Jiwei, Jian Luan, the head of the AI Lab Big Model Team from Xiaomi, explains that large AI models have gain attention because they effectively drive the production of large-scale informational content. This is made possible through users’ extensive data, tasks, and parameter of AI model training. The next step in achieving lightweight models, to ensure effective operation on end-user devices, will be the main focus of industry development.

In fact, generative AI’s combination with smart terminal has several advantages:

1. Personal data will not be uploaded to the cloud, reducing privacy and data security risks.
2. AI models can connect to end-user databases and personal information, potentially transforming general AI LLMs into personalized small models, offering personalized services to individual users.
3. By compressing AI LLMs and optimizing end-user hardware and software, edge AI can reduce operating costs, enhance response times, and increase service efficiency.

Users often used to complain about the lack of intelligence in AI devices, stating that AI systems would reset to a blank state after each interaction. This is a common issue with cloud-based LLMs. Handling such concerns at the end-user device level can simplify the process.

In other words, the expansion of generative AI from the cloud to the edge integrates AI technology with hardware devices like PCs and smartphones. This is becoming a major trend in the commercial application and development of large AI models. It has the potential to enhance or resolve challenges in AI development related to personalization, security and privacy risks, high computing costs, subpar performance, and limited interactivity, thereby accelerating the commercial use of AI models.

Integrated Chips for End-User Devices: CPU+GPU+NPU

The lightweight transformation and localization of AI LLMs rely on advancements in chip technology. Leading manufacturers like Qualcomm, Intel, NVIDIA, AMD, and others have been introducing products in this direction. Qualcomm’s Snapdragon X Elite, the first processor in the Snapdragon X series designed for PCs, integrates a dedicated Neural Processing Unit (NPU) capable of supporting large-scale language models with billions of parameters.

The Snapdragon 8 Gen 3 platform supports over 20 AI LLMs from companies like Microsoft, Meta, OpenAI, Baidu, and others. Intel’s latest Meteor Lake processor integrates an NPU in PC processors for the first time, combining NPU with the processor’s AI capabilities to improve the efficiency of AI functions in PCs. NVIDIA and AMD also plan to launch PC chips based on Arm architecture in 2025 to enter the edge AI market.

Kedar Kondap, Senior Vice President and General Manager of Compute and Gaming Business at Qualcomm, emphasizes the advantages of LLM localization. He envisions highly intelligent PCs that actively understand user thoughts, provide privacy protection, and offer immediate responses. He highlights that addressing these needs at the end-user level provides several advantages compared to solving them in the cloud, such as simplifying complex processes and offering enhanced user experiences.

To meet the increased demand for AI computing when extending LLMs from the cloud to the edge and end-user devices, the integration of CPU+GPU+NPU is expected to be the future of processor development. This underscores the significance of Chiplet technology.

Feng Wu, Chief Engineer of Signal Integrity and Power Integrity at Sanechips/ZTE, explains that by employing Die to Die and Fabric interconnects, it is possible to densely and efficiently connect more computing units, achieving large-scale chip-level hyperscale computing.

Additionally, by connecting the CPU, GPU, and NPU at high speeds in the same system, chip-level heterogeneity enhances data transfer rates, reduces data access power, increases data processing speed, and lowers storage access power to meet the parameter requirements of LLMs.

(Image: Qualcomm)