According to IJIWEI News, two Indian government officials have revealed that India is considering Tesla’s request to reduce import duties on electric vehicles as an enticement for the company to establish a factory in the country.

Tesla has reportedly indicated that establishing a facility in India hinges on government concessions regarding import duties. Officials mentioned that Tesla insists on “at least a duty relaxation for a certain transition period” and added that “there would be sunset clauses.”

Currently, India imposes a 70% tax on imported cars under $40,000 USD to support the local automobile industry, while those above $40,000 USD face a 100% duty. India is contemplating reducing tariffs on all electric vehicles to 15%, regardless of their selling price, although there’s no unified consensus within the government.

As reported, the proposing officials hope that the aforementioned legislation will not only benefit India but also other qualifying manufacturers, instead of favoring a specific company alone.

Previously, there were reports suggesting Tesla’s intention to establish a factory in India for manufacturing low-cost electric vehicles, catering to the domestic market and planning for exports. However, Tesla’s 2022 plans for reduced import duties on electric vehicles were canceled as the Indian government insisted that the vehicles must be manufactured in India.

Over the past year, senior Tesla executives have met with Indian government officials at least three times. When Indian Prime Minister Narendra Modi visited the United States for an official visit in June this year, he met with Tesla CEO Elon Musk in New York to discuss the potential establishment of a plant in India.

(Photo credit: Pixabay)

According to IJIWEI’s news, during the Huawei Smart Mobility Conference held on November 9, Huawei, in collaboration with Chery, unveiled its first smart electric sedan, the Luxeed S7. Priced at a starting pre-sale cost of 258,000 RMB. Huawei had previewed the release of Luxeed S7 during a product launch event held on September 25th. “It will be superior to Tesla’s Model S in various aspects,” said Richard Yu, the CEO of Huawei.

The vehicle is produced on a new platform using Huawei’s smart automotive solution. It features the Huawei’s turing intelligent chassis, HarmonyOS 4 smart cockpit, and the advanced Huawei ADS 2.0 intelligent driving assistance system.

The Huawei ADS 2.0 advanced intelligent driving system is highlighted for its cutting-edge perception capabilities, obstacle recognition and processing abilities, and advanced features in intelligent driving and smart parking. The ADS 2.0 achieves a leading experience with nationwide map-agnostic driving, intelligent parking assistance, and continuous improvement over time, making it a top-tier intelligent driving system.

In terms of appearance, the Luxeed S7 incorporates an entirely new OneBox design to maximize the interior space, achieving a cabin space utilization rate of 88%. Richard Yu mentioned that after numerous internal discussions about pricing, it was found that all four versions of this car would incur losses. The hope lies in later substantial shipments of the car to offset these losses.

According to the introduction, the Luxeed S7 offers an impressive 800 kilometers of range, and a quick 15-minute charge can cover 400 kilometers. Richard Yu stated that in terms of energy consumption, the Luxeed S7 once again leads the industry with an energy consumption of 12.4 kWh per 100 kilometers.

Yu further mentioned that Huawei supports its partners in achieving commercial success through three cooperation modes: component supply mode, solution mode, and Huawei Smart Car mode. Currently, Huawei’s Smart Car model has four partner companies, including Seres, Chery, JAC Motors, and BAIC Group.

Currently, the Aito Series, including the M5, has seen cumulative deliveries surpass 120,000 vehicles, with the newly introduced M7 series achieving a cumulative sales total of 86,000 units. Even before its official release, the upcoming Aito Series M9 has received more than 25,000 pre-orders.

According to the introduction, Huawei’s Smart Travel Solution represents a strategic advancement in the Huawei Smart Choice Car model. It aims to leverage Huawei’s over 30 years of intelligent incremental component products in the ICT domain, technological solutions, and Huawei’s quality control, sales service, and brand marketing experiences accumulated over more than ten years in consumer businesses, deeply empowering partners to pioneer a new era of smart vehicles.

(Photo credit: Flickr)

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)

Ford announced the withdrawal of its full-year financial forecast due to the impact of the recent labor strike and ongoing challenges in the EV sector. Most consumers are reluctant to pay higher prices for electric cars compared to traditional or hybrid vehicles. Ford also postponed its planned $12 billion investment in expanding electric vehicle production capacity but remains committed to its goal of advancing its electric vehicle business.

TrendForce’s Insights:

1. Slower Market Demand Spurs Automakers to Rethink EV Strategies

The United Auto Workers (UAW) union initiated a six-week strike in Detroit starting on September 15, 2023, motivated by demands for improved compensation and benefits. The strike came to an end when consensus was reached with Ford, Stellantis, and GM (General Motors), resulting in the signing of a new contract.

According to predictions from Deutsche Bank, this new agreement will add an estimated $6.2 to $7.2 billion in costs for each of the three major automakers. This cost increase is nearly equivalent to the expense of building an electric vehicle platform. Compounded by the impact of slowing demand for global new energy vehicles (BEV and PHEV), with growth rates decreasing from 54% in 2022 to 30% in 2023, Ford announced the suspension of its $12 billion electric vehicle investment plan. This plan includes its partnership with SK On for a battery factory and a partly reduction in production capacity for the Mustang Mach-E.

2. Automakers Must Adopt More Practical EV Development Strategies to Address Price and Range Concerns

The slowdown in electric vehicle market demand stems from the issues of high vehicle prices and range anxiety, which affect consumer willingness to make a purchase. Addressing these two problems requires increasing battery energy density to achieve comparable driving range to conventional vehicles and constructing an adequate charging infrastructure. However, achieving these goals will take time and effort.

With range anxiety still unresolved and the goal of banning fossil fuel vehicles unchanged, automakers positioned between policy and the market face transition risks. At this juncture, choosing to independently develop electric vehicle platforms might add financial burden and risk, with the associated costs reflected in vehicle prices, potentially eroding competitiveness. A more practical approach would involve considering alternative development strategies, such as exploring platform outsourcing to reduce manufacturing costs.

Automakers or Tier 1 suppliers with proprietary electric vehicle platforms have the option to lease their platform production capacity to companies that are currently unable or unwilling to independently develop their own platforms. This strategy can increase production efficiency for lessees, allowing them to commission the production of all or some of their electric vehicle models from the lessor, ultimately reducing manufacturing costs and accelerating the release of new vehicle models.

By doing so, companies can maintain their market share in the electric vehicle race while waiting for the right opportunity to reevaluate the potential for developing their own electric vehicle platforms. In summary, as the demand for electric vehicles slows down, automakers will face tighter financial constraints, making it crucial for them to explore how to collaboratively leverage existing resources to create electric vehicles that align with market demands.

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• [News] Ford Shifts EV Investment Focus Amidst Fierce Price Competition

(Photo credit: Ford’s Facebook)

According to Yahoo’s report, recent developments in China’s automotive industry, particularly the electric vehicle sector, have been a mixed bag. While some companies have reported impressive export performance and surging delivery volumes, the overall market has faced challenges due to weak consumer demand and intense price wars.

Even NIO, which had previously pledged to enhance efficiency without layoffs, recently announced a workforce reduction of approximately 10%, affecting around 3,000 employees. This unexpected move has sent shockwaves through the industry and suggests that a layoff storm may be approaching the Chinese automotive sector.

Amidst numerous recent developments in the Chinese auto market, the most widely discussed topic is the announcement by NIO’s Chairman, William Li, regarding a workforce reduction of approximately 10%, with specific adjustments to be completed by November.

NIO, known as a market favorite and listed in both the U.S. and Hong Kong, has been considered one of the leading players in China’s new force of automotive companies. However, it now finds itself in the challenging position of staff downsizing, signaling a potentially tough year-end for China’s automotive industry.

While NIO, XPeng, and Li Auto, often hailed as representatives of the new forces in China’s automobile industry, had been at the forefront, NIO’s performance in 2023 seems to be lagging behind its peers.

In contrast to Li Auto, which has seen ten consecutive months of rising sales figures this year, and XPeng, which achieved a 292% year-on-year increase in October and set its record for single-month deliveries, NIO’s performance has been more volatile. Since reaching a peak delivery volume of 20,462 vehicles in July, NIO has struggled to maintain a consistent delivery rate of 20,000 vehicles per month.

Additionally, NIO’s losses have continued to grow quarter by quarter, with the company posting over ¥20 billion in net losses over the past year. In the same period, Li Auto recorded nearly ¥2 billion in profits, while XPeng faced losses of nearly ¥10 billion. Consequently, NIO holds the distinction of being the leader in losses among the new energy vehicle manufacturers. NIO’s layoffs serve as a cautionary signal, highlighting the pressing need to cut costs and enhance efficiency.

Amid China’s economic slowdown and intensified market competition, NIO’s challenges represent just a microcosm of the broader Chinese automotive industry. It’s not just NIO; in 2023, several automotive companies have already begun layoffs or faced closures. Examples include Levdeo, which filed for bankruptcy; WM Motor, which already closed its doors; and Enovate, which announced a suspension of operations.

Furthermore, the chill in the market is also affecting automotive supply chain companies. An industry insider candidly revealed that except for BYD and Li Auto, most car manufacturers are in the process of downsizing, indicating that the Chinese automotive industry is currently experiencing a major shake-up and a fierce battle for survival.

(Photo credit: Pixabay)