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… traditional strategy: price cuts.
Since launch, the Camry has undergone multiple rounds of price reductions. Initially priced at RMB 171,000 (USD 23,940), the model can now be purchased for less than RMB 140,000 (USD 19,600). Even the Avalon, positioned slightly above the Camry, has seen its price drop below RMB 150,000 (USD 21,000).
However, for Toyota, price cuts come at the expense of dealer profitability. A dealership insider told 36Kr that the wholesale price dealers pay for Toyota vehicles typically ranges from 90–95% of the official retail price, depending on the model and timing. "Right now, most Toyota cars are selling at 70% to 80% of their original price—meaning dealers are selling at a loss." The only way for dealers to stay afloat is by relying on year-end rebates from Toyota.
With low margins and declining demand, some dealers are exiting the business altogether. "Last year, especially in central cities like Wuhan, Toyota dealers exited in large numbers," an industry source said.
Toyota’s decision to consolidate its twin models is a direct response to this profit erosion.
In fact, resource integration is becoming an industry-wide trend. Geely, for example, recently merged its Zeekr and Lynk &amp; Co brands, shifting from aggressive expansion to a more strategic resource optimization approach. Meanwhile, Honda and Nissan have also announced their own <a href="https://kr-asia.com/honda-and-nissan-in-merger-talks-to-secure-ev-future">consolidation plans</a> to tackle declining sales and operational challenges.
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Unlike some global automakers that are taking a cautious approach in China, Toyota is betting big. It aims to boost its annual production in China to 2.5–3 million vehicles by 2030, an 80% increase from its 2024 sales of 1.776 million units.
To achieve this, Toyota is ramping up investments in localized R&amp;D. Its Toyota IEM R&amp;D Center is spearheading developments in intelligent and electric vehicle technology.
Li, the newly appointed general manager of Toyota China, also recently shared that starting in 2025, Toyota will build a dedicated R&amp;D system in China, mirroring Volkswagen’s strategic shift.
From technology partnerships with Huawei to investments in range-extender systems and small-engine plug-in hybrids, Toyota is charting an aggressive course for China’s evolving market.
KrASIA Connection features translated and adapted content that was originally published by 36Kr. This <a href="https://36kr.com/p/3131886737267465">article</a> was written by Xu Caiyu for 36Kr.

Toyota shakes up its China strategy as sales slip

East Asia

Japan

Toyota

Transportation

Electric Vehicles

Mobility

China

The tech industry and stock markets have been trying to grasp how a small, relatively unknown Chinese company was able to develop a sophisticated artificial intelligence chatbot on par with <a href="/company/openai">OpenAI's</a> ChatGPT at a fraction of the cost.
One possible answer being floated in tech circles is distillation, an AI training method that uses bigger "teacher" models to train smaller but faster-operating "student" models.
<a href="/company/deepseek">DeepSeek</a> claims to have achieved a similar level of performance as OpenAI's o1 model at a fraction of the cost through "optimized codesign of algorithms, frameworks, and hardware."
This sparked a sharp selloff in tech shares as investors considered whether the Chinese company's low-budget approach signaled the end of the AI investment race and the dominance of US tech giants.
But questions soon arose, with some in the industry speculating that the company had piggybacked on OpenAI's developments.
Such speculation was fueled when Bloomberg reported that Microsoft and OpenAI had launched a probe into whether DeepSeek improperly obtained data from OpenAI to train its own model. OpenAI told the Financial Times on January 28 that it has seen evidence of distillation, though it did not make that evidence public.
<a href="/company/microsoft">Microsoft</a> and DeepSeek did not immediately respond to Nikkei Asia's request for comment.
Distillation itself is not a new technique and is not necessarily controversial. <a href="/company/nvidia">Nvidia's</a> Minitron and Falcon 3, which was developed by the Technology Innovation Institute in the UAE, both used the technique, likely using their own families of large language models (LLMs) as the teacher. It has become increasingly popular since 2024 amid demand from businesses wanting to utilize LLMs in their services.
Big LLM models, however, are "difficult to handle, and you would need a vast number of graphics processing units (GPUs) for its deployment," said an engineer at an AI startup in Japan.
GPUs are the main reason AI systems are so expensive. Nvidia's signature H100 chips, for example, can cost USD 30,000–35,000 each. Distillation drastically cuts development time and costs, and results in models that can operate faster than their bigger counterparts.
The issue for DeepSeek is whether its low-cost model is based more on distillation than innovation.
"There is a question on whether they're able to use existing large language models to distill their results," Kirk Boodry, an analyst at Astris Advisory Japan, told Nikkei Asia. "It seems to be coming up quite a bit in discussion. People are like, 'I don't know how much of this is really cutting edge.'"
Kazuhiro Sugiyama, consulting director at Omdia, is skeptical that DeepSeek could drastically disrupt the current AI ecosystem. Its impact is "temporary and limited," he said, pointing out that although the Chinese company's chatbot shows signs of impressive innovation, the industry still needs to verify how much it holds up.
Analysts have also questioned whether the Chinese chatbot was indeed developed with a fraction of the budget of Western counterparts.
"When people talk about [DeepSeek's] headline numbers, like a couple months of development, [or spending] USD 6 million, what they're talking about is this very specific [model]," said Boodry from Astris. "The numbers that people are throwing around are probably way too low."
The Chinese company released a paper in December 2024 which set the figure for its V3 model at USD 5.6 million. This does not include costs associated with prior research and experiments. The training cost of OpenAI's GPT-4, is estimated to exceed USD 100 million.
Sugiyama said more companies will likely enter the race to develop LLMs, but the market position of the big players, including OpenAI, will probably not change. AI models will gradually "polarize," he predicted, with big companies like Microsoft and <a href="/company/google">Google</a> continuing to invest in bigger and more powerful models to be used on their services, and smaller players developing smaller, cheaper and more efficient models that are tailored to specific markets.
Hype aside, engineers do not doubt that DeepSeek has accomplished something that deserves to be acknowledged.
Even if the company used distillation, that alone would not be enough to develop a functioning model, according to one engineer. "It will need know-how to utilize GPUs efficiently and also come up with a way to do complex training," such as combining different models to come up with a better answer.
Another AI engineer said he was "not surprised" that a company like DeepSeek suddenly appeared. "There is a big trend of reducing the size of the AI model. … Over time, there will be many ways to achieve this."
This article first appeared on <a tabindex="0" href="https://asia.nikkei.com/Business/Technology/What-is-AI-distillation-and-what-does-it-mean-for-OpenAI" rel="noopener noreferrer" data-token-index="1">Nikkei Asia</a>. It has been republished here as part of 36Kr’s ongoing <a tabindex="0" href="https://www.kr-asia.com/nikkei-teams-up-with-36kr-in-asia-tech-news-coverage/" rel="noopener noreferrer" data-token-index="3">partnership with Nikkei</a>.

What is AI distillation and what does it mean for OpenAI?

Artificial Intelligence

Deep Tech

Foundation and Large Models

<a href="/company/alibaba-cloud">Alibaba Cloud</a> has introduced <a href="https://qwenlm.github.io/blog/qwen2.5-max/">Qwen 2.5-Max</a>, its latest artificial intelligence model, claiming it outperforms OpenAI’s GPT-4o, Meta’s Llama-3.1-405B, and DeepSeek-V3 across multiple benchmarks. The announcement comes as AI development in China gains momentum, with new players entering the space and established firms adjusting their strategies.
In recent weeks, <a href="/company/deepseek">DeepSeek</a> has gained traction with a different approach to AI. Its V3 model, introduced late last year, was reportedly trained on a budget of just USD 5.6 million, a fraction of what larger firms typically spend. Then, just before the Lunar New Year, DeepSeek followed up with R1, a model said to be on par with OpenAI’s GPT-o1.
Unlike models that depend on large-scale computing infrastructure, DeepSeek has prioritized efficiency and lower costs. This approach has <a href="https://kr-asia.com/a-new-ai-disruptor-businesses-rush-to-integrate-deepseek-r1">attracted interest</a> from businesses seeking a balance between AI performance and cost-effectiveness. Amazon Web Services and Microsoft—an OpenAI backer—have also added R1 to their model catalogs, further raising its visibility.
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Meanwhile, Alibaba is taking a different route. With Qwen 2.5-Max, the company is focusing on both AI performance and cloud infrastructure. The model is part of a broader rollout that includes a series of upgraded cloud computing services aimed at enhancing efficiency for AI applications.
To drive adoption, Alibaba Cloud is also launching a generative AI "empowerment program," offering free cloud credits, training, and co-marketing opportunities for developers and businesses using Qwen models. In its statement, Alibaba said the goal is to support AI adoption across industries while equipping enterprises with the tools to scale their applications.
For Beijing, these developments are likely encouraging. The releases of Qwen 2.5-Max and DeepSeek’s latest models signal China’s growing role in the global AI sector. Once viewed as trailing industry leaders like OpenAI, Meta, and Google, China’s AI firms are now demonstrating their ability to compete on equal footing—and, in some cases, exceed expectations set by global counterparts.

Alibaba Cloud fires back in the AI race with Qwen 2.5-Max

Alibaba Cloud

… for success through imitation or following trends.
Instead, markets can now only be gained and sustained through continued innovation. To stay ahead, both new ideas and a willingness to pursue less conventional paths are quintessential.
KrASIA Connection features translated and adapted content that was originally published by 36Kr. This <a href="https://36kr.com/p/3135411079535110">article</a> was written by Xiao Xi for 36Kr.
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Forget the price wars—MiniMax goes open-source to rewrite the AI playbook

MiniMax

… Quotient.</li>
</ul>
If there are any news or updates you'd like us to feature, get in touch with us at: <a href="mailto:hello@kr-asia.com">hello@kr-asia.com</a>.
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Deals in brief: Clime Capital invests in Ampotech, Nibertex raises pre-Series A funding, Alpha JWC targets fourth fund, and more

Venture Capital

Private Equity

Investment

Merger &amp; Acquisition

Singapore

Southeast Asia

… vehicle adapter, taken seven days before the planned launch. Photo courtesy of ispace.</figcaption></figure>
Resilience is expected to touch down on the moon's surface in May or June. It will take an energy-efficient path relying heavily on the Earth and moon's gravity in a winding series of flybys to steer its trajectory, similar to the Japanese space agency's SLIM which succeeded in the country's first lunar landing in 2024.
Firefly's Blue Ghost aims to reach the moon 45 days after launch, around March 2. The lander is carrying 10 payloads from a variety of NASA-funded customers and one from Blue Origin-owned Honeybee Robotics.
Both landers' missions will last a full lunar day, or roughly two weeks. They will not survive the frigid lunar nighttime where temperatures can plunge to roughly minus 128 degrees Celsius.
NASA with its Artemis program aims to return humans to the moon by 2027—but likely later—for the first time since 1972, while China plans to put its own crews on the lunar surface by 2030 following a series of robotic missions.
CLPS missions like Firefly's Blue Ghost, privately owned but substantially funded by NASA, are meant to study the moon's surface and stimulate private lunar demand before NASA sends humans there using SpaceX's Starship and later Blue Origin's Blue Moon lander.
But the US space agency faces potential changes to its Artemis program with the incoming administration of Donald Trump, who has largely sided with SpaceX CEO Elon Musk's vision to focus heavily on Mars.
"We've invested in going to the moon and I think everybody wants us to go back to the moon," Nicky Fox, head of NASA's science mission directorate who oversees CLPS, told Reuters on January 14 when asked about potential changes to the moon program.
"The great thing about NASA science—we do amazing science wherever we go," she said.
This article first appeared on <a tabindex="0" href="https://asia.nikkei.com/Business/Aerospace-Defense-Industries/Japan-and-U.S.-private-companies-take-on-China-in-new-Moon-race2" rel="noopener noreferrer" data-token-index="1">Nikkei Asia</a>. It has been republished here as part of 36Kr’s ongoing <a tabindex="0" href="https://www.kr-asia.com/nikkei-teams-up-with-36kr-in-asia-tech-news-coverage/" rel="noopener noreferrer" data-token-index="3">partnership with Nikkei</a>.

Japan and US private companies take on China in new moon race

Space Tech

<h3>fileAI raises USD 14 million to scale AI-powered workflow automation</h3>
<a href="https://www.file.ai/">fileAI</a>, an enterprise artificial intelligence startup, has raised USD 14 million in a Series A funding round co-led by Illuminate Financial, Antler Elevate, Insignia, and Heinemann Group. This latest round brings its total funding to over USD 20 million.
Based in Singapore, fileAI specializes in automating workflows by leveraging AI to process unstructured data—such as PDFs, spreadsheets, and emails—for clients spanning financial services, insurance, accounting, and manufacturing.
According to company claims, fileAI has automated more than 200 million documents, saving clients an estimated 420,000 hours and USD 7 million in costs.
The startup plans to use the new funds to further enhance its proprietary AI capabilities and to launch a new platform in the first quarter of 2025. This forthcoming platform will be tailored for finance, operations, and legal teams and is expected to introduce features such as automated document comparison, discrepancy detection, and compliance assurance tools.
<figure id="attachment_151841" aria-describedby="caption-attachment-151841" style="width: 1024px" class="wp-caption alignnone"><img loading="lazy" decoding="async" class="size-large wp-image-151841" src="https://console.kr-asia.com/wp-content/uploads/2025/02/fileAI-Christian-Schneider-Clare-Leighton-1024x683.jpg" alt="Photo of Christian Schneider (left) and Clare Leighton, co-founders of fileAI." width="1024" height="683" srcset="https://console.kr-asia.com/wp-content/uploads/2025/02/fileAI-Christian-Schneider-Clare-Leighton-1024x683.jpg 1024w, https://console.kr-asia.com/wp-content/uploads/2025/02/fileAI-Christian-Schneider-Clare-Leighton-300x200.jpg 300w, https://console.kr-asia.com/wp-content/uploads/2025/02/fileAI-Christian-Schneider-Clare-Leighton-768x512.jpg 768w, https://console.kr-asia.com/wp-content/uploads/2025/02/fileAI-Christian-Schneider-Clare-Leighton-1536x1024.jpg 1536w, https://console.kr-asia.com/wp-content/uploads/2025/02/fileAI-Christian-Schneider-Clare-Leighton.jpg 1920w" sizes="(max-width: 1024px) 100vw, 1024px" /><figcaption id="caption-attachment-151841" class="wp-caption-text">Photo of Christian Schneider (left) and Clare Leighton, co-founders of fileAI. Photo and header photo courtesy of fileAI.</figcaption></figure>
<h3>GOAT Gaming secures USD 4 million to expand gaming on Telegram</h3>
GOAT Gaming, a platform for competitive and casual gaming on Telegram, has raised USD 4 million in funding. Key investors in this round include TON Ventures, Karatage, Amber Group, and Bitscale Capital. This infusion brings the platform’s total funding to around USD 15 million.
Founded by the team behind Mighty Bear Games, GOAT Gaming plans to use its capital to build an interactive entertainment ecosystem on Telegram. The company aims to host hundreds of games and is rolling out AI-powered autonomous gaming agents called “AlphaGOATs.” Its proprietary AI, developed since 2016, reportedly powered the launch of 37 games in 2024. The new autonomous agent offering is set to launch on February 6.
“We believe that Telegram is the most accessible gateway to Web3 and GOAT Gaming is on the way to hosting hundreds of games, integrating countless autonomous agents, and delivering a seamless, AI-driven gaming experience,” said Simon Davis, CEO of GOAT Gaming.
<h3>SoftBank in talks to invest up to USD 25 billion in OpenAI</h3>
SoftBank Group is reportedly in early discussions to invest USD 15–25 billion in OpenAI, potentially becoming its largest external investor, according to the <a href="https://www.ft.com/content/6a482d4f-0c90-47bf-a4c2-67a2f1b743b1">Financial Times</a>.
If finalized, this deal could eclipse Microsoft’s estimated USD 13 billion stake in OpenAI and push the startup’s valuation to around <a href="https://www.businessinsider.com/openai-valuation-softbank-investment-spacex-bytedance-2025-1">USD 300 billion</a>, which would position OpenAI among the most valuable private companies globally, second only to SpaceX, which is valued at roughly USD 350 billion.
These talks occur as OpenAI reaffirms its commitment to the Stargate Project—a joint venture with Oracle and SoftBank that aims to build up to USD 500 billion in AI infrastructure over the next four years. SoftBank has already pledged USD 15 billion to the project, and a portion of its potential OpenAI investment may help finance the initiative.
In addition to this capital injection, SoftBank is also expanding its AI portfolio by forming a joint venture to bring OpenAI’s technology to corporate clients in Japan and is expected to pay an annual fee of about USD 3 billion to integrate OpenAI’s models across its global businesses.
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<h3>Utsav raises INR 63.5 million to expand religion tech platform</h3>
Utsav, an Indian religion tech startup and platform, has raised INR 63.5 million—around USD 730,000—in a pre-Series A funding round led by Equanimity Investments, with participation from India Quotient.
The company plans to use the funding to scale operations by onboarding additional temples in India’s first- and second-tier cities, while also planning an international expansion to serve the Indian diaspora.
In addition, Utsav intends to enhance its platform’s personalization features by introducing real-time pandit consultations and upgrading its logistics network to ensure faster delivery of religious offerings.
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<h3>Elev8.vc, 129Knots, HongShan, and more made recent headlines:</h3>
<ul>
<li aria-level="1">Elev8.vc, a venture capital firm based in Singapore, closed a USD 30 million fund targeting early-stage startups specializing in fields such as AI, robotics, medtech, and advanced manufacturing.</li>
<li aria-level="1">129Knots, a fintech company incubated under Singapore EDB’s Corporate Venture Launchpad program, officially launched with USD 10 million in funding led by Sing Fuels.</li>
<li aria-level="1">HongShan, previously the Chinese investment arm of Sequoia Capital, acquired a majority stake in Stockholm-based audio equipment maker Marshall Group.</li>
</ul>
If there are any news or updates you'd like us to feature, get in touch with us at: <a href="mailto:hello@kr-asia.com">hello@kr-asia.com</a>.
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Deals in brief: fileAI raises Series A funding, GOAT Gaming secures backing for Telegram expansion, SoftBank eyes major OpenAI stake, and more

India

… id="caption-attachment-151854" class="wp-caption-text">And this robot is practising how to arrange dining utensils and tableware. Graphic source: 36Kr.</figcaption></figure>
However, achieving this vision is no small feat. Yao Maoqing emphasized the critical role of feeding continuous streams of data into large models. The more data these models ingest, the closer they come to human-level performance in specific scenarios. Yet, scaling robotics to this level will require tens of millions—if not billions—of data points. The “scaling law” of robotics is still a work in progress, far from being fully realized.
Ultimately, the advancement of robotics depends on integrating hardware and software—prioritizing one at the expense of the other is unlikely to yield meaningful progress.
In the US, where hardware costs are high, most robotics startups prioritize algorithm development while outsourcing hardware. China, however, benefits from a robust and cost-effective supply chain. By combining advanced algorithms with self-developed hardware, Chinese robotics companies can iterate more quickly and efficiently.
Yao highlighted that China’s robotics industry is now on par with the US. “Labor costs in the US are ten times higher than in China, and US companies still rely on Chinese suppliers for components,” he said.
This cost advantage, coupled with faster development cycles, has allowed Agibot to expand its capacity for scene simulation and data collection. Technologies that US robotics companies might find cost-prohibitive are increasingly attainable in Agibot’s facility, where streams of data are steadily transforming futuristic ideas into practical realities.
KrASIA Connection features translated and adapted content that was originally published by 36Kr. This <a href="https://36kr.com/p/3131190931839490">article</a> was written by Tian Zhe for 36Kr.

Inside Agibot’s Shanghai center, robots learn to master tasks in human-like ways

Agibot

Embodied Intelligence

… approach, protectionism risks doing more harm than good—raising costs for consumers, straining businesses, and injecting volatility into global trade.
Trump’s new tariffs are set to take effect at 12:01 a.m. ET on February 4.

Trump’s new tariffs rattle global markets—will they backfire or pay off?