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Tencent says it could make instant profits on $53bn hardware splurge by renting it for AI workloads

Plans to build models instead because it thinks selling tokens will prove more lucrative in the long term

Tencent says it could make instant profits on $53bn hardware splurge by renting it for AI workloads

Chinese tech giant Tencent has invested $53 billion in its new AI department but is not expecting immediate financial returns, according to a recent Q2 earnings call. Instead, the company is betting that its AI-infused products will generate superior economic returns in the long run. During the call, Bernstein analyst Robin Zhu inquired about Tencent's return on investment, to which Chief Strategy Officer James Mitchell replied that demand for computing resources is so strong, Tencent could make back its depreciation costs "almost immediately" if it rented out its infrastructure.

Company president Martin Lau elaborated that if Tencent acted like a "neocloud," it would achieve a "decent return in an immediate timeframe" as offers for its compute capacity are at more than 30 percent profit. Instead of seeking instant profits, Tencent is focusing on building its own cutting-edge models and deploying popular AI applications to achieve market leadership in China.

The company believes that by providing superior intelligence through state-of-the-art models and AI applications, it can convert into superior economic returns over the long term. Tencent's latest model, the 295-billion open-weight Hunyuan-3, has already been released in July, and the upcoming Hunyuan-4 is expected to be even more powerful.

The company plans to continue optimizing its products to work seamlessly with Hunyuan-4 and is already making significant strides in the messaging apps and gaming sectors. Despite the company's impressive growth and exceptional AI efforts, investors are uncertain about the future of Tencent's share price, which has declined slightly since the earnings announcement.

Written by urgent.news from The Register Science's reporting — not their text. Machine-written — may contain errors; check the original before relying on it.

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