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	<title>Alibaba &#8211; Firethering</title>
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	<link>https://firethering.com</link>
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		<title>A Bluetooth Glitch Just Exposed How AliExpress Fingerprints Vistors&#8217; Browsers Through Audio</title>
		<link>https://firethering.com/aliexpress-web-audio-fingerprinting/</link>
					<comments>https://firethering.com/aliexpress-web-audio-fingerprinting/#respond</comments>
		
		<dc:creator><![CDATA[Mohit Geryani]]></dc:creator>
		<pubDate>Thu, 27 Aug 2026 13:54:29 +0000</pubDate>
				<category><![CDATA[Tech]]></category>
		<category><![CDATA[Trends]]></category>
		<category><![CDATA[Alibaba]]></category>
		<category><![CDATA[Security]]></category>
		<guid isPermaLink="false">https://firethering.com/?p=7806</guid>

					<description><![CDATA[Your headphones can tell you when a website is doing something strange.

At least, that's what happened when a developer noticed his Bluetooth headphones stopped switching back to his phone whenever an AliExpress tab was open on his PC.

There was no music playing from the computer. No video. No audible sound. Closing the AliExpress tab immediately fixed the problem.

That strange Bluetooth glitch led him to something much more interesting: AliExpress was quietly running audio through the browser, not to listen to the user, but to measure how the browser and device processed a known sound.

The technique is called Web Audio fingerprinting. And while it sounds like something from an older era of browser tracking, the discovery shows just how much information a website can extract from seemingly ordinary browser APIs.

Brave later highlighted the case, explaining that AliExpress wasn't recording users' audio. Instead, it was generating a silent signal and measuring how a device processed it to help fingerprint the browser.

So what exactly was happening inside that supposedly silent AliExpress tab and why did a fingerprinting technique end up interfering with a pair of Bluetooth headphones?]]></description>
		
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		<title>Alibaba&#8217;s Qwen3.7-Max Ran Autonomously for 35 Hours on Unfamiliar Hardware. It Still Kept Getting Better.</title>
		<link>https://firethering.com/alibaba-qwen3-7-max-autonomous-agent/</link>
					<comments>https://firethering.com/alibaba-qwen3-7-max-autonomous-agent/#respond</comments>
		
		<dc:creator><![CDATA[Mohit Geryani]]></dc:creator>
		<pubDate>Mon, 25 May 2026 08:26:49 +0000</pubDate>
				<category><![CDATA[Tech]]></category>
		<category><![CDATA[AI Models]]></category>
		<category><![CDATA[Trends]]></category>
		<category><![CDATA[AI]]></category>
		<category><![CDATA[AI Agents]]></category>
		<category><![CDATA[Alibaba]]></category>
		<category><![CDATA[Qwen]]></category>
		<guid isPermaLink="false">https://firethering.com/?p=7067</guid>

					<description><![CDATA[Alibaba gave Qwen3.7-Max a kernel optimization task on a hardware platform the model had never encountered before. No documentation or profiling data. No example kernels for the architecture. Just a task description, an existing implementation, and an evaluation script.

The model ran for 35 hours. It made 1,158 tool calls. It wrote, compiled, profiled, and rewrote the kernel repeatedly, diagnosing failures, fixing bugs, identifying blocks, and redesigning the architecture multiple times without anyone watching. After 30 hours it was still finding meaningful improvements.

The final result was a 10x speedup over the reference implementation.

For context: GLM 5.1 ran the same task and reached 7.3x. Kimi K2.6 reached 5x. DeepSeek V4 Pro reached 3.3x. The models that stopped early did so because they issued no tool calls for five consecutive rounds, they concluded they couldn't make further progress and stopped. Qwen3.7-Max didn't stop.]]></description>
		
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