Tesla’s arch rival has already won at charging tech. Now, it’s testing a self-driving breakthrough


BYD has made no secret of its ambition to build more of its own technology. That includes everything from batteries to electric motors, and now even the AI chips that power advanced driver assistance systems. But despite all that momentum, the company’s latest move suggests it’s not ready to cut ties with outside chipmakers just yet. Instead, BYD appears to be taking the practical route.

A smart detour before the destination

The latest reports out of China indicate that the BYD Seal is currently testing Horizon Robotics’ upcoming Super Drive 2.0 platform. BYD Chairman Wang Chuanfu was reportedly seen evaluating the system alongside Horizon Robotics CEO Yu Kai, hinting that the software is nearing a more mature stage of development.

The focus isn’t simply on adding new driving features. Engineers are reportedly refining how the vehicle’s cameras communicate with its central computing hardware, squeezing better performance from the existing architecture before an entirely new generation of hardware arrives. That matters because BYD has already shown off its own custom AI processor — the 4nm Xuanji A3 — which promises an impressive 700 TOPS of computing performance. Many expected that chip to quickly replace third-party suppliers across the lineup. That isn’t happening, at least not anytime soon.

Sometimes waiting is the smarter upgrade

According to recent industry reports, BYD’s in-house silicon won’t reach production until 2027, beginning with premium Denza models. Until then, Horizon Robotics and other chip suppliers will continue powering many of the company’s high-volume vehicles. There’s a practical reason behind that decision: money.

Using established third-party processors reportedly cuts manufacturing costs by roughly 1,500 to 4,000 yuan per vehicle. When you’re building cars at BYD’s scale, those savings add up remarkably fast. Lower hardware costs also make it easier to bring advanced driver assistance features to more affordable models, rather than reserving them exclusively for flagship EVs. There’s another advantage, too. Horizon has already supplied millions of processors for BYD’s driver-assistance program, giving the automaker a mature supply chain ready to scale without disrupting production.

The broader chip race is still very much alive. NVIDIA continues to dominate the automotive AI market, while Horizon Robotics has steadily expanded its footprint. BYD clearly wants to eventually join that conversation with silicon of its own. For now, though, the company seems more interested in getting capable software into customers’ hands than in rushing to prove it can do everything on its own. And for buyers, that’s probably the more sensible strategy.



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Recent Reviews


YouTube has an AI slop problem, and its crackdown is catching legitimate creators in the crossfire. Faceless channels, where no human host ever appears on screen, have existed for years and are not inherently AI-generated.

Many are run by solo creators who simply prefer to stay anonymous. The problem is that AI tools made it easy to flood the platform with low-effort faceless content at scale, and YouTube’s algorithm is now penalizing the format as a whole.

How bad is the AI slop problem on YouTube?

A Kapwing study found that roughly 21% of the first 500 videos recommended to a new YouTube account were classified as AI slop, while 33% fell into a broader brainrot category. The problem extends to children, too, as more than 40% of YouTube Shorts recommended to kids in a 15-minute session contained low-quality AI content.

YouTube’s response has been to tweak its algorithm to favor videos with real human faces on camera, which is hitting faceless creators even when their content is entirely human-made.

How is YouTube tackling its AI slop problem?

YouTube is now testing a new pop-up on mobile that asks viewers to rate whether a video feels like AI slop, on a scale from “not at all” to “extremely.” The idea sounds reasonable, but crowdsourcing AI detection has real problems. People are bad at spotting AI content, and they are getting worse at it as AI capabilities continue to improve.

There are also legitimate concerns that YouTube could use this viewer feedback as training data for its own AI models, potentially making future AI-generated content even harder to spot.

🚨 Did you just see what YouTube did?

YouTube isn’t banning AI slop.. They’re making you label it so they can train their next model to not look like slop.

Read that again…

You flag the bad AI content. YouTube collects it. Google feeds it into Veo 4… Then next year their… https://t.co/8UC2J3mjjv pic.twitter.com/mIrTChqC1b

— Tuki (@TukiFromKL) March 17, 2026

Meanwhile, faceless creators are scrambling to adapt. According to The Hollywood Reporter, some are hiring cheap on-camera hosts through platforms like Fiverr and Upwork. Others are doubling down on niche educational content, which has held up better than broad content farms.

The AI text-to-video space is still valued at enormous sums, with Higgsfield AI alone sitting at $1 billion, but on YouTube, the math for faceless creators is getting harder to work out every month.



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