Twitch is going to train Amazon’s AI models on streamers’ content unless they deliberately go into their settings and opt out, potentially sweeping up a wealth of streamers who either don’t hear about the announcement or follow steps stop it.

On Wednesday Twitch announced a new setting that lets streamers opt-out of the training. The announcement confirms rumors that have percolated over the last week: It is using streamers to train Amazon’s AI models. 

The new toggle says, "Allow your channel content to train generative AI content models at Amazon." All users are opted in by default. It's located at the bottom of users' security settings page. 

An American AI computer has turned up inside Russia's newest cruise missile. Ukrainian specialists has found an Nvidia Jetson micro-computer in Russia's new S-71 "Monokhrom" cruise missile, the Defense Ministry's Main Intelligence Directorate (HUR) reports.

S-71M “Monokhrom is the first fully autonomous long-range strike system designed to engage not only stationary but also moving targets. The system is designed to independently decide whether to destroy a target based on threat priorities. A significant problem for such autonomous systems is determining exactly what they are attacking — a military truck or a bus carrying children.

The discovery is the latest evidence that Russia's newest weapons still run on Western technology. Ukraine has already documented hundreds of foreign components in Russian missiles and drones reaching Moscow despite sanctions.

The AI chip is the standout find

The use of the Nvidia Jetson may indicate the application of AI technologies in the missile. This capability would let the weapon process visual or sensor data onboard to identify targets or navigate, functions that depend on exactly the kind of compact AI computing it provides.

The chip sits among many foreign parts. In total, 35 electronic components used by Russia in the missile were identified, making Monokhrom another Russian weapon built substantially from foreign electronics.

The same parts show up across Russia's arsenal

HUR's analysis linked the missile to Russia's wider weapons program. The identified components included parts of a passive radar seeker that Russia has begun installing on Geran-2 drones to detect and strike Ukrainian air-defense systems and radars.

Other finds tied the missile to Russia's newest strike systems. They included a Chinese Honpho TS130C-01 camera from the jet-powered Geran-4 drone and components of the active homing seeker of the Kh-47M2 Kinzhal aeroballistic missile.

The finding sharpens the sanctions case

HUR framed the discovery as an argument for tighter enforcement.

"The discovery of an Nvidia Jetson in a new Russian missile once again demonstrates the need to strengthen sanctions pressure and coordinate the efforts of the civilized world," HUR said.

HUR specialists and Ukrainian research institutions continue to study Russian weapons and trace the origin of their electronic components to strengthen measures to block them.

CGTrader, an online marketplace for 3D assets, found that one in six models uploaded to the site these days is AI generated, but that AI generated assets account for only $1 out of $90 in revenue on the site. These numbers show that AI generated assets are quickly flooding the marketplace, but that most people are not interested in paying for them.

“Buyers are voting with their wallets, and AI-generated content is struggling to compete,” CGTrader said in a press release about its 2026 market trends reports. The company says the gap between the surging supply of AI generated 3D models and the middling demand points to “a gap that undercuts the assumption that AI-made content is repricing the market.”

“The upload numbers alone would suggest a takeover,” CGTrader said. “The revenue numbers say otherwise, and buyers refusing to pay for AI-generated models is saying something bigger than no thanks: it is a signal of how far they trust AI generation itself. Which leaves the question the industry has been avoiding: an AI model may be cheaper to produce, but what is it actually worth?”

Like the Unreal and Unity asset stores, CGTrader is a marketplace where people can buy more than two million 3D models to use in their videos, games, or 3D printing projects, and has been around since 2011. The report it published is based on marketplace data collected between June 2025 and May 2026 and surveys of buyers. 

Alexander Spivak, a 3D artist who sells his assets on CGTrader, told me that he’s not against AI, but that “as an artist, I haven't yet found a way to seamlessly collaborate with AI.

Because in creativity, the most important thing is the process of creation, which I enjoy.

The result is a completely different story. And I haven't yet been able to integrate AI into my workflow in a way that allows me to continue enjoying [the process.]”

Buyers told CGTrader that the reason they weren’t buying as many AI generated assets their quantity might suggest is simple: they’re not as good as human made 3D models. Buyers said that quality was the number one factor in choosing what they buy, even more than the price. This was especially important to buyers who wanted models for 3D printing, where a bad model could break or not print correctly. Only 4 percent of those buyers said AI “works well.” The survey also found that most people who bought AI generated assets weren’t satisfied with them. 20 percent of buyers found it not good enough, and 7 percent used it only with heavy editing. 5 percent said it worked well. 

CGTrader’s findings come months after the company announced it was partnering with Tencent on an AI powered 3D model creation workflow. CGTrader CEO Dalia Lašaitė told me that the workflow doesn’t just generate assets from scratch, but that designers can use it to refine topology and textures, segment parts, create variations and prepare models for production. 

“AI can accelerate the more mechanical parts of the process, while the designer retains creative direction and control over the final result,” she told me. “For that reason, we think of this work as AI-accelerated rather than simply AI-generated. Our goal isn't to increase the volume of AI-made assets on the marketplace. It's to give designers better tools to work faster and focus more of their time on creative work. Ultimately, buyers will choose the assets that best meet their needs. The distinction that matters most isn't whether an asset is AI- or human-generated, but whether it meets the required quality standard.”

AI generated content is creating a discoverability problem across the internet. On Instagram, porn sites, YouTube, and music streamers, human creators are being drowned out by a flood of AI generated slop. Lašaitė acknowledged that, despite the current discrepancy between how many AI generated models are uploaded to CGTrader and how many people are buying them, the increase in uploads alone could make it more difficult to find human artists.

“AI uploads are currently growing faster than AI purchases, which makes effective discovery and ranking increasingly important,” she said. “Our approach is to prioritize quality and performance signals rather than raw volume, including how an asset performs commercially, how buyers rate it and other indicators of quality.”

From space to telecommunications, the US has a long history of fostering technology for the public good. These AI models could be aligned to democratic values, not corporate profits

OpenAI, and then Anthropic, were each formed by AI developers who feared unrestrained corporate AI development – specifically, that companies like Google and Meta would steer the technology towards deleterious, maybe even catastrophically unsafe, outcomes for society. Their founders proclaimed that their new labs, uniquely, could be trusted to develop the technology in humanity’s best interest. But each, in turn, were themselves co-opted by the same market incentives, themselves becoming corporate behemoths zealously guarding future investor value rather than the public interest.

It was only a few weeks ago, in June, when OpenAI and Anthropic each filed for their IPOs and were met with buzz about trillion-dollar valuations. The hype around their valuations is so extreme that many worry about their potential for concentrating wealth on a global scale. In an effort to leave something for the rest of us, some observers have proposed that the federal government seize a share of these companies’ stock to create a US sovereign wealth fund, or redistribute their revenues to produce a dividend for taxpayers.