California will tax downloaded software for the first time as part of a $351.7 billion budget deal


TL;DR

California’s $351.7B budget taxes downloaded software for the first time, raising $2B annually. A ballot measure would let the state save more from AI IPO windfalls.

California Governor Gavin Newsom and top Democratic legislators agreed on a $351.7 billion state budget that will extend sales tax to prewritten software downloaded from the web. The tax is expected to raise $900 million for the state and another $1.1 billion for local governments starting in fiscal year 2028 and annually thereafter, according to Bloomberg.

The change applies to software that was previously only taxed when purchased on a physical disc. “Most of us don’t get prewritten software on a physical disc anymore. The whole world is past that, our tax code isn’t,” said state Senator John Laird during a legislative debate on June 18.

Republicans argued the measure raises costs for businesses that rely on software ranging from basic office productivity apps to electronic medical records. “For millions of Californians, this isn’t abstract. This impacts real people, real businesses. This tax could be the difference between making payroll and missing it,” said state Senator Suzette Martinez Valladares.

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The budget also places a measure on the November ballot that would allow California to save more money from revenue spikes, such as the IPOs planned by California-based OpenAI and Anthropic. The state’s highly progressive tax structure leaves its finances vulnerable to market downturns, and the budget leaves $35.2 billion across savings accounts with $4.5 billion in the regular reserve.

The spending plan is Newsom’s last as governor and arrives as state finances are buoyed by the AI boom. But even with better-than-expected tax revenues, the budget is largely void of major new spending commitments. Appropriators are saving in anticipation of significant federal funding cuts to healthcare under Trump. The deal provides $90 million for distressed hospitals and $250 million for public hospitals, less than half what hospital systems requested to prepare for over $3 billion in annual federal cuts.

The budget also extends existing limits on business tax credits and establishes a permanent cap in 2030, when companies will be limited to using the greater of $5 million in credits per year or 70% of their tax liability. A separate proposal for a one-time tax on billionaires, backed by a labour union, is advancing to the ballot despite Newsom’s attempts to negotiate a compromise. The AI boom has reshaped California’s fiscal landscape, but the state is building reserves rather than spending the windfall, hedging against the possibility that the same market that is filling its coffers could correct sharply.



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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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