from the the-neverending-corruption-story dept

The saga of Trump suing his own IRS for $10 billion just got weirder. What started as a brazenly corrupt attempt to personally pocket $10 billion in taxpayer money has now morphed into something arguably worse: a $1.7 billion patronage slush fund — unappropriated by Congress — that Trump could dole out to loyal MAGA allies who claim they were “victimized” by the Biden administration.

As you’ll recall, Trump sued his own IRS over something that a contractor (who has already been convicted and is currently serving in prison) did: leaking some tax returns Trump had promised to release, but never did. He asked for $10 billion, in a situation where he, himself, would decide if he got paid or not. When his own DOJ told the court that it was negotiating a settlement, the judge pointed out that she was concerned that it looked an awful lot like a single party negotiating with itself over how much of the Treasury it should receive.

The judge — Kathleen Williams — asked for further briefing from “both” parties on this, and the deadline is coming up quickly, which is why various purported “settlements” are leaking to the press. A few days ago it was going to be that Trump and all of his family and all of his related businesses would magically have all IRS audits dropped, which would be an astoundingly brazen level of corruption.

But now ABC is reporting about another potential “settlement” (again, “settlement” is the wrong word — it’s Trump’s legal team negotiating with Trump’s DOJ, which is run by his former legal team. It’s one team negotiating with itself) which is just as egregious and corrupt: Trump would apparently agree to drop his case against the IRS in exchange for… a $1.7 billion slush fund of taxpayer money that he could dole out to his friends who whine to the government that they were “targeted” for retribution by a “weaponized” Biden administration.

President Donald Trump is expected to drop his $10 billion lawsuit against the Internal Revenue Service in exchange for the creation of a $1.7 billion fund to compensate allies who claim they were wrongfully targeted by the Biden administration, sources familiar with the matter told ABC News.

The commission overseeing the compensation fund would have the total authority to hand out approximately $1.7 billion in taxpayer funds to settle claims brought by anyone who alleges they were harmed by the Biden administration’s “weaponization” of the legal system, including the nearly 1,600 individuals charged in connection with the Jan. 6 Capitol attack as well as potentially entities associated with President Trump himself.

So, yeah, a $1.7 billion slush fund for Trump supporters who (in some cases) literally engaged in insurrection to overturn the results of a free and fair election, or for various hangers-on who play the victim every chance they get and pretend the Biden administration “weaponized” the government against them.

It’s not worth getting into the possibility of using this slush fund to pay off the ~1,600 Trump supporters who were duly convicted in a court of law for various crimes, all of whom were later pardoned by Trump (even as dozens of them have been re-arrested for other crimes, which should put to rest any remaining notion that Trump is the “law and order” president — but of course it won’t).

But we can talk about the various claims of “weaponization” because we covered many of them. Remember, Jim Jordan got himself appointed as the anti-weaponization czar in Congress, and used that to actually weaponize the government to investigate and attack individuals and organizations who were not the government, but who Jordan felt unfairly pointed out disinformation and lies from those MAGA supported.

The supposed investigations into the “weaponization” of the government to suppress speech served only to suppress the First Amendment protected speech of academic researchers and organizations. And now all those who falsely insisted that the Biden administration “censored” them, even as all the evidence showed that social media companies removed content because they found that the content violated their own rules, will get to line up at the trough to get free money from American taxpayers.

This is Donald Trump handing out American taxpayer money that has never been appropriated by Congress for this purpose — shoveling it to anyone who claims victimhood under his banner, whether convicted insurrectionists, Trump allies who want their legal bills paid, or propagandists who got called out for spreading disinformation. We’re already seeing this play out. This week, Trump’s DOJ “settled” with the pandemic’s wrongest man, Alex Berenson, who got suspended from Twitter not because of any government action, but because Twitter felt that he violated their rules against spreading health misinformation.

Berenson has been suing over this for years (and mostly losing), but this week Trump agreed to pay him $150,000 and “admit” that the Biden administration tried to censor him. While some are trying to present this as some sort of big victory, getting Donald Trump to blame Joe Biden for something that didn’t happen — while shoveling taxpayer money to a man who publicly supports Trump — is not exactly a landmark legal victory. It’s almost expected in the Trump era.

The Berenson payout is a preview. Once the $1.7 billion fund is running, expect a line out the door of Trump’s groveling fans making false claims about Biden “weaponizing” the government — all of it paid for by taxpayers, none of it appropriated by Congress.

Filed Under: donald trump, irs, maga, patronage, slush fund, victimhood, weaponization

Users may not be able to combine Microsoft software with competitors’ products effectively, the CMA has been told.

The UK’s competition watchdog has launched an investigation into Microsoft’s enterprise software ecosystem over interoperability concerns.

The Competition and Markets Authority (CMA) probe will consider whether Microsoft should be given a ‘strategic market status’ (SMS) designation reserved for companies that dominate the UK market in a particular digital activity.

Apple and Google received this status last year over their dominance of mobile platforms.

The investigation will also assess whether Microsoft’s product bundling, limits in interoperability for users, and default settings prevent customers from switching to competing services. This will include probing how Microsoft’s AI competitors are able to integrate with its business software.

Hundreds of thousands of UK organisations across public and private sectors use Microsoft’s enterprise software daily, spanning the Windows operating system, Microsoft 365 suite and Copilot AI.

The CMA finds that Microsoft has more than 15m commercial UK-based users across its ecosystem, making it a key provider of productivity tools in the country.

The competition watchdog said it has received information that users may not be able to combine Microsoft software with competitors’ products effectively.

In its probe, it will examine Microsoft’s wide range of products, including productivity software, personal computer and server operating systems, database management systems and security software.

The investigation will take up to nine months to complete. The authority has invited organisations based in the UK and around the world, including rival tech companies and business software customers, to share their experiences.

This is the fourth SMS investigation opened by the CMA since the UK’s digital markets competition regime came into force in January 2025. The law gives the CMA additional powers to propose remedies and improve market competition in the country. Early last year, it opened a probe into Apple and Google over their mobile ecosystems,

The designation would also allow the CMA to potentially intervene on concerns from a separate investigation into Microsoft’s software licensing in the cloud market.

“Business software is a cornerstone of how the UK economy functions, from small businesses to major public services and infrastructure. Hundreds of thousands of customers in the UK rely on Microsoft’s systems, which is why it’s so important to ensure these services are delivering good outcomes,” said Sarah Cardell, the CMA’s CEO.

“Our aim is to understand how these markets are developing, Microsoft’s position within them and to consider what, if any, targeted action may be needed to ensure UK organisations can benefit from choice, innovation and competitive prices.”

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For AI systems to keep improving in knowledge work, they need either a reliable mechanism for autonomous self-improvement or human evaluators capable of catching errors and generating high-quality feedback. The industry has invested enormously in the first. It’s giving almost no thought to what’s happening to the second.

I’d argue that we need to treat the human evaluation problem with just as much rigor and investment as we put into building the model capabilities themselves. New grad hiring at major tech companies has dropped by half since 2019. Document review, first-pass research, data cleaning, code review: Models handle these now. The economists tracking this call it displacement. The companies doing it call it efficiency. Neither are focusing on the future problem.

Why self-improvement has limits in knowledge work

The obvious pushback is reinforcement learning (RL). AlphaZero learned Go, chess, and Shogi at superhuman levels without human data and generated novel strategies in the process. Move 37 in the 2016 match against Lee Sedol, a move professionals said they would never have played, didn’t come from human annotation. It emerged from AI self-play. 

What enables this is the stability of the environment. Move 37 is a novel move within the fixed state space of Go. The rules are complete, unambiguous, and permanent. More importantly, the reward signal is perfect: Win or lose, and immediate, with no room for interpretation. The system always knows whether a move was good because the game eventually ends with a clear result.

Knowledge work doesn’t have either of those properties. The rules in any professional domain are dynamic and continuously rewritten by the humans operating in them. New laws get passed. New financial instruments are invented. A legal strategy that worked in 2022 may fail in a jurisdiction that has since changed its interpretation. Whether a medical diagnosis was right may not be known for years. Without a stable environment and an unambiguous reward signal, you cannot close the loop. You need humans in the evaluation chain to continue teaching the model.

The formation problem

The AI systems being built today were trained on the expertise of people who went through exactly that formation. The difference now is that entry-level jobs that develop such expertise were automated first. Which means the next generation of potential experts is not accumulating the kind of judgment that makes a human evaluator worth having in the loop.

History has examples of knowledge dying. Roman concrete. Gothic construction techniques. Mathematical traditions that took centuries to recover. But in every historical case, the cause was external: Plague, conquest, the collapse of the institutions that hosted the knowledge. What’s different here is that no external force is required. Fields could atrophy not from catastrophe but from a thousand individually rational economic decisions, each one sensible in isolation. That’s a new mechanism, and we don’t have much practice recognizing it while it’s happening.

When entire fields go quiet

At its logical limit, this isn’t just a pipeline problem. It’s a demand collapse for the expertise itself.

Consider advanced mathematics. It doesn’t atrophy because we stop training mathematicians. It atrophies because organizations stop needing mathematicians for their day-to-day work, the economic incentive to become one disappears, the population of people who can do frontier mathematical reasoning shrinks, and the field’s capacity to generate novel insight quietly collapses. The same logic applies to coding. Our question is not “will AI write code” but “if AI writes all production code, who develops the deep architectural intuition that produces genuinely novel systems design?” 

There is a critical difference between a field being automated and a field being understood. We can automate a huge amount of structural engineering today, but the abstract knowledge of why certain approaches work lives in the heads of people who spent years doing it wrong first. If you eliminate the practice, you don’t just lose the practitioners. You lose the capacity to know what you’ve lost.

Advanced mathematics, theoretical computer science, deep legal reasoning, complex systems architecture: When the last person who deeply understands a subfield of algebra retires and no one replaces them because the funding dried up and the career path disappeared, that knowledge isn’t likely to be rediscovered any time soon. 

It’s gone. And nobody notices because the models trained on their work still perform well on benchmarks for another decade. I think of this as a hollowing out: The surface capability remains (models can still produce outputs that look expert) while the underlying human capacity to validate, extend, or correct that expertise quietly disappears.

Why rubrics don’t fully substitute

The current approach is rubric-based evaluation. Constitutional AI, reinforcement learning from AI feedback (RLAIF), and structured criteria that let models score models are serious techniques that meaningfully reduce dependence on human evaluators. I’m not dismissing them.

Their limitation is this: A rubric can only capture what the person who wrote it knew to measure. Optimize hard against it and you get a model that’s very good at satisfying the rubric. That’s not the same thing as a model that’s actually right.

Rubrics scale the explicit, articulable part of judgment. The deeper part, the instinct, the felt sense that something is off, doesn’t fit in a rubric. You can’t write it down because you need to experience it first before you know what to write.

What this means in practice

This isn’t an argument for slowing development. The capability gains are real. And it’s possible that researchers will find ways to close the evaluation loop without human judgment. Maybe synthetic data pipelines get good enough. Maybe models develop reliable self-correction mechanisms we can’t yet imagine.

But we don’t have those today. And in the meantime, we’re dismantling the human infrastructure that currently fills the gap, not as a deliberate decision but as a byproduct of a thousand rational ones. The responsible version of this transition isn’t to assume the problem will solve itself. It’s to treat the evaluation gap as an open research problem with the same urgency we bring to capability gains.

The thing AI most needs from humans is the thing we’re least focused on preserving. Whether that’s permanently true or temporarily true, the cost of ignoring it is the same.

Ahmad Al-Dahle is CTO of Airbnb.

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Ahead of the return to District Court for the continued appeals process in the Apple-Epic legal fight, the two companies have made a schedule to discuss a change in App Store fees for outbound links.

The May 6 decision by the Supreme Court to decline Apple’s request for a stay on a mandate to meet Epic Games to negotiate a new commission rate means more legal action in the coming months. In preparation, the two sides have agreed on a few ground rules for that meeting.

In a joint filing to the U.S. District Court for the Northern District of California on May 15, there is a multi-point schedule of actions and activities for the two companies.

The list starts with Apple being given 45 days to file with the court a “proffer,” namely a good-faith offer of evidence, testimony, documents, or some form of evidence to the court. This proffer will propose commissions for any “linked-out purchases,” along with supportive evidence, in a document that’s up to 30 pages long.

Up to ten days after the proffer, Apple will hand Epic all non-privileged documents about the decision-making process to create the proffer’s proposal. This includes fee proposals and a privilege log.

Within five days of that action, Apple will meet with Epic to discuss the privilege log and whether Epic needs any extra material to evaluate the Apple proposal. Epic can then designate up to 10% of the documents on that privilege log for further review by a third party.

Within 60 days from the latter of Apple’s proffer filing or Apple’s completion of document production, Epic will then file its own response to Apple’s proffer to the court. This too can be up to 30 pages in length, and if Epic makes an objection, it must include evidence supporting that move.

Once that has been filed, Apple has another 30 days to file its reply, though with a 15-page limit. After all that, the court can then hold a status conference or decide any further proceedings.

Based on all parties taking the last possible moments to complete each stage in the schedule, it could be 150 days or five months before the court schedules another meeting.

How Apple got here

Apple and Epic have endured a six-year legal battle that started with “Fortnite” allowing players to make in-app purchases using a third-party payment processor. Epic also made demands, including allowing alternate app storefronts in iOS and a change in the commission structure.

For the most part, Apple succeeded against Epic, but the court found against Apple’s anti-steering measures, which prevented developers from directing users to other ways to pay. Apple was ordered to make changes, and it claimed it did.

Epic responded, arguing Apple didn’t follow the spirit of the law, convincing a court in April 2025 to its viewpoint. The court viewed Apple’s moves as a “gross miscalculation” of acceptability.

The GameSir G8+ MFi is the controller that the G8 Galileo probably should have been from the start. It takes the same full-size grips, Hall effect thumbsticks and triggers, and programmable back buttons that made the original one of the best mobile grips going, then layers on MFi certification for iPhone and iPad Mini, swappable ABXY button caps, dual vibration motors, and crucially, improved case compatibility.

Best of all? It’s still the same $79.99 / £79.99 / AU$129.99 asking price.