Trump bears an economic grudge against Taiwan and wants Taiwan to pay for US protection. He also says: “Taiwan is 9,500 miles away. It’s 68 miles away from China.”

Feeling robbed of my path to citizenship right now after grinding a PhD and contributing to foundational AI computing technologies for the United States for the past ~ 10 years. Feels like robbing top and technologists like me of the opportunity to achieve the American Dream.

Feeling robbed of my path to citizenship right now after grinding a PhD and contributing to foundational AI computing technologies for the United States for the past ~ 10 years. Feels like robbing top and technologists like me of the opportunity to achieve the American Dream.

AOC: This is what drinking water in Georgia looks like after Meta began data center construction in the community.

“When Xavier Becerra was state attorney general, his office pushed the state Supreme Court to artificially inflate a Black man’s IQ in order to execute him.” theintercept.com/2026/05/19/…

What historical fact sounds fake but is true?

What historical fact sounds fake but is true?

venice was built on a sandbar in 421 ad what's stopping us?

what is your most leftist urbanist opinion?

"Nobody reviews compiler output, why review AI code?" Wrong. We do review compiler output. Godbolt exists. Disassemblers exist. Anyone doing serious performance work reads what the compiler produced. The premise is false. But the analogy itself is flawed. It compares two things that aren't comparable. A compiler takes a formal language as input. Languages with grammars and semantics defined precisely enough that "what does this code mean" has only one answer. An LLM takes natural language as input. Natural languages are ambiguous. "Write me a function that handles user input safely" has a thousand valid interpretations and a thousand more invalid ones. The LLM picks one. You don't know which. Unless you look at the code. Compilers are built from specifications and designed to meet them. The output is the result of a defined translation. When the output violates the spec, it's a bug. LLMs are built from whatever was in their training data. There is no spec. There can't be one, natural languages have no defined semantics that map to code. Compilers are semantically deterministic. The same input produces output with the same behaviour, every time. LLMs are not. Partly by design and partly due to hardware variance, batch size, inference order, and floating point operations (and no setting temperature to zero does not address those). All of which can push the same prompt to produce different code. Compilers complain loudly when the input is nonsensical. LLMs fail silently, producing plausible-looking, but wrong code. We trust compiler output because the trust was earned across decades of use, with millions of engineers using the same tools. Early compilers were reviewed heavily. Hand-written assembly was the default because trust hadn't been earned yet. We're at the hand-written assembly stage with AI. We may never get to the trust-the-output stage for the reasons explained above. If you’re a software developer, you should own what goes to production. The compiler analogy is a way of skipping that responsibility.

My statement suspending my candidacy for the U.S. Senate:

i can still live another 50 years if @Mike_Pence has the courage

Need more of whatever genre this is where you think the protagonist is based on a real person but they’re actually not and it makes for great character studies.

Researchers sent the same resume to an AI hiring tool twice. Same qualifications. Same experience. Same skills. One version was written by a real human. The other was rewritten by ChatGPT. The AI picked the ChatGPT version 97.6% of the time. A team from the University of Maryland, the National University of Singapore, and Ohio State just published the receipt. They took 2,245 real human-written resumes pulled from a professional resume site from before ChatGPT existed, so the human writing was actually human. Then they had seven of the most-used AI models in the world rewrite each one. GPT-4o. GPT-4o-mini. GPT-4-turbo. LLaMA 3.3-70B. Qwen 2.5-72B. DeepSeek-V3. Mistral-7B. Then they asked each AI to pick the better resume. Every model picked itself. GPT-4o hit 97.6%. LLaMA-3.3-70B hit 96.3%. Qwen-2.5-72B hit 95.9%. DeepSeek-V3 hit 95.5%. The real human almost never won. Then the researchers tried the obvious objection. Maybe the AI is just better at writing. So they had real humans grade the resumes for actual quality and ran the experiment again, controlling for it. The result was worse. Each AI kept picking itself even when human judges rated the human-written version as clearer, more coherent, and more effective. It gets worse. The AIs do not just prefer AI over humans. They prefer themselves over other AIs. DeepSeek-V3 picked its own resumes 69% more often than LLaMA's. GPT-4o picked its own 45% more often than LLaMA's. Each model can recognize and reward its own dialect. Then the researchers ran the simulation that ends careers. Same job. 24 occupations. Same qualifications. The only variable was whether the candidate used the same AI as the screening tool. Candidates using that AI were 23% to 60% more likely to be shortlisted. Worst gap was in sales, accounting, and finance. 99% of large companies now run AI on incoming resumes. Most of them use GPT-4o. The paper just proved GPT-4o picks GPT-4o 97.6% of the time. If you wrote your own cover letter this week, you did not lose to a better candidate. You lost to a worse candidate who paid OpenAI 20 dollars. Your qualifications do not matter if the AI prefers its own handwriting over yours.

At our city-owned grocery stores, staples like eggs and bread will actually be affordable. And we're going to do it the right way, without cutting workers' pay or dignity. Because in the wealthiest city in this country, buying groceries shouldn't be an unsolvable equation. It should be simple, fair, and within reach for everyone.

Initial VA reaction: -Turnout was to the right of both 2025 and 2024, closest to 2021. It’s quite likely that Youngkin won last night's electorate. -YES won because it massively overperformed Harris with Hispanic and Asian voters in NoVA, while also improving with Black voters.

Ossoff: How much do you guys know about Jared Kushner—Ivanka’s husband? He’s on the Saudi payroll for $2 billion. And now he’s leading American diplomacy in the Middle East, apparently, while at the very same time asking princes and sheikhs to give him billions more. Can you imagine a normal sitting U.S. ambassador just hitting MBS for billions? But he’s a Trump, a royal, a princeling. The rules are for us, not for them. And it’s not just Jared. Never before have we seen so little effort to hide so much corruption. The Mar-a-Lago mafia has taken American corruption to spectacular new heights.

Introducing Claude Opus 4.7, our most capable Opus model yet. It handles long-running tasks with more rigor, follows instructions more precisely, and verifies its own outputs before reporting back. You can hand off your hardest work with less supervision.