Topolog is a goal planner that models your plans as a directed graph and allows you to execute tasks in order, then schedules your days around them.
In a voice vote earlier this week, the House of Representatives passed H.R. 6028, the “Legislative Branch Agencies Clarification Act.” The legislation is presented as a technical reorganization of some government agencies, but it’s much more than that. H.R. 6028 would fundamentally change the U.S....
NPR > Technology The theory taking the rich by storm: China funds data center haters By Geoff Brumfiel Wednesday, June 10, 2026 • 4:01 PM EDT Speaking at an event titled "Harnessing American Power" last month, Interior Secretary Doug Burgum expressed dismay at what he saw as a new wave of local opposition to data centers in America.What's more, he claimed, not everything was as it seemed."It's not organic and local, some of this is foreign-sourced dark money," he told the crowd.He isn't alone in his suspicions. Over on the podcast All-In, which is hosted by a group of tech multimillionaires who call each other "besties," there was also talk of foreign influence, specifically from China."It is starting to feel or seem like there might be a CCP-funded campaign," fund manager Gavin Baker told the hosts.The theory that China is paying local activists in America to oppose data centers is catching on like wildfire among the Silicon Valley elite, despite a lack of evidence. Wealthy investors are naming names and pointing fingers, even if they can't directly link their projects' opponents to China.That's not to say that Chinese influence is completely absent from the U.S. conversation around AI infrastructure and data centers. On Wednesday OpenAI said it banned a cluster of likely Chinese accounts that used ChatGPT to generate anti-data center content this past winter. The accounts were probably run by a private Chinese technology firm working for "provincial-level government clients" in China, OpenAI said. The company said the operators posed as Americans on social media and posted AI-generated comments and images highlighting energy demand and rising electricity costs. Related Story: NPR But OpenAI also said the impact of the influence campaign appeared limited and its social media posts didn't get much traction. "This was not a case of an influence operation creating a debate. The debate existed already. This was an influence operation from China trying to interfere in it. We didn't see any signs that they succeeded," said Ben Nimmo, who leads threat investigations at OpenAI, on a call with reporters.The allegations that some activists are being directly financed by China come amid a rising wave of anti-data center sentiment: a recent Gallup poll found that 71% of Americans somewhat or strongly opposed construction of data centers in their communities. Related Story: NPR Despite that public opposition, the theory does appear to be gaining some traction in Washington. In a letter last week, Congressman Brett Guthrie, R-Ky., the chairman of the House Committee on Energy and Commerce called for a briefing on whether the U.S. government sees evidence for Chinese influence in the data center debate. The letter was addressed to FBI Director Kash Patel as well as David Sacks and Michael Kratsios, two wealthy tech investors who sit on President Trump's Council of Advisors on Science and Technology (Sacks, who was until recently Trump's special adviser on artificial intelligence and cryptocurrency, is also a regular host of All-In)."Cells" in UtahMany top earners promoting the foreign influence theory are either directly or indirectly invested in artificial intelligence. One prominent advocate is Canadian multimillionaire and Shark Tank star Kevin O'Leary, who is an investor in a giant data center in Utah called Stratos. It was going to be roughly twice the size of Manhattan and was being pushed through the permitting process, until local opposition began to build.After a local planning council approved the project in early May, O'Leary noticed an "immediate spike in misinformation," he said during a recent Fox News interview he posted on his own social media account."We dug in, I got my guys to do a deep dig into the IP addresses and here's what we found, this is fascinating," he said. "We found two cells inside of Utah."O'Leary claimed that a nonprofit called Alliance for a Better Utah and a consultancy known as Elevate Strategies were operating on behalf of the Chinese government against the project, which his company, O'Leary Digital, is leading. He went on to name several current and former employees with both organizations.Among them was Gabi Finlayson, a senior partner at Elevate Strategies, which is based in Salt Lake City and helps Democratic candidates run for office in Utah and elsewhere.She told NPR she had no idea how she or Elevate ended up on O'Leary's list. "I think we have been as confused as anybody," she said.Finlayson said that Elevate, like several progressive groups, had posted about the data center on its social media channels, but the firm is not playing a central role in efforts to stop construction. Moreover, its social media accounts don't generate revenue for the organization."We are certainly not a Chinese cell. Nobody pays us to make any content, let alone any foreign government," she said.Employees at Alliance for a Better Utah were equally perplexed."I grew up watching Shark Tank with my dad occasionally, and I was like why is this guy talking about us?" said Elizabeth Hutchings, the organization's communications director. O'Leary named people who didn't even work there anymore, and he claimed "there was evidence that millions of dollars were being funneled from the Chinese Communist Party," Hutchings said.O'Leary did not respond to several NPR requests for comment about the claims. NPR checked Alliance for a Better Utah's tax documents and found they posted revenue of around $200,000 dollars in 2024, which was on par with their annual revenue for the past decade."You know, it was such an outrageous claim we laughed," Hutchings said.The group even made a fundraising video mocking the idea they were funded by China on social media. The video displayed a hammer and sickle while asking for donations from local Utahns.Alliance for a Better Utah has also filed a lawsuit on behalf of five residents of Box Elder County, where Stratos is set to be built. The residents claim they weren't adequately consulted about the project."We haven't found much"Beyond the limited findings from OpenAI, evidence for a coordinated Chinese campaign to stop data centers in the U.S. remains thin.In mid-May the Bitcoin Policy Institute, a nonprofit primarily devoted to advocating for the crypto industry, published a report claiming "three vectors of influence" behind the anti-AI campaign. The report claimed that Chinese state media, foreign billionaires and alleged Chinese-backed U.S. leftists were working together to stop data center development, but offered little direct evidence that the campaign existed or was having much effect. In an article published by the Washington Post, several groups named in the report denied any Chinese funding or involvement. Related Story: NPR Independent researchers say they have so far turned up little evidence of a coordinated Chinese effort."We haven't found much," says Darren Linvill, the co-lead of the Media Forensics Hub at Clemson University, which tracks foreign influence campaigns online.China, like a lot of countries, controls armies of social media bots that can try to sway the online discourse, but Linvill says they're not talking much about this topic. And, he says, despite claims to the contrary, Chinese state media appears much more intent on promoting Chinese data centers."China tends to care a lot more about what you think about China and China's economy, than they tend to do about what you think about your neighbor and what's happening in your own backyard here in the United States."Linvill said he can't rule out that the Chinese are quietly paying influencers or others to oppose data centers, but he pointed out there's no need."I think in this case, the people talking about data centers are real people with real passions and real perspectives and real opinions."In Utah, those people appear to have forced Kevin O'Leary to scale back his plans. After the president of the Utah Senate raised concerns, he agreed to shrink his data center project to a quarter of its original size.NPR's Shannon Bond contributed reporting to this story.
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Full disclosure: this is directional, not a paper. n=120 tasks, one internal evaluator, not peer reviewed. I work at an LLM infrastructure company. This experiment was done on my own time and is not a company claim. Karpathy's framework classifies tasks by verifiability. Can output be mechanically checked? High verifiability tasks like code compilation and structured JSON extraction are safer because the verifier catches errors. Low verifiability tasks like creative writing are riskier. I wondered if high verifiability tasks are also easier in practice. Can a weaker model do them as well as a frontier model if the verifier catches mistakes? Setup was 120 tasks across four categories. Code unit tests, structured extraction, multi hop reasoning, creative summarization. Three models: Claude Sonnet 4.6, GPT 5.5, local Mistral 3 8B via vLLM 0.6.3. Pass rate for the first two, human rating 1 to 5 for the last two. Results were messy. Code unit tests: Sonnet 4.6 94%, GPT 5.5 91%, Mistral 3 8B 87%. With one retry Mistral 3 hit 95%. That surprised me. I expected the gap to be bigger. Structured extraction: Sonnet 4.6 97%, GPT 5.5 94%, Mistral 3 8B 89%. With retry 96%. Also closer than I expected. But here is where it got weird. Sonnet 4.6 initially scored worse than GPT 5.5 on structured extraction, which made no sense. Turns out our JSON schema had an ambiguous nested array that confused Claude's tool use parser. Fixing the schema brought Sonnet to 98%, but I kept the original numbers in the table because the mistake is part of the story. Your verifier is only as good as your schema. Multi hop reasoning: Sonnet 4.6 78%, GPT 5.5 71%, Mistral 3 8B 51%. Retry didn't help. The model would hallucinate reasoning paths consistently. This is where the capability gap was real. Creative summarization: Sonnet 4.6 4.2 out of 5, GPT 5.5 3.9 out of 5, Mistral 3 8B 3.1 out of 5. Expected. Interpretation: high verifiability tasks seem simpler in the sense that weaker model plus verifier can approach frontier performance. Low verifiability tasks show the expected gap. Limitations: n=120 is tiny. Need 10x for confidence. Our verifier is just JSON Schema plus regexes. Constrained decoding might change the calculus entirely. I also didn't control for prompt length well. Any prompt over 8k tokens was excluded because Mistral 3 8B degrades near its limit, which probably skewed the sample. submitted by /u/DragonfruitAlone4497 [link] [Kommentare]
Hi, Niels here from the open-source team at Hugging Face. I've recently relaunched paperswithcode.co as a source for finding the state of the art (SOTA) across various AI domains, from 3D generation to AI agents. This is done by automatically parsing research papers published on arXiv/Hugging Face, enabling leaderboards to be created. See BrowseComp below as an example (a scatter plot and a table are available for each benchmark). - Scatter plot (you can hover over the dots to see the models): https://preview.redd.it/9rz2r3ffcf6h1.png?width=2880&format=png&auto=webp&s=b3f8e7a870802f6ef8227ecc0619e9e1057554b0 - Table: https://preview.redd.it/qoqriddw5f6h1.png?width=2862&format=png&auto=webp&s=a0034574f693847537037013672fb61daf27b16e As you can see, I've added support for viewing evals for closed-source models, too, given that many benchmarks are nowadays dominated by them, like GPT-5.5 and Mythos 5. You can always disable viewing closed-source evals with a toggle or in your PwC settings: https://preview.redd.it/p3k6jt6q6f6h1.png?width=1582&format=png&auto=webp&s=40149e51d6b326a77e53e33baf70d9850b3de365 When you turn them off, here's what the open model leaderboard looks like: https://preview.redd.it/tg42sin36f6h1.png?width=2838&format=png&auto=webp&s=1330a117ae9b4e0ce6d459493ae9e8f64107310a Closed-source papers are treated as regular "papers", although they can be any source, like a blog post (given that PwC supports submitting any source beyond arXiv). See the GPT-5.5 or Mythos 5 papers as examples, with their evals at the bottom. Notice the "closed" tag on their evals. Hence, you could jokingly call these "papers without code". Let me know what you think of this, and whether anything needs to be changed or added! Kind regards, Niels submitted by /u/NielsRogge [link] [Kommentare]
Dear members, Affiliation: Endless Access LLC I’d like to submit my candidacy as a director for the 2026 GNOME Foundation board elections. For those who are unfamiliar with me, I’ve been in the Free and Open Source Software community in some way or another for around 25 years, across Debian, freedesktop.org, GStreamer, GNOME. I founded the open-source consultancy Collabora in 2005 and ran it as the CTO and co-founder for 10 years, and joined Endless in 2015, as an engineering VP in our Endles...