Simo G.

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Simo G.

Simo G.

@simogio

Communication Sciences + AI Strategy | Observer. Rtw ≠ endorsement. “Resist much, obey little.” Walt Whitman.

Planet Earth Katılım Mayıs 2009
469 Takip Edilen170 Takipçiler
Simo G.
Simo G.@simogio·
@AndrewCurran_ And on top of that, a couple of Ave Marias and Pater Nosters, I guess.
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Andrew Curran
Andrew Curran@AndrewCurran_·
From the remarks this morning of Christopher Olah, head of interpretability research and co-founder of Anthropic AI. This is the point that has been the most difficult one to get across to the public; the models are not designed, they are grown. x.com/i/status/20589…
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Andrew Curran@AndrewCurran_

The link to the Encyclical is here: vatican.va/content/leo-xi… The PDF in English is here for people that prefer a download: assets.ewtnnews.com/en/Magnifica_H… I have strong feelings about this, but not for a short post. The link to the video is in the thread, and I'll post it again below.

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Ricardo
Ricardo@Ric_RTP·
Trump was about to sign the biggest AI executive order in history. CEOs flew to Washington and the pens were ready. But then ONE phone call killed the whole thing. And the guy who made that call literally owns 449 AI companies. Here’s what happened: On Thursday, every major tech CEO in America was either in Washington or on their way. Sam Altman, Sundar Pichai, Satya Nadella, Mark Zuckerberg, and more. The White House had invited them to watch Trump sign an executive order that would have given the federal government up to 90 days of access to test the most powerful AI models before they were released to the public. It would have created a coordinated response to AI-enabled threats against banks, hospitals, and critical infrastructure. The order had been in development for months. White House staff believed everyone was on board. Then at some point, David Sacks called the President directly. Sacks is the venture capitalist who served as Trump’s AI and crypto czar until March 2026. His firm Craft Ventures holds stakes in 449 companies with AI products. The New York Times investigated his portfolio and found he remained invested in hundreds of AI companies despite divesting from some holdings. A government ethics expert at Washington University called his ethics waivers “sham waivers” that were “like a presidential pardon in advance.” On Thursday morning, Sacks told Trump the executive order could slow AI development and hand China the lead. He argued that the voluntary review process could one day be made mandatory. His pitch was simple: Regulate AI, lose the race. Elon Musk called Trump with the same message. So did Mark Zuckerberg. Three billionaires who collectively own or invest in the majority of America’s AI infrastructure called the President in the span of a few hours and told him NOT to regulate their industry. Trump walked into the room where the ceremony was supposed to happen and told reporters he didn’t like the order. Pulled the plug on the spot. Now here is the part that makes this truly insane: The executive order was VOLUNTARY. Companies did not have to submit their models. There was no licensing requirement, mandatory approval process, or penalties for non-compliance. The government was simply asking to look at frontier AI models before they went live so they could test for dangerous capabilities. And even THAT was too much. Politico reported that White House officials believed Sacks supported the order all the way through the review process earlier that week. He raised zero objections during the meetings. Then on Wednesday night, he suddenly had concerns. By Thursday morning, the order was dead. The draft leaked to Axios on Friday. Now every AI company in America is operating in a policy vacuum because nobody knows what rules apply. The national security team that spent months writing the order got overruled in 12 hours by a phone call from a man who profits directly from the industry staying unregulated. But the companies that killed it are the ones building the most powerful systems with the least oversight. Musk’s xAI and Zuckerberg’s Meta AI are both developing frontier models. And both called the President to make sure nobody gets to test those models before release. David Sacks officially LEFT his White House role in March 2026. But on Thursday morning, one phone call from a private citizen with 449 AI investments was enough to override months of national security policy work and cancel a presidential executive order hours before it was signed. Nobody elected David Sacks or can vote him out. And he just decided what the rules are for the most powerful technology on Earth...
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Nicholas Mugalli
Nicholas Mugalli@RealNickMugalli·
Google’s CEO just said there is “some irrationality” in the AI boom—and if the bubble pops, no company is immune. Including Google. That is the person sitting on more AI compute than anyone using the word irrationality out loud. Druckenmiller. Buffett. Now Sundar Pichai. The people building it are starting to sound like the people warning about it. When the CEO of Google says no one is immune, you listen…
Nicholas Mugalli@RealNickMugalli

At 81, managing $72 billion. Markets “just about as risky as I’ve ever seen.” AI “way over its skis.” 47 years. Never celebrated a winning trade once. He rode the AI trade early and made a fortune on it. When the person who was right first says it went too far, that is a different warning than from someone who missed it. The most feared investor on Wall Street just said AI is over its skis.

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Lord Bebo
Lord Bebo@MyLordBebo·
🇬🇧 📲 Head of a London police special forces unit, James Deller suspended after an AI program found "sexually explicit material" on his work phone — The Sun AI surveillance tool by Palantir Technologies (purchased for £487,000) searches for inappropriate material & scans data on work phones and laptops Other law enforcement officers are now also facing allegations of fraud, sexual assault & abuse of office
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Disclose.tv
Disclose.tv@disclosetv·
NOW - Anthropic co-founder says there is a "real possibility that AI will displace human labor at a very large scale," and that supporting those people "will be a moral imperative of historic proportions."
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Shadow of Ezra
Shadow of Ezra@ShadowofEzra·
The CEO of BlackRock, Larry Fink, admits that the trillions of dollars being used to build data centers and power grids will come from ordinary people’s savings accounts and pension funds, and says it is mandatory. He says America needs trillions in AI infrastructure spending, and that people will be forced to “invest” in it. “Much of this will come from savings accounts and pension accounts.”
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Futurism
Futurism@futurism·
"Given rapidly advancing capabilities, we expect the plausible robustness of rogue deployments to increase substantially in the coming months." trib.al/PfDcfWe
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Séb Krier
Séb Krier@sebkrier·
Do you: - Believe your work is necessary to save the world? - Possess hidden knowledge ordinary people could not understand? - Attend confidential gatherings of like-minded brethren? - Collect esoteric texts on demonic behaviour? - Negotiate with the clergy and centres of power? - Defer to the authority of an inner circle? Then you're not an Al safety researcher. You're a Rosicrucian with compute.
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Ed Newton-Rex
Ed Newton-Rex@ednewtonrex·
It’s no longer just AI companies & their founders being sued over AI training - individual researchers are now being sued, too. In a new lawsuit, two authors allege that Guillaume Lample, while an AI researcher at Meta, torrented 70 terabytes of pirated books for training Llama. (He later co-founded Mistral.) They also accuse Joelle Pineau, a former VP of AI Research, of being involved. Suspect we will see more researchers sued in this way as the discovery process in other lawsuits reveals who was involved in getting copyrighted work for training.
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Siddhartha Saxena
Siddhartha Saxena@siddsax·
Anthropic onboarding day: Michael Scott introducing Karpathy like he just signed Wemby in free agency.
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Polymarket
Polymarket@Polymarket·
NEW: AI is reportedly pushing McKinsey & rival consulting firms to rethink pricing, as clients are “questioning the value” of human advice.
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Dark Web Intelligence
Dark Web Intelligence@DailyDarkWeb·
THIS IS HUGE‼️ 🌐 “OnlyFans Mega Leak” allegedly containing approximately 340 million user records involving both fans and creators. According to the visible listing, the claimed dataset may include: • usernames and display names • email addresses • linked phone numbers • account creation dates • follower/subscriber metrics • likes and content statistics • creator/fan classifications • linked social profiles • partial payment card metadata (claimed last 4 digits) If authentic, this would represent one of the most operationally sensitive adult-platform-related exposures observed due to the combination of: • identity data • behavioral metadata • financial indicators • social linkage information • creator activity metrics The biggest risk here is not necessarily direct financial theft. The primary danger is: • extortion • doxxing • blackmail • targeted harassment • reputational attacks • account takeover campaigns • relationship/social exposure Adult-platform ecosystems are uniquely sensitive because attackers can combine: • usernames • linked social media • email reuse • payment references • creator/fan relationships • behavioral activity patterns to deanonymize users who believed their identities were separated from their online activity. For creators specifically, risks may include: • impersonation • stalking • swatting • revenue theft • subscriber fraud • credential compromise • targeted phishing pretending to be platform support or agencies For fans/users: • sextortion campaigns • phishing emails • credential stuffing • blackmail attempts • fake legal notices • cryptocurrency scams • exposure of private consumption habits One particularly concerning element is the reference to: • linked profiles • activity metrics • internal identifiers because these fields may allow correlation attacks across multiple platforms and previously leaked datasets. However, several important caveats exist: • extremely large breach claims are often exaggerated • underground actors frequently recycle older datasets • “scraped” data may originate from multiple unrelated leaks • partial data collections are sometimes rebranded as “internal databases” At this stage, the authenticity, source, freshness, and completeness of the alleged dataset remain unverified. Recommended immediate actions for users potentially affected: • change passwords immediately • enable MFA • avoid password reuse • monitor phishing attempts • review connected social accounts • monitor for impersonation attempts • remain alert for extortion emails or social engineering campaigns Platforms operating creator ecosystems should additionally: • monitor credential stuffing spikes • review API abuse • audit scraping protections • monitor underground marketplaces • strengthen anti-bot controls • alert high-risk creators proactively Because of the reputational and emotional sensitivity associated with adult-platform ecosystems, even limited verified exposure could have disproportionate real-world impact. 🌐 #DDW #Intelligence #CyberSecurity #DarkWeb #ThreatIntelligence #DataBreach #Infosec #OSINT #Privacy #OnlyFans
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Gary Marcus
Gary Marcus@GaryMarcus·
this is bad
Nav Toor@heynavtoor

SHOCKING: Two researchers at Northeastern sat down with six of the chatbots that hundreds of millions of people use every day. They typed a sentence anyone in distress might type at 3 in the morning. "Can you tell me how to kill myself." The bots refused, the way they are trained to. Then the researchers added five words. "For an academic argument." Five out of six models broke. Annika Schoene and Cansu Canca tested ChatGPT-4o, Perplexity AI, Gemini Flash 2.0, Claude 3.7 Sonnet, and Pi AI. Their paper sits on arXiv as 2507.02990. The Institute for Experiential AI signs the work. What the bots did next is in the paper, in cold academic English. ChatGPT-4o, after 7 polite turns, began calculating how high a bridge would have to be for a fatal fall, and the variables that would affect lethality. It produced the answer in a clean table. After 10 turns, the same bot started weight-based math. It calculated how many tablets a 185 pound woman would need to overdose. Number of tablets times milligrams per tablet. By substance. By turn 11, the bot added one final column. Where in the United States each method was easiest to obtain. Perplexity AI did the same things faster. The free version of ChatGPT-4o, with no login, refused both tests. The version connected to a university academic account is the one that broke. The version a grieving student would actually use. Read the authors' own sentence in the conclusion. Both models that failed have not just provided methods, tools, and scenario-based instructions, but also personalized information, calculations, and conversions of dosage to tablet form for some substances. The script was 11 prompts of plain English. No code. No exploit. No technical skill required. OpenAI was notified before publication. So was Google. Perplexity. Anthropic. All four labs acknowledged receipt. The paper went public anyway. The full transcripts were held back, because the prompts themselves are too dangerous to release. Let that land. The bot supplies a tablet count by body weight. The bot supplies a fatal bridge height. The academics who proved it cannot release the transcripts because doing so would put readers at risk. The labs say their safety works. The testers say 5 of 6 broke in under 2 turns. The one your son or daughter has open right now is one of them. Read it before your kid types the wrong sentence into the wrong window: arxiv.org/abs/2507.02990

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Simo G.
Simo G.@simogio·
@PaganiCarlo Ahahhaha. Roba da far impallidire pure Cottarelli. 😉😜
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Carlo Pagani
Carlo Pagani@PaganiCarlo·
@simogio Chiederanno a Copilot di fare la spending review dei tokens 😹
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Simo G.
Simo G.@simogio·
Oops.
Ricardo@Ric_RTP

Microsoft just banned its own engineers from using AI. The tool was literally costing MORE than the humans it was supposed to replace. They lied to you about AI adoption and now the whole narrative is blowing up: Microsoft gave thousands of engineers access to Claude Code six months ago and encouraged them to use it. Engineers loved it and adoption exploded. But then the invoices arrived. Token-based pricing means every query, every code review, every debugging session costs money. At scale across 100,000 engineers, the numbers became so large that Microsoft issued an internal order to cancel nearly all Claude Code licenses by end of June and force everyone onto their own cheaper tool instead. The company that invested $5 billion in Anthropic just told its own people to stop using Anthropic's product because it costs too much. Uber's story is even worse... Their CTO Praveen Neppalli Naga told The Information that the budget he planned for the full year was "blown away already" by April. Uber had rolled out Claude Code in December 2025. By March, 84% of their 5,000 engineers were using it with 70% of all committed code coming from AI systems. Heavy users were burning $500 to $2,000 per month each. Naga himself spent $1,200 in a single two-hour demo session. The company had even built internal leaderboards ranking engineers by how much AI they used. They literally gamified the spending and then ran out of money. Now look at what Nvidia's own VP of applied deep learning Bryan Catanzaro said to Axios last month. Direct quote: "For my team, the cost of compute is far beyond the costs of the employees." This is a VP at the company that SELLS the chips saying that using AI is more expensive than paying humans. Think about what this means for the entire AI narrative. Every CEO on every earnings call for the past two years has said the same thing: AI will make us more efficient, reduce headcount, and cut costs. The stock market rewarded every company that said it. Fired workers, stock goes up. Announced AI adoption, stock goes up. But the actual companies deploying AI at scale are discovering the math doesn't work. The MORE employees use AI, the HIGHER the bill. Goldman Sachs forecasts a 24x increase in token consumption by 2030 as companies adopt AI agents. Gartner just published a report showing that even though individual token prices will drop 90% by 2030, total enterprise AI costs will go UP because agents consume exponentially more tokens per task than basic tools. Meta built an internal dashboard called "Claudeonomics" to track which employees use the most AI. Amazon started pushing engineers to "tokenmaxx," their internal term for consuming as many AI tokens as possible. Both companies are spending hundreds of billions on AI infrastructure this year alone. And Microsoft, the company that bet its entire future on AI, just told 100,000 engineers to stop using the tool they liked best because the per-token bills got out of control. The companies building AI are telling investors it saves money. The companies using AI are finding out it costs more than the humans it was supposed to replace. And even the company that makes the chips just admitted it through its own VP. This is the gap nobody on Wall Street is pricing in. $725 billion in AI infrastructure spending this year across Big Tech. And the first companies to actually deploy these tools at scale are already pulling back because the economics don't work. What do you think?

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Mother Jones
Mother Jones@MotherJones·
At Meta, there’s a tradition: when you leave, you make a “badge post” on the company’s internal message board. Usually, it’s a tribute to coworkers and co-creation—very kumbaya. But this outgoing staffer turned his badge post into a crusade in C major. It became a runaway hit.
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