Dr. Ruth, Ph.D.

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Dr. Ruth, Ph.D.

Dr. Ruth, Ph.D.

@LCCWC_Ruth

#Cybersecurity researcher, improving #communications. Cybersecurity #capacity, #policy, #digitaldivide, #digitalHygiene All views my own. 基督門徒

가입일 Nisan 2009
861 팔로잉501 팔로워
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Brian Allen
Brian Allen@allenanalysis·
🚨 HOLY SHIT. A U.S. citizen just testified before the Senate that ICE agents ignored his passport, detained him, placed him on suicide watch, and released him WITHOUT charges or explanation. Read that again. An AMERICAN CITIZEN says he showed agents his passport multiple times… and still ended up locked in a cell under 24/7 lights, stripped naked, wearing a hospital gown while guards watched him constantly. His family reportedly had no idea where he was. Then after all of that? No charges. No explanation. Just released.
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Glenn Tunes
Glenn Tunes@glenn_tunes·
ABSOLUTELY FUCKING REPULSIVE THAT PETE HEGSETH REMOVED COLIN POWELLS NAME FROM A LIST OF NOTABLE AMERICANS BURIED AT ARLINGTON CEMETERY 🤬 HE ALSO REMOVED THE NAMES OF EVERY PERSON OF COLOR AND EVERY SINGLE WOMAN ON THE SAME LIST 🤬ONLY WHITE MEN WERE LEFT IN PLACE 🤬 SO PLEASE TELL US ONE MORE TIME HOW THE TRUMP ADMINISTRATION RESPECTS AMERICAS FALLEN HEROES 🤬
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Brian Allen
Brian Allen@allenanalysis·
BREAKING: A federal judge is now signaling the Trump administration’s so-called “weaponization fund” may have emerged from collusive litigation and could potentially amount to fraud on the court. That is nuclear-level language from a judge. “Fraud on the court” is not normal criticism. It is reserved for situations where a court believes it may have been manipulated, misled, or used as part of a coordinated scheme. And the judge reportedly pointed to two giant red flags: - the massive $1.8 billion settlement amount - and concerns the opposing sides may not have actually been acting as true adversaries Translation? The court is openly questioning whether this lawsuit was partially engineered to create a taxpayer-funded political compensation machine. That is an absolutely extraordinary development.
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Gold🤍🌚
Gold🤍🌚@GOLDBABYO·
My husband, sweet man that he is, doesn't want to press charges because he "doesn't want to cause drama in the family." Meanwhile I'm like, oh I will BRING THE DRAMA. I have an internal "Eye of the Tiger" training montage going in my head, rehearsing exactly what I'm going to say/do. So, Sunday June 14th. Let's freaking gooooo.
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Gold🤍🌚@GOLDBABYO·
Ok, I need to vent. My MIL has dementia. It's very sad, but she's 90, and she's not suffering, she's just... not there. But it's still terrible. She'd been living alone, and a lot of mail/bills had piled up. My husband went through it all, and found a credit card bill of $6,000. Almost all of the charges were for Instacart and Uber Eats. Which is kind of odd, considering my MIL has never once used the internet in her whole life. 🤔 Husband asks MIL if she ever gave her credit card to anyone else or added an authorized user. She says no. Not that she's exactly a reliable narrator at this point. I told my husband to just report the charges as fraudulent, it'll take the credit card company probably 10 seconds to figure out where the Instacart & Uber Eats orders were delivered, and bam, there you have it. Fraudster found.
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Tymofiy Mylovanov
Tymofiy Mylovanov@Mylovanov·
Petraeus: The U.S. has not remotely learned the lessons it should from Ukraine. This is the future of war: Ukraine alone uses 10,000 drones a day, and 90% of Russian casualties are caused by drones. That should force institutional change. 1/
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Dr. Ruth, Ph.D.@LCCWC_Ruth·
AI can be a powerful tool- but it should be used judiciously. We need ways to control the levels of inference we want to control token usage. In the end, token controls could lower costs and reduce the demand for new data centers
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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Hedgie
Hedgie@HedgieMarkets·
🦔Fortune published a piece this afternoon connecting Microsoft and Uber's AI cost overruns to token economics, with a headline that lands hard: "Microsoft reports are exposing AI's real cost problem: Using the tech is more expensive than paying human employees." Underneath those headlines, the unit economics tell the story. OpenAI is projected to lose $14 billion in 2026, spending roughly $2 for every dollar of revenue it brings in. Anthropic is in a similar position with break-even not projected until 2028. GPU rental prices for Nvidia's newest Blackwell chips jumped 48% in just two months. OpenAI's response was to close a $122 billion private funding round at an $852 billion valuation, the largest in history. My Take The token pricing story is really an IPO timing story. OpenAI, Anthropic, and xAI all need to go public in the next 18 to 24 months because the private market cannot keep absorbing burn rates like these indefinitely. Public markets do not accept "we will figure it out" as a line item on an S-1, they require disclosed unit economics with a credible path to profitability and a date attached. That deadline is why the price increases are happening now rather than next year. The labs need to show declining loss curves before the filings hit, and that means enterprise customers have to start covering more of the actual cost regardless of whether the productivity math holds on their end. Every token bought over the last two years was effectively subsidized below cost by venture capital and hyperscaler cross-subsidies, and that subsidy has a hard deadline. Uber publicly admitted burning through its entire 2026 AI budget in four months, and CFOs at major enterprises are starting to flag the same pressure. The labs cannot keep losing $2 per dollar of revenue once they file public statements, so the cost transfer to customers accelerates from here. For investors, the question is not whether these companies are valuable. They clearly are. The question is who absorbs the difference between what enterprises can budget and what the models actually consume between now and 2028, and right now the answer is the hyperscalers funding the buildout. That is why I have been watching Microsoft and Amazon capex commentary more closely than the lab announcements themselves. Hedgie🤗 Link: fortune.com/2026/05/22/mic…
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Congressman Christian D. Menefee
Enslaved Africans brutalized and forced to build this country for generations: *no reparations* Black Americans lynched and denied rights by their own government for more than a century: *no reparations* Insurrectionists storm the Capitol and are rightly prosecuted: can apply to a $1.7 billion compensation fund because they were “horribly treated” Absurd.
Acyn@Acyn

Reporter: Why should taxpayers pay $1.6 billion for January sixers? Trump: It’s being very well received. I know very little about it. I wasn't involved in in the whole creation of it. This is reimbursing people who were horribly treated.

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Sarah Larchmont
Sarah Larchmont@SarahLarchmont·
Almost. Two. Billion. Dollars. For guys like this. (are you angry? You should be.)
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Amber Woods
Amber Woods@AmberWoods100·
NEW They quietly brought back cyanide bombs on public lands. Spring-loaded traps that fire sodium cyanide into animals’ faces. These devices have reportedly killed pets, endangered wildlife, and even injured children in past incidents. And now they’re back. What kind of country are we becoming?
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Jamie Dupree
Jamie Dupree@jamiedupree·
President Trump says those prosecuted for Jan. 6 should get money from the federal government. That means giving cash to people who violently assaulted police at the U.S. Capitol. Here's a few possible recipients from what Trump called 'A Day of Love'
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GBX
GBX@GBX_Press·
🚨 JUST IN: ​Trump’s sons became partners in a Kazakh mining company. ​Right after the company received a $1.6 billion government contract in the US! ​Are we having fun yet, America?
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MSU
MSU@michiganstateu·
The 517 is where a top 30 public university, a top 10 college town and the heart of Michigan meet. It's home, and so are the people here.
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Dr. Ruth, Ph.D.@LCCWC_Ruth·
This is an amazing story of Qunfei’s hard work and intelligence in the face of overwhelming odds. 👏👏👏👏
陈剑Jason@jason_chen998

这次美国访华晚宴坐在马斯克和库克中间C位最亮眼的,是蓝思科技创始人周群飞,从农村打工妹到中国女首富,完全没有任何背景全靠自己白手起家。她出生在湖南的一个小村庄,5岁时母亲去世,父亲也因工伤残疾双目失明,家徒四壁,16岁交不起学费被迫辍学去广东打工,在一家工厂流水线打磨玻璃,白天干活,晚上疯狂自学,考了会计证、电脑操作证等技能证书,就这样过了几年,她拿着靠打工攒的2万块,拉上哥哥姐姐、嫂子姐夫等8个亲戚,在深圳开了一家小作坊,做手表玻璃加工,她一个人修机器、跑销售,就这样又干了4年。 到了2000年后手机行业开始大规模发展,一次偶然的机会她的手表玻璃厂接到了TCL手机屏幕的订单,她看到了手机玻璃市场的巨大潜力,于是迅速成立了蓝思科技,专门负责手机玻璃的生产研发和销售,一开始只做国产手机和山寨机,但是直到有一次想谈下摩托罗拉的订单,但外企的质量要求非常严格,她赌上几乎全部的资源配合摩托罗拉,拿下了全球销售超过1亿台的V3订单,直接把蓝思科技推到了行业领先位置,随后顺利拿下诺基亚、三星等外企。 关键的转折点又一次出现在了2007年,当时乔布斯发布初代iPhone,彻底把手机往全玻璃触屏的方向变革,乔布斯那变态的工艺要求全球都找不到符合的厂商,周群飞敏锐的意识到这又是一个巨大的机会,于是带领团队和苹果工程师联合攻关了3个月,突破关键工艺,成功量产了第一代iPhone玻璃面板,从此拿下苹果长期合同,后续的iPad、MacBook等几乎所有苹果设备全部都交给了蓝思科技,也帮助蓝思科技在触摸玻璃面板领域成为全区最大公司。 这也是为什么她能坐在库克旁边,那为什么马斯克也坐在她旁边呢? 蓝思科技在玻璃面板干到全球第一后,开始往更加多元的智能化设备发展,包括汽车座舱和机器人,其中汽车领域包括车窗、中控等已经拿下了特斯拉、宝马、奔驰、理想等30家车企,机器人领域则主要负责关节、传感器等部件,这些都和马斯克的业务有深度重合。 一个15岁辍学只有初中文凭的女生,从湖南农村出来白手起家成为中国女首富,40年后进入中美会谈,坐在了马斯克和库和中间,这就是周群飞的故事。

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St. Wilding Gyres
St. Wilding Gyres@wilding_gyres·
This is the most artfully constructed and well-planned humiliation I have ever seen.
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