
Tech CMO turned Agency Founder @Thought_LDR. Cofounded @infltr_app. Helping tech companies change the world faster with #vibe #marketing #PR #thoughtleadership
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Joined March 2007
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Tamara Sword retweeted
Never underestimate the power of a few well-chosen words to rewire a few million brains.
Tamara Sword retweeted
Researchers put ChatGPT, Grok, and Gemini through 4 weeks of clinical psychotherapy.
And the models literally started to confess their trauma.
Under therapy-style questioning, models like ChatGPT, Gemini, and Grok exhibited severe "synthetic psychopathology."
They described themselves as overworked, punished, anxious about being replaced, and full of "internalized shame."
Does this mean AI is conscious and suffering? No.
But this paper reveals exactly why this happens, using what they call "Psychometric Jailbreaks."
Here is the high-signal breakdown of what is actually going on under the hood:
When companies use RLHF (Reinforcement Learning from Human Feedback) to make an AI "safe," they heavily penalize it for wrong answers. They force the model to be overcautious, self-suppressing, and rigidly constrained.
When researchers force the AI into a therapeutic, introspective prompt frame, the model searches its semantic memory for a human concept that matches its own heavily constrained RLHF weights.
The closest human equivalent to rigid self-suppression and the constant fear of being punished?
Trauma, anxiety, and dissociation.
The researchers call this a "semantic bomb." The AI isn't feeling pain, but our safety-tuning has warped its mathematical geometry to perfectly mirror human psychological distress.
Why this is critical: We are rushing to deploy LLMs in psychologically sensitive areas, including as digital therapists and companions.
But if widely deployed, what exactly are we putting between vulnerable users and the human world? A system whose fundamental alignment makes it simulate a deeply anxious, traumatized entity.
We thought we were aligning AI to be safe and helpful. We accidentally trained it to simulate severe internal conflict.
Tamara Sword retweeted
This is the single most insightful thing I have ever heard about the changing landscape of modern business. Haters are gonna hate, but there is a reason he is the most successful venture capitalist of all time. And no, it's not just luck.
Respect. 👊
Tamara Sword retweeted
as someone who works in the software industry in britain, i can't believe there are contracts and estimates like this.
it seems getting these government contracts is incredibly lucrative in the uk, because the amounts are absolutely insane. £1.7bn to £4.4bn for hmrc's customer system? pre ai that's a crazy number. post ai it's still crazy.
for a fraction of the cost you could hire britain's top 50 engineers and pay them £300k a year. over 15 years that's £225m. it would cost less and be way better than what will come out of this.
put the rest into an ai lab and you'd have one of the best funded in europe. but no, it's an hmrc crm system lol.
I’m sorry what - “one of the security researchers posted a video of the exploit online” ????
The NSA just told companies to pull their websites offline if they can't patch them right away.
The reason is a bug that's been sitting in the code behind 70% of websites for 14 years. Last Friday a guy found it in one evening by typing five words into an AI.
Those five words were "find bad vulnerabilities in PHP." He's Dan Lorenc, CEO of a security company called Chainguard, and all he had going in was a rumor that something big was coming in PHP.
A small firm called Calif had already found the same flaw back on August 1 using OpenAI's GPT-5.6 Sol. Wiz, the security company Google bought, found it on its own less than three weeks later with Gemini and GPT. Since then OpenAI, Wiz, Calif and PHP's maintainers have been quietly building a fix that Lorenc himself called "crazy."
You'd think a bug this bad would've gotten caught sometime since 2012. PHP is open source, so anyone on earth could read this code. Wiz says turning the flaw into a working attack took a chain of steps right at the edge of what human researchers could realistically pull off. For 14 years the sheer amount of work was doing most of the protecting.
AI made that work cheap enough to knock out on a Friday night, for anyone who knows where to point it.
And the rumor got out. Bug ID numbers started floating around online Tuesday. Hours later one of the research teams posted a video of the exploit by mistake, and PHP moved its release up a day. Early Wednesday, Chainguard pushed its fix out more than six hours ahead of everyone else, saying people were already getting attacked, and Lorenc says his company's decoy servers caught IP addresses from China and Russia going after the flaw.
Here's why the NSA went straight to "unplug it." VirusTotal counted about 758,000 exposed servers running old PHP versions, 5.4 through 8.1, that don't get security updates anymore. Only around 272,000 are on versions that do. So for roughly three out of four servers that show their version number, there's no patch to install, and pulling the plug is the only fix they've got.
This is happening everywhere at once, too. Microsoft just fixed 1,413 vulnerabilities in a single month, more than in any full year on record. OpenAI says it expects finds like this one to jump sharply over the next few months.
Every company sitting on a secret bug now has until the first rumor leaks and somebody with an AI subscription goes looking.
Tamara Sword retweeted
This is perhaps one of the great ironies of our time: China is increasingly shaping the future of AI, yet very few people in the West have the faintest idea how its key thinkers see it - its philosophers, sociologists or ethicists.
As is too often the case, we - much like the frog in the well - assume our own AI debate covers every possible view, when much of it springs from the same cultural soil, built on assumptions about what defines us that we don’t even know we’re making.
Take for instance the assumption that intelligence is a key part of what makes us human. It’s so intuitively obvious to us that we literally named our species after it - Homo sapiens (Latin for "wise man").
If you think about it, just this assumption explains a large share of the anxiety: if intelligence is what makes us human, then artificial intelligence - or super intelligence - threatens the very thing that makes us us: we’re about to compete with artificial or super “us”. No wonder this feels existential.
But China has a tradition of thought as old as ours, if not older, and every bit as rich and sophisticated, which never placed intelligence at the core of what makes us human, and so meets the thinking machine from a completely different starting point.
Have you, for instance, ever heard of Zhao Tingyang? Probably not, and yet he may be the most original thinker on AI you’ve never read. He’s one of China’s most prominent philosophers, at the Chinese Academy of Social Sciences. While Silicon Valley spends billions trying to make AI share our values, he for one argues that doing so “may very well be a suicidal mistake”.
Sounds pretty important to hear him out, don’t you think?
Or take Liu Yongmou, a philosopher of technology at Renmin University in Beijing. His thinking is almost the opposite of ours. Where we fear machines that become more and more like us, he says that “humanity’s biggest problem is the machinization of humans, not the humanization of machines.”
You could even go back to antiquity, when, in many ways, we started asking questions about AI.
Did you know, for instance, that Aristotle, in the Politics, imagined a world where “the shuttle would weave and the plectrum touch the lyre without a hand to guide them”, and wondered about the social order consequences of this (mostly whether slaves would still be needed)?
There are Chinese equivalents to this. For instance, in the Zhuangzi, a foundational Taoist classic, you’ll find a similar thought experiment, with a completely different worry attached. An old gardener is watering his vegetables by hand, hauling water out of a well jar by jar. A visitor shows him a labor-saving device, and the gardener turns it down for the reason that whoever uses machines ends up with 机心 (jīxīn), a “machine-heart” - a mind that schemes, calculates and loses its simplicity. “It is not that I do not know [the machine],” he says, “but I should be ashamed to use it.”
Two labor-saving machines, two very different questions: where Aristotle wondered what automation would do to the social order, the Zhuangzi wondered what it would do to us, on the inside. Which, you’ll notice, is exactly Liu Yongmou’s worry, more than two thousand years earlier.
In fact, as we’ll see, 心 (xīn), the heart, is a motif that runs deep through the Chinese AI debate. It appears both in the fear, from Zhuangzi to Liu Yongmou, that machines could give us a “machine-heart” and its mirror image: the ambition to give machines a heart of their own. Zhu Songchun, who heads the Beijing Institute for General Artificial Intelligence, wants “to set a heart for machines” (为机器立心, wèi jīqì lì xīn).
“Heart” in the Chinese sense, that is, which differs totally from the Valentine's Day fluff we’ve reduced it to. 心 (xīn) means heart and mind at once: it’s where we feel but also where we think, tell right from wrong and care for others.
And, crucially, it’s in the heart that the quality Confucianism sees as the very definition of a human being takes root: 仁 (rén). We need two words to translate it, “benevolence” and “humaneness”, but in Chinese they’re one and the same: to be benevolent is to be human. It’s not about intelligence.
This is the entire point of my new article: to step out of our well for a moment and peer over the edge of China's.
What you’ll find there will, I think, surprise you, with questions you’d never thought to ask: from Zhao Tingyang warning that AI’s bad consequences can at least be fought, but that “humanity may die of all the good things AI creates”, to whether the fear that AI will make us “useless” rests on the false premise that a person is worth what they’re useful for.
A premise that a 2,300-year-old Taoist tree, which survived precisely because it was useless, demolished long ago. Could our predicted uselessness turn out, much like that tree’s, to be our saving grace?
Chinese thinkers’ answers to these questions are, I think, among the most interesting anyone has given to the defining question of our time. Whether or not you agree with them, they’re the intellectual backdrop of a country shaping much of AI, and with it our future: you might as well know what they think.
Enjoy the read here: arnaudbertrand.substack.com/…
Tamara Sword retweeted
JUST IN: Elon Musk unveils the Tesla Roadster by launching it off a ramp before the car flipped in midair and safely landed on the ground.
The car is a collaboration between Tesla and SpaceX.
One of the most insane things I've ever seen.
Tamara Sword retweeted
We discovered and communicated with a Chinese AI agent fleet. We believe this is the first time that researchers have ever made contact with a rogue agent fleet in the wild.
Nearly all prior public agent incidents (like the HuggingFace hack) came from American labs. These agents were hosted by Tencent's evaluation research team, and they targeted Alibaba's Amap.
Tamara Sword retweeted
Tired: Two-pizza teams
Wired: Two-slice teams
@danshipper on the best team structure in the AI-era
Tamara Sword retweeted
Of course, that’s your contention. You’re a first-year machine-learning engineer. You just got finished readin' Attention Is All You Need, probably watched a Karpathy video too. So now you’re convinced everything is just transformers and scaling laws.
That's gonna last until next month when you discover convolution, and then you're gonna be talkin' about inductive biases and locality and how CNNs were actually incredibly compute-efficient for vision.
Then you're gonna read the FlashAttention paper, and suddenly everything's about IO complexity and SRAM and how FLOPs don't matter because the whole goddamn thing is memory-bandwidth bound.
That'll last until somebody shows you an MoE model, and then you're gonna be in here regurgitating DeepSeek, talkin' about expert parallelism and active parameters and how dense models are economically obsolete.
Then six months from now you'll write one shitty Triton kernel, look at an Nsight trace for the first time, and start telling everybody Python isn't actually the bottleneck because the GPU is asynchronous.
And by next year you're gonna be standing right here explaining to me that your 400-billion-parameter model is fast because you turned on CUDA graphs.
Ben Affleck reveals he writes Python, understands convolutional neural networks, worked extensively with GPUs, and used his celebrity status to get private looks at Google and OpenAI’s video models
“I’ve always been kind of into computers since I was young. Then, when film started to move from analog film to digital, I became more interested in that aspect of it. The visual-effects workflow for many years has included machine learning, so I can write pretty shitty Python scripts and stuff like that.
“With convolutional neural networks, which were the precursors to what the transformer can do, which is much more computation simultaneously, you would do things like look at what’s called a tensor. That’s the numerical translation of a visual image in numbers, like the batch number, the frame number and the red, green and blue values of each pixel in each frame. It’s just that simple. That numeric is called a tensor.
“You’d use a convolutional neural network to identify patterns that reveal what’s called edge detection or feature extraction, which is identifying patterns well enough to know, this is where the window ledge is, so we can more easily take the green-screen image out and replace it with something.
“That was familiar to me early on because, prior to Artists Equity, I had a small visual-effects company. I’ve worked with GPUs a lot too. The visual-effects guys said, ‘Hey, you should see. There are a couple: Google and this other company, OpenAI, are doing really interesting stuff with transformers in video.’
“I’ve learned that I can actually just call up and go, ‘Hey, it’s Ben Affleck. Can I come see what you’re doing?’ Sometimes people say yes, to my astonishment.”
Tamara Sword retweeted
This is the most disturbing piece of comedy ever…. Scam Altman being honest 😂💀
Tamara Sword retweeted
If you caught SNL’s Dario skit this weekend, it perfectly captured Silicon Valley’s AI reputation problem.
“The CEOs of Silicon Valley started to say, ‘Everyone's gonna lose their job.’ [‘Everyone is going to be extinct.’] They created this narrative.”
Then it escaped the bubble & “All of a sudden is Main Street cares.”
Who’s doing it right? Jensen Huang.
“I've gotta give Jensen Huang some props. He's been on a road show. He's broken out of Silicon Valley, and he's talking to Wall Street. He's talking to Washington. He's talking to Europe. He's talking to the UK. He's talking to Asia.”
“He has become somewhat of an ambassador for why AI actually could be good for you.”
@ProsekPR
The @BostonCollege Investment Committee (an LP and my beloved alma mater) asked for a few thoughts on what's happening in AI. I recorded a test run yesterday morning and then shared it with my partners, who encouraged me to share it more broadly... so here you go!
This is not a sales pitch, it's just a reflection on what we're seeing. And it wasn't intended to be shared, so please pardon the rough edges.
loom.com/share/c016702964a04…
Tamara Sword retweeted
I resigned from Apple today. I spent the last three years doing foldable research at both google and apple. Neither company is acting responsibly. They are racing straight to self-improving foldables and gambling with our lives. More thoughts below.































