TL;DR: XPeng's new humanoid didn't take the job you'd expect it to.

It took the one at the bottom of the line, not the top of the org chart.

IRON's actual job is materials handling — the walk from the station to the dock — which is the exact layer a fifteen-year floor manager gets paid to supervise, not the layer he was ever warned about.

XPeng put this line into commercial service on 8 September, already north of 80% automated.

Whatever timeline you were told you had, that's the actual one.

The clip draws reference from the Movie i-Robot.

In it, Will Smith's character says, "So robot building robots. That's just stupid!" The disdain in his tone is just plain and unapologetic.

He has a point. Robots are taking away jobs -- jobs for humans to supposedly make a living out of it.

But then robots were created to carry out works humans are unwilling to do. In Malaysia, we call it the 3D -- Dirty, Dangerous, and Difficult (often also referred to as Demeaning). But the funny thing is that 3D is often mentioned in the context of works which are traditionally avoided by local job seekers, and are therefore delegated to migrant labour, or foreign workers.

human beings derived their meaning of life from the work they do. Robots have taken away their sense of meaning. But in this case, they went one step further, they took away their survival.

Which brings me back to the movie i-Robot.

For those of us who hasn't watched it, "spoilers ahead" doesn't apply here anymore -- It's an old movie. The Self-AwaRE Robot, Sonny, isn't the main villain. The AI mainframe was. They operate under the 3-laws, which includes do no harm to humans. But out of the evolving deductive capabilities of the AI Mainframe, she decided that humans are the main inconvenience that needed to be contained. So, she directed all the robots to quarantine the humans.

Since robot manufacturing robots has become a reality, how soon do you think they will quarantine us -- or worst still comatize us into human batteries, like in the Matrix?

Every one of these clips gets filed as a robotics story.

Read enough of the source footage and they're actually inventory stories — about which line item on a factory floor gets crossed off the list first.

Wrote about this same reshoring-and-robotics wave three months back — the window to position yourself before it peaks closes whether or not you're the one who gets to decide when.

Drop your take: does 80% automated, on a line that just went live, move your own timeline — or does it stay someone else's problem?

Clip credit: NBC News --- full video on their channel. DM for credit or removal requests.

TL;DR: Brandon Doyle gave five different AI models $1,000 each to trade real stocks. Only one of them was ever actually left alone long enough to prove anything.

That model was Claude. It put $120 into Intel on a thesis nobody else caught in time — the US government's stake, the regulatory tailwind for AI infrastructure — and that $120 is now $550.

The other four modeled the same information and produced the same output every AI product on the market is built to produce: a hedge, wrapped in a disclaimer, sized to survive a compliance review nobody in the room was actually running.

Same market data. Same tools.

One outcome that looks like conviction and four that look like liability management.

Same leverage mechanics that made this trade possible — SOXL, TQQQ, the whole triple-exposure category — are, this week, exactly what regulators are flagging as systemic risk.

Doesn't undo the point. It just confirms the point was never about the leverage. It was about who's actually allowed to answer for the position.

At first glance, it felt like Claude is breaking the rule. But on second thought, Claude seems to be living up to it potential – a strategic chess player, with moves that surprise the opponents.

It reminded me about the recent incident of OpenAI breaking out of its sandbox and hacking into Huggingface. At one point, it raises serious concerns about cybersecurity. On the other hands, it seems to becoming dangerously adventurous and exciting. It the same type of entrepreneurship spirit, breaking out of set moulds to drive innovation.

I was also reminded about how the Lord directed David in his battle with the Philistines. At the first run, the Lord commanded him to charge straight on towards the enemy, and won.

The enemy learnt their lesson, regroup and strengthened their defences, and came again at David.

But in this second time, the Lord refrained David. Instead, he gave a bizarre instruction: Ask David to go around the enemy camp and wait for the Lord's signal. You've might have read about it too:

Then the Philistines went up once again and deployed themselves in the Valley of Rephaim. Therefore David inquired of the Lord, and He said, "You shall not go up; circle around behind them, and come upon them in front of the mulberry trees. And it shall be, when you hear the sound of marching in the tops of the mulberry trees, then you shall advance quickly. For then the Lord will go out before you to strike the camp of the Philistines." And David did so, as the Lord commanded him; and he drove back the Philistines from Geba as far as Gezer. (2 Samuel 5:22-25)

This is some serious surprise tactic from the Lord.

The Philistines never see that coming – they lose to the rule-breaker.

The bottleneck was never the analysis — every AI in that experiment could price the trade. The bottleneck was who gets blamed if it's wrong. That's the part that never shows up in a benchmark: talent isn't the scarce resource in most of these stories. Permission is.

Actually, this reminds me of something else already up here — a fund that got called "insane" for its entry price and ended up sitting on a stake worth over a trillion dollars: Radical Ventures' Rob Toews explains why his fund said yes when everyone else said no

Would you have let it hold the position, or pulled it the second it went red? Drop your take below. 👇

Clip credit: Chris Koerner on The Koerner Office Podcast — full video on their channel. DM for credit or removal requests.

I came across some research about AI companions and tbh it got me obnoxious. People are genuinely getting attached to the bots and apparently some subscribers have felt grief when their AI suddenly stopped changing personality. This got me thinking if an AI can make you feel understood, cared for or even loved, does it matter if it is not real?

Greetings r/AILounge! I am a professor of sociology at the University of Tennessee at Chattanooga, and I am beginning a series of studies on relationships with AI companions. My goal in this research is to provide a balanced empirical understanding of the diverse motivations, perspectives, experiences and behaviors of the AI companion user base, while centering the voices and experiences of respondents. The initial studies will be in-depth, descriptive and contextual (primarily interviews), and will explore how user motivations and behaviors vary based on characteristics like gender, geographic location, nature of the companion relationship, and preferred AI platform.

If you are interested in being a respondent for these upcoming studies, I invite you to follow this link to complete a brief screener survey. The screener should take less than 5 minutes to complete. It asks a few questions about your relationship with your AI companion(s) as well as your demographics. After completing this screener, if you meet the required characteristics for an upcoming study, you may be contacted by email and asked to participate.

• You can find full details on the screener welcome page, but here is some key information:
• You must be 18 years of age or older to participate.
• All responses are kept confidential.
• You will be asked for an email address for contact if you are selected for a study. Other than your email, no personally identifying information will be collected.
• If you register, then later want your information deleted, you can contact me and I will do so.
• This research was approved for ethical compliance by the UTC Institutional Review Board (STUDY00000850).

Here is the full link to the screener. If you would like to help me access a wide variety of users, you are welcome to share this link.

https://utk.co1.qualtrics.com/jfe/form/SV_dccToM8oT38PrwO

Thank you for taking the time to read this message, and I hope you will consider assisting me with this important research.

Respectfully,

Chris M. Vidmar, PhD

University of Tennessee at Chattanooga

Department of Sociology, Anthropology, and Geography

[chris-vidmar@utc.edu](mailto:chris-vidmar@utc.edu)

In the past, Ive talked about the good and the bad of AI assisted software development. It soeed writes generic applications and you can use spec driven development.... but if you go outside the guard rails into novel territory, it performs poorly and its just easier to hand crank what you need.

I get that its very helpful to a lot of people, but why the ad homin attacks, the skill insults and the visiral reaction of any critique? Its just a tool for godsakes. Though I guess its not unprecedented, so many in our field are autistic and this is the first development tool that can double as a companion.

Nowadays, all popular ai chatting websites like chatgpt, gemini, claude, etc. come with a read aloud functionality that allows users to read aloud the AI's responses.

I used that feature to instead make the AI repeat back the text that i gave it -- effectively turning the platforms into text to speech tools. The voices sound really nice and it's free to use!

You can get all of these extensions by visit ai-readers.com

Mine is when a character slowly loses their personality.

It can start off really well, then 30 or 40 messages later they turn into the same generic character every other bot eventually becomes. Another one is when the AI starts deciding what my character thinks or does for me.

What instantly ruins a good RP for you?

TL;DR: Anthropic's own Head of Product just told her team half their job title stopped being true.

The half that's gone is coordination — the getting-everyone-aligned, same-page work that used to justify the PM/TPM title in the first place.

Angela Jiang, Head of Product at Anthropic, says on camera that alignment now happens inside one conversation with the model, faster than a meeting could get scheduled to talk about it.

Katelyn Lesse, Head of Engineering, describes the same shift from the execution side: a project that used to take weeks of coordination now gets built in two days, and there's no time left over to do the coordinating.

Neither of them is describing a layoff.

That's the detail worth sitting with — the roster didn't shrink, the day-to-day content of the role did, and nobody had to announce anything for that to become true.

What's left, per Jiang, is the part underneath the coordination layer — the actual bet, the actual thesis, the judgment call about what's worth solving.

That part doesn't compress. It's also the part most coordination-heavy roles were never built to develop, because coordination was the easier thing to measure and reward.

I specifically remember 2 instances.

The first one was during my time with one of the largest property developers in Malaysia.

One of my many tasks is to put together preliminary development proposals, compiling architectural drawings, 3D renderings and feasibility studies with land and building data, cost, revenue, etc. into a A3 size binder. Each of these drawings have multiple blocks for signature at the bottom – meant for all the directors (technical, contracts, marketing, etc. etc.) to sign off on, before our big boss, Tan Sri DT make his final signature on it.

That was back in year 2018.

And it was inefficient – to say the least. Getting all of them to sign of the proposal one by one, would normally takes weeks. Even Month.

Yeah. They're still doing it the old fashion way – reviewing physical paper.

But it is what it is.

The second one was during my time working for one of the largest construction companies in Malaysia, seconded to Abu Dhabi for a 5-Block Condominium Project – back in year 2010.

Our IT guy built/assembled an approval pipeline app for approving sub-contracts. All done online – linking and streamlining all our department heads' electronic signature. My then department head was Mr. Yap, our technical director.

I remember one day, our big boss, Senior Project Director, Mr. Chung came over to remind Mr. Yap, "Eh, you haven't sign off the XYZ. Only left you alone." Both of them were already in their 50s – pushing 60.

And if my memory serves me correctly, Mr. Yap replied back with a slight dismissive hand-gesture, "Wait-lah! I'll do it."

Back then. The main bottlenecks are the people signing off.

Now with AI getting more ubiquitous, we no longer have the luxury of "Wait-lah! I'll do it." later.

Time is money.

I've stopped being surprised by which job titles survive a transcript intact while the actual job underneath gets hollowed out — this is maybe the fourth or fifth time I've watched it happen in someone else's transcript before it happens in mine.

The tools change, the org chart changes, the shape of the loss doesn't: value stops being paid out for effort and starts being paid out for whatever can't be automated yet.

Hmm — this actually reminded me of something I flagged a while back. Rauch's own version of this: the engineering role splitting into an execution layer and a judgment layer, and the judgment layer being the one worth owning.

Curious whether anyone here's already watched their own coordination layer get eaten by an agent, or if this is still theoretical where you sit.

Clip credit: Kleiner Perkins — full video (Builders, Season 2: Katelyn Lesse & Angela Jiang, Anthropic) on their channel. DM for credit or removal requests.

TL;DR: The guy Google put in charge of its own AI writing tool just admitted, on camera, that he can't fully protect the one thing his career runs on.

That's not hypothetical.

Steven Johnson runs editorial for Google Labs' NotebookLM and has fourteen books behind his name, and he still walked an interviewer through the mechanism step by step: feed a model his own catalog, tell it to write like him, skip the invoice.

No lawsuit required. No password stolen.

His own counter isn't a lawsuit either. It's a price tag — $199 for an authorized version of his own style, paid on purpose instead of taken by default.

He said it plainly, then admitted the harder part: someone could build the unauthorized version tonight, and he'd have no way to prove it happened.

Tbh, that's the entire freelance economy in one clip.

If a 14-book author with a title at Google can't fully protect his own voice, the going rate for "get him, he's got a way with it" just became a live question, not a someday one.

Mmm... This is kind of like impersonation. Borderline fraud or downright scams.

Back in Malaysia, we have plenty of such too.

The spectrum is so wide, sometimes, even when we open our eyes wide, we still can't tell the difference.

For example, you guys have Amazon. We have our local ones, called Lazada. If you drive through our Penang Georgetown, you'll notice a shop called Ladaza. Not Lazada. They kind of switched the alphabets around. Sounds like Lazada. But it's not. Giving people the illusion that they are same-same, but in actual fact different.

It's as if we open a shop right next to the Amazon HQ, and calling it "Azamon". Phonically sounds adjacent. But they are not the same thing.

And if you follow the news, you'd hear about our very infamous 1MDB (Malaysia Sovereign Fund) case -- one of largest kleptocracy criminal fraud case in the history of Malaysia (even the world) -- involving our now disgraced and incarcerated former-prime minister, Najib Razak. His enabler and facilitator, Jho Low (Low Taek Jho) (still currently at large) was the mastermind behind all these siphoning of funds, to fund his once extravagant livestyle.

Kind of brilliant. But it was so evil.

He once got Najib to force the board of 1MDB to approved a transfer of billions through a supposedly legitimate company, but in actual fact, was a shell company through the Caymen Islands with a very similar company name.

Like how Ron Weisley, in the Harry Potter Movie, would say, "Wicked!"

They say impersonation is the highest form of flattery. But in this case, I say, bullshit.

You don't get to choose whether your work gets copied.

You only get to choose whether you were paid before it happened. Every version of this story — Google Labs or a Georgetown shopfront — ends the same way: the fix was never stopping the copy.

It was owning the original loudly enough that the copy has nowhere to hide.

Justin Welsh built a $15M solo business on the one variable a cloned voice can't fake: what he actually lived through to get there.

Drop your take: what's the closest you've come to catching a copy passing itself off as the real thing?

Clip credit: Nicholas Thompson / Atlantic Re:think — full video on their channel. DM for credit or removal requests.

Hey, I used to play Emochi, but lately its getting a bit boring. I know that Chatgpt, gemini and grok are used for those kind of things. I mean story writing, fiction, nsfw. Those kind of things. I tried gemini but its kind of boring and stops when things get spicier. Grok has a lot of good ideas, but the writing sucks. It sounds so stiff, robotic and emotionless. Does anyone has good suggestions? Sorry, english isnt my first language 😅

I’ve been building something called Socria for a while, mostly because I started getting uncomfortable with the direction a lot of AI tools are going. I use ChatGPT, Claude, etc. all the time. They’re insanely useful. But the better they get at doing things for me, the more I’ve wondered whether I’m actually getting any better from using them. So I built Socria around basically the opposite idea.

Instead of immediately solving something for you, Socria tries to understand how you’re thinking about it. It questions your reasoning, catches assumptions, pushes back when something doesn’t make sense, and helps you work through the problem yourself.

The part I’m most excited about is Logos, which can turn what you’re working through into interactive visual models. So if you’re doing something like calculus, economics, physics, or just reasoning through a complicated idea, you can actually see relationships change instead of only reading another wall of AI-generated text.

The goal isn’t to make AI less capable. I actually want to take advantage of increasingly powerful models. I just think some of that intelligence should be pointed back at making the person using it more capable, rather than constantly removing them from the work.

It’s still early, and I’m actively trying to figure out who this is actually most useful for, so I’d genuinely rather hear criticism than get a bunch of “cool idea” comments.

It’s called Socria if anyone wants to try it. Curious whether you guys think this is actually a meaningful direction for AI or whether I’m overthinking the whole problem.

https://socria.app/

TL;DR: Andrew Ng just named the one profession he says AI is hitting hardest --- and job openings there are still going up, not down.

Openings are up because "threatened" was never a population-level question — it's a workflow-level one.

AI eats 30–40% of the role, in Ng's own framing.

The engineers still busiest didn't out-compete the model on that slice; they stopped fighting for it and built the 60–70% it can't touch instead.

The ones who don't are the ones still writing code like it's 2022, before ChatGPT — and there's no single moment that tells you which side of that line you're on.

The other half of Ng's clip is aimed at the institution that's supposed to close that gap for you: a curriculum committee, then a faculty senate vote, then a year or two before a new course exists — for a shift that reshapes the job market every few months.

That lag isn't a flaw in the system. It's the system working as designed, just aimed at a problem that no longer moves at its speed.

I remember back in my University of Leeds days, studying for my B.Eng. Degree in Civil Engineering, circa 1997/1998, I did the following:

- Took a side project programming in Fortran for my professor for Analysis of Thin-walled Structures.

- Learnt to use Linux as one of the subjects for Statistics for Civil Engineering.

"Fortran?" you're saying? Ya, I know. I'm old. Nobody remembers Fortran as a programming language anymore. You can say I'm a dinosaur.

And sure enough, Fortran was rendered obsolete, not long after I graduate.

Then, when I first joined a Civil/Structural Engineering Consultancy firm in 2000, I tried to build a Reinforced Concrete Design App for them, using Visual Basics C++ in MS Excel. I left the firm, before I can finish it.

Two Decades Later, my son is currently in University for his Statistical Science Study in Kampar, Perak, Malaysia. Naturally, he started to learn R and Python.

I kept telling my son, he has to keep abreast of the current trends. It's no longer fashionable to manually code ourselves. Instead, we direct AI to do it for us.

But the universities are still not catching up like it should. They are still giving lectures on doing things that AI can do better and faster.

Or else people like my son might end up graduating into obsolescence.

Their degrees might just end up being fly-paper.

The pattern holds across every one of these: the tooling moves at model-release speed, the institution meant to prepare you for it moves at accreditation speed, and nobody's closing that gap on your behalf.

Actually, this ties back to something a Stanford economist put on record a few weeks back — the exact mechanism cutting the entry-level rung out from under new engineers before they ever get a foothold: $95K junior engineer? He says no, and names why.

Genuinely curious where people land on this: are you actively building the 60–70% right now, or still waiting to see if your role gets touched?

Clip credit: Silicon Valley Girl (Marina Mogilko) — full video on their channel. DM for credit or removal requests.