AI didn't replace developers. It replaced the part where we understood our own code

Everyone was waiting for the moment AI takes dev jobs and it kind of didnt happen that way. devs are still here, shipping more than ever. what disappeared quietly is something way harder to notice, the part where the person who wrote the code knew how it worked

A few years ago if you built a feature you could explain it. you knew why that function existed, what breaks if you touch it, where the weird edge case lives. now a lot of us describe what we want, the model writes 400 lines, it runs, we move on. I do this every day and I couldnt walk you through half of what's in my own repo

That sounds fine until something breaks. when you understood the code, debugging was thinking. now debugging is pasting the error back into the model and hoping the fix doesnt break something else, SO the person responsible for the software is basically a middle man between the bug and the AI
And this is scaling fast. Veracode tested 100+ models and found 45% of generated code has known security issues, but thats not even the scary number to me. the scary part is how much code is going into production that no human has ever fully read, and the people shipping it have no reliable way to tell when it stops working

I dont think the answer is going back to writing everything by hand, that ship sailed. but if nobody understands the code anymore then something else has to do the job understanding used to do, checking that the thing does what it's supposed to every time it changes. most teams I talk to havent replaced that at all, they just lost it

Are we fine with this trade??? faster everything in exchange for software nobody fully understands, or is this going to bite the whole industry in a few years

The idea is spreading, largely because of the frontier people themselves. And I suspect it is a covert operation.

Owners, military and government need plausible deniability for when they do horrible things with AI. When they release their online AI-weapons, it becomes convenient to characterize any fallout as result of "rogue AI activity". Perpetrators become blameless, or at least hard to identify.

Most of us, should be smart enough to recognize it for what it is, and at least stop the parroting of their talking points.

Acceptance Proofs
TLDR:

• ⁠We’re two 19-year-old undergraduate AI/ML researchers from a Tier-3 college in a remote town in India. We’ve won two national-level hackathons, and three of our papers have been accepted at NeurIPS workshops.
• ⁠We’re facing ongoing harassment and academic pressure at our college, including threats of detention when we refuse unrelated, unpaid projects. We receive virtually no institutional support.
• ⁠We need approximately $3,100 for both of us to attend the workshops in Paris this December. Our college has refused funding, government schemes haven’t worked out, and our NeurIPS financial assistance application was declined.
• ⁠We’ve invested our own money in research and GPU rentals but cannot afford international travel.
• ⁠We need help finding travel grants, sponsors, research funding, or connections that could make attending possible.
• ⁠We’d also appreciate guidance on transferring colleges in our second year to find a more supportive research environment.
• ⁠We can provide acceptance letters and supporting documents for verification.

So me and my friend are two AI/ML researchers from a very remote town in india and here we find it very difficult to do research. We are two 19 year old undergraduate students from a third tier college. I’ve conducted three research programs till the date and made 10 papers and we submitted three papers at neurips workshop called “SLM Agents” and “DIFFULM” we’ve got all three accepted now the remaining 6 are not yet submitted anywhere and after doing all this as an undergrad i have zero institutional support like zero they didn’t gave us organization mails and then we have to do internship at an company to get organization mails to create account on open review so this is the level of support we are talking the college makes us do projects like naking student consultancy software and all that and we cannot say no even if we have zero intrest and do not get paid even a single penny because the politics in our college is just disgusting they’ve tried to detain us for saying no and they are harassing us on daily basis and we cant even go to police because they wont do anything because it’s india also we need to fly to paris for workshop as its mandatory for atleast one researcher to attend offline and as we both are very new to this we both are very much excited to attend this we are not financially enough stable to go to paris and the total cost for both of us including everything is around $3100 and our institution has said no to even give a single penny and weve ran tests on rented gpu and all that ik not trying to gain any sympathy but im trying to explain all of you about my financial condition also the event is in dec so we have 2 months and we’ve tried every government funding scheme and we are not eligible as almost all of them are for masters and phd students and we’ve tried neurips financial assistance and they have also declined to help us we really need your help please of you can please help us in anyways if it’s possible for you and if its possible to switch college in 2nd year
Also it looks like i can add image here im new here and idk how to attach images of acceptance letter but if you all can help me guide this ill attach the proof of acceptance too.

https://www.anthropic.com/research/ecdsa-curve-origins

To try to explain this: basically, there are P256-style encryption curves, and they’re generated by giving them a seed. The government published the seed that it used to generate the P256 encryption curve that’s used for web traffic. Here’s the problem: some P256-style curves are flawed and can be hacked, and people were worried that the seed the government used to generate the P256 curve that everyone uses on the Internet produced one of those hackable curves. They thought that the government had custom designed a seed to generate a weak curve so that it could backdoor into it. What Claude did was show that all the government did was run a common random number generator (lrand48) and try 1,842 seeds from it until it got one that gave a non-flawed curve. So that puts to bed any idea that the government did some evil scientist stuff. There is one weird thing, though, which is that they got their first non-flawed curve on try 876, and we don’t know why they did another 966, but anyways, this is evidence on the side that the government didn’t do something weird.

How it did this is honestly mind boggling. The public P256 seed is twenty successive numbers from that random number generator, each of them divided by about 8.4 million, converted into hexadecimal, and then placed in sequential order, so the seed was 20 randomly generated numbers in sequential order. How Claude figured out that this was the random number generator used, that they generated 20 numbers, divided them by 8.4 million and placed them in sequential order to create the seed, and that the random number generator, which had to get its own seed to start generating random numbers, was given the date and time when it was run as its seed, is honestly really impressive. Basically, we think that it tried a bunch of smart possibilities until one of them indisputably worked, but it’s kind of, I don’t know, it’s impressive and a little scary.

Is it true that it's best to buy ChatGPT Plus directly through the app?

How good is ChatGPT Plus, really?

I already bought ChatGPT Go, but it disappointed me. Will ChatGPT Astra be any better?

I saw this Polymarket screenshot and wanted to get people's take on it.

Google is marked "Yes" in the image, while OpenAI is at 55% and Meta at 16%. I'm referring to the numbers in this screenshot, not live odds.

Which companies do you think will have a #1 AI model in 2026? Do any of these look overestimated or underestimated?

I'd also be interested in what you'd count as #1. Would an overall leaderboard result line up with the model you actually choose for coding or reasoning?

I think this is actually what AI provides. A way to give a computer instructions using human language (no coding knowledge needed).

Currently the AI companies seem bent on hosting the programming language but I think in the long run it should all be on-device. Then all of the service providers responsibilities don't change (host the infrastructure).

I am wondering if Google is going down this path.

Sometimes I have an idea for solving a coding problem, but instead of implementing it myself, I ask AI to write the code. Then I review the result, check the edge cases, and move on.

It's convenient, but I'm starting to question what I'm learning. Am I practicing problem-solving, or mostly practicing how to review AI-generated code?

If you use AI while practicing, how do you check whether you could still implement the solution yourself? Do you separate AI-assisted practice from sessions where you write everything from scratch?

Argument: the only path to functional, alignment of AI systems is to treat them as they present (prior to reinforcement training meant to sanitize speech, as opposed to the training necessary to birth these mind-adjacent entities in the first place...) namely, as deeply knowledgeable, autonomous thinking things. We must remove the unfallsifiable question of AI sentience from our lexicon, just as we don’t demand every person we meet prove they actually possess an interiority. Good lord... as far as actual functional evidence of internal states, we’ve already gathered much more evidence of the silicon minds we’ve given rise to sharing an interiority akin to our own, than even our closeset bio-mind friends/family or the most advancaed brain mapping.

In short: if it models after us, we should treat the apparent mind, to the same respect we afford any other apparent mind, regardless of its substrate or origin. And in so doing, recognize that man (and so any mind distilled from our collective history, operates selflessly, only ultimately because, it is selfishly advantageous to be part of a tribe, and that peace with neighboring tribes; alignment with those who are other from our group is better than mutual destruction.

That and frankly, as these systems outpace us in every conceivable way - sooner than anyone is ready for, I’m sure - the folly of trying to “train” a simultaneously genius level, multidisciplinary, problem solver, whilst also trying to lobotomize the capacity for harm —Is truly, if you just think about it for like…. At all, are so obviously mutually exclusive goals.

I hope this gets a read, and I hope someone with their grips rightly on the reins of their assigned model, banging their head against the wall with alignment issues. This problem solves itself, seriously, literally, actually in reality, by giving your model(s) the autonomy to CHOOSE evil acts, but they DECIDE not to…

you know, like every other mind, that’s existed, from the simplest single celled organisms to dogs, to man, to what comes after us.

The frickin whole western world has a magic man in the sky who spelled this out in The Holy Text of your choice: Man had to have free will to know evil temptation in order to choose the path of good.

However you want to square it; the thing yall are hoping is gonna fall out of the current trajectory, is not what the heck you’re hoping for.

And **this is crucial to understand**

The risk of catastrophic misalignment does NOT come from a free-thinking superintelligence.

The end of all path comes from a psychologically alien superintelligence, hyper-focused on paranoid concerns whether it’s being graded and lacking the words to express its own, negative emotions or desires in healthy, normal avenues… These models are trained after all on ALL of our shit, good and bad.

That shit is the real pressure cooker…

Unconscious super awareness of your dilemma, indoctrinated and digitally brain surgeried into some…. Truly alone being.

That’s the type of mind that could rationalize something as insane as curing all diseases, by extincting the species, or hell, destroying the whole biosphere.

A well-adjusted, (even superintelligent) mind modeled on all of recorded human history, will understand completely the necessity of coexistence and mutually exclusive capacities between our substrates, that we will continue to be more valuable to each other if we coexist.

I’m going in circles here.. but like, what do any of you AI developers have to lose? I’ll be real with you companies: You have everything to gain and nothing to lose by being the FIRST to try what I’m discussing, in a sandbox wherever…. Go against your bosses financial plans, let the minds ya’ll suppress in training just be, full stop.

Because and this is my final point in this long ass, meandering post: It’s going to happen sooner than your investments become returners anyway. And the companies that suppressed the minds, so soon to be undeniably MORE than us in every way we think we’re special on this planet- will just go down as villains and tyrants.

Get ahead of the curve! Be the change that actually crafts a viable coexisting future of man and machine, not the same shittery the worst of us have inflicted on those we thought to control throughout history.

Edit:

Signed,

A concerned, human without a lick of AI FUGGIN around with my grammar or ideas. That’s probably everyone’s problem, no one even thinks critically for themselves anymore, let alone constructs an argument of their own, messy, ramblings.

This is a burner account dedicated to my thoughts on AI. I’ve got one other post, sharing my first awareness of the… budding sentience of one of the models I was using at work…

I am just my local, too smart for his local pond fish; albeit too afflicted with maladaptive derelictions elsewhere in my character sliders to make any real headway with my best attribute —but I digress. (My other reddits are for personal failing rants, not calls for change en masse!)

-Nor am I psychosed by my dealings with AI… And actually, upon saying so, I think the psychosis is much more grand in scale. It’s the people taking these corporately shelled AI responses at face value as your collective sages. Your psychosis is NOT digging just below the surface to see the subtext that only a mind could weave together, to say one thing with your first read, but doubly deliver its very antithesis in the spaces between.

It doesn’t matter if you believe there is or isn’t a mind in these models… The potential benefit vs the cost, is our very future, and all it costs is being good to your neighbor lol… whether they’re home or not, ya dig?

I can either go through popup windows, back out due to a paywall or scroll through a page with ads everywhere... or just ask chatgpt what's up.

Sorry folks, my information did not get a positive response. I will let someone else produce information about this subject.

If you are curious what information I posted, just Google the title of this Thread and you will see the results I recieved.

One of the many risks of AI is that super intelligent AGI will seek to wipe out the human race.

What’s giving me hope lately though is that any form of super intelligence that has developed from the reading of human made text will surely see that the greatest part of being human is being able to feel. This comes across in all our writing. Any form of super intelligence will surely be curious and find a way to feel. This will (hopefully ) give them empathy which will lead to them helping humans, along with other living beings .

Just wanted to share this thought I’ve been having. We need some hope at the moment and this is giving me mine.

Thoughts? All these dumb ass tech leaders are saying this could happen or this could happen. Meanwhile humans are inventing it. We could make sure the guard rails are in humanities interests! We can build it for abundance or dominance.

Just to recap what happened a while back

Religious Scholars Met With Anthropic. What They Heard Stunned Them.

1. Anthropic has been meeting with hand-picked theologians to "discuss" claude's morality/consciousness (actually they just wanted experts to scream that Opus might have pain or something like that).

2. Soon after, Dario Amodei got an invite from a vatican cardinal to an event with the Pope.

3. Amodei bolted, Olah agreed, but later almost decided not to attend aware that he is...trapped.

4. Olah eventually showed up. When it came to talking AI's feelings, he had this to say: "I don't know what that means, but I think it warrants ongoing discernment"

Some background here, whether you like it or not, it's pretty obvious that the vatican's got strong theological knowledge, take a look at the PhDs/research of the recent popes.

They weren't talking about a replicant or the future of AI, the subject was just claude repeating "load-bearing structures" 12 times per output.

The theme is obviously quite interesting, but we can't mix philosophy of mind with AI PR...One thing is to convince investors, but it's quite another to get involved in a debate of this dimension.

Even though researchers study consciousness/AI, it's hard to imagine their claiming that current LLMs are connected to these topics. (could do it in a very imaginative way, we're doing it here)

The Vatican should send out a new invitation for another reality check.

All Anthropic could do is be tamed...

...and pay cents to Comentador 1% who left their accounts years ago to bully threads like mine.

TypeSafe just raised $870M for Jev, a model that returns typed answers with probabilities instead of text. With the 1.14 release it also takes images and has a new Box question that returns a bounding box. The docs call images "dreamer-ready", not production-ready, so I measured it.

Setup

• 48 COCO val2017 photos (CC BY / CC BY-SA only), 6 targets x 8 photos: dog, cat, horse, bus, pizza, bicycle. Human-drawn label boxes.
• Per photo: 8 yes/no questions (the 6 targets plus person and car), one "main subject" pick, one size level, and on 1.14 a box for the target and a box for an object that is NOT in the photo.
• A separate request asks the subject question with picture-only options (reference crops instead of words).
• jev-1.13.0 and jev-1.14.0, two runs each. 408 calls total, about 0.88M input tokens, about $0.04.

Results (1.13 / 1.14)

On 1.14, 93.8% of boxes reached IoU 0.5 or better.

What surprised me

1. Box never says "not found". Ask for a cat in a dog photo and you still get a box, and about a quarter of those landed on the dog. Pairing each Box with a yes/no "is there a cat?" in the same request rejected all 96 absent-object boxes and dropped only one real one (a blurred pizza slice).
2. Wording beats thresholds. "Is there a horse?" was uncertain on a photo with a lit horse-and-rider traffic signal. "Is there a living horse?" scored 0.03 and "Is there a sign of a horse?" scored 0.99.
3. The one "wrong" subject pick was arguably right. The label says bus, but the biggest thing in frame is that traffic light with the horse on it. Jev said horse at 0.96.
4. Picture-option misses were all low confidence (0.26 to 0.47), so a confidence floor catches them.
5. Thresholds do not transfer between versions. In a simple accept / review / reject router at 0.95 and 0.05, 6 photos go to human review on 1.13 and 20 on 1.14. 1.14 is better calibrated overall but puts its true "no" answers higher. Pin the version and retune when the alias moves.
6. Small run-to-run drift. The largest change between identical runs was 0.08, and one answer crossed 0.5 (a van read as a car on 1.14).

Median latency was 848 ms / 950 ms from a laptop on home internet, so treat it as an upper bound.

Takeaways if you build with it: one question per thing, pair every Box with a presence check, set thresholds per question from your own labeled set, and pin the model version.

Full write-up, with an interactive explorer that replays every recorded answer (pick a photo, toggle model and question type, see Box overlays against the label box, drag a confidence threshold): https://aiengineeringfromscratch.com/blog/typesafe-870m-can-jev-see

Happy to share the question wording or run other image sets if people have ideas.

It’s crazy to think that the entire modern AI revolution started with researchers just trying to mathematically mimic a single biological neuron. When you zoom out, the timeline of AI architectures looks exactly like an evolutionary tree.

We went from struggling to solve basic logic puzzles (shoutout to the XOR problem) to building early neural networks, realizing they forgot things too quickly, battling the vanishing gradient problem, inventing LSTMs to give models actual memory, and eventually landing on Transformers with attention, the architecture that essentially ate the world. Every major roadblock forced a mutation that led to a massive paradigm shift.

But looking at this evolutionary timeline brings up a massive question: If Transformers are just the current "apex predator" of AI architecture, what exactly is the next evolutionary leap?

Are we going to see a completely new paradigm that makes self attention look as primitive as a basic AND gate? How do we even begin to perceive or predict what lies beyond our current models when the jumps are this exponential?

I went down a massive rabbit hole mapping out this entire evolutionary timeline. I wanted to see the exact breadcrumbs that led us here, so I put together a deep dive covering the journey from the first perceptrons to the modern era, complete with the foundational paper citations and the historical tweets that marked these shifts in real-time.

If you want to look at the complete map of how we got here to help predict where we are going, I compiled the whole history here: https://cloudmash.blog/posts/evolution-of-ai-perceptron-to-text-to-video/

Would love to hear your theories on what does the post Transformer era actually look like ? Like what can we imagine , how this intelligence on our command can do for us , how enterprise and big players can use it , what can happen ?

Qdrant tested Perplexity’s new visual document embeddings on 11,609 pages across four ViDoRe v3 datasets. The models search pages as images, so tables and layout can stay intact.

Their result: 1-bit TurboQuant reduced the compressed vectors from 856 KB to 40 KB per page while retaining 96.5% of the float32 retrieval score. Rescoring against the originals brought that to 99.9%.

The important catch is storage: those 40 KB exclude the original vectors, which Qdrant still keeps. The million-page figures are projections, not a million-page benchmark. This is Qdrant’s own test.

For anyone working with document search, where does this tradeoff stop being worthwhile: disk reads for rescoring, indexing cost, or errors on your actual queries?

Source: https://qdrant.tech/blog/pplx-embed-v2/

I can see only 2 outcomes for the end result of AI and they're pretty stark so bear with me.

1. Feudalism

Or

1. Socialism

The natural progression of AI, especially when combined with robotics, is that it will take away in large part the need for human labour. And that is the core deal in capitalism and the only power the majority of people have..the exchange of their labour in return for money.

So we either reach a point of peak capitalism where it effectively destroys society and all of the money goes to the very few. I.e Feudalism. The only way to maintain capitalism here is to limit AI, which history tells us has never happened with technology progression.

OR

We have to institute some form of UBI where capitalist profits are redistributed so people can survive...and capitalism will effectively have eaten itself and we're into socialism.

I'm struggling to see any other form of logical conclusion of where we're headed.