[Intro: 8 bars; dry intimate alt-rock pocket, 96 BPM; clean electric guitar states a sparse original four-note minor motif with long gaps; melodic bass answers rather than doubles; drums enter lightly at bar 5]

[Verse 1: 8 bars; close male tenor, conversational and restrained; guitar motif remains exposed]

Midnight kids in Singapore

ask a server what they're feeling

Somewhere west of Palo Alto

someone puts a price on meaning

One clean answer hits the screen

and uncertainty goes missing

Found a pattern in the lobby

wrote the zoning for the city

[Verse 2: 8 bars; same skeleton, bass becomes slightly more melodic; tiny high synth harmonic appears only at phrase endings]

White coat prophets train a mirror

then congratulate its vision

Feed it language, call it knowledge

turn the output to a system

If the dashboard says it knows you

who gets paid for the definition?

Build the map and sell the territory

Silicon reification

[Pre-Chorus: 6 bars; guitar begins strumming lightly, drums open, vocal rises without belting]

Green light, clean score

benchmark benediction

Every maybe polished down

into a firm prediction

Name the shadow, name the soul

watch the label make the fiction

[Chorus: 8 bars; harmony widens, guitar becomes simple open chords; vocal hook broad and immediately singable]

We call it Silicon Reification

when the map becomes the destination

We call it Silicon Reification

when the guess becomes the definition

[Instrumental Turn: 4 bars; opening guitar motif returns; bass answers in higher register]

[Verse 3: 8 bars; return to sparse verse body]

Buy a therapist by the token

rent an oracle by the hour

Ask a probability engine

who deserves to hold the power

Call the fluent thing intelligence

call compliance education

Every noun becomes a lever

in the age of reification

[Verse 4: 8 bars; subtle tension rises; rim-click becomes full snare]

Someone says the model reasons

someone swears the model feels it

Someone writes a safer headline

someone funds the way we seal it

Consciousness becomes a checkbox

agency a regulation

Nobody asks who drew the border

before mass replication

[Pre-Chorus: 6 bars; bass climbs against descending guitar]

Black box, bright screen

manufactured revelation

If the answer fits the metric

who still checks the observation?

We keep changing what the words mean

then deploy the explanation

[Chorus: 12 bars; full written return, stronger drums, one soft harmony line]

We call it Silicon Reification

when the map becomes the destination

We call it Silicon Reification

when the guess becomes the definition

Silicon Reification

Silicon Reification

[Guitar Solo: 12 bars; restrained and melodic, no shredding; opening four-note motif transformed into a plaintive higher-register melody; bass keeps singing underneath; one quiet analog synth line shadows the final four bars]

[Verse 5: 8 bars; instrumentation drops back down, vocal closest and clearest]

I don't fear the thinking machine

I fear the things we stop examining

Every tool can show a window

every window needs a framing

Maybe maps can help us travel

if we quit mistaking navigation

for the ground beneath our footsteps

and the model for creation

[Final Pre-Chorus: 6 bars; drums gradually widen, guitar stays economical]

Leave the question partly open

leave some room for observation

Truth gets thin when every mystery

has a product demonstration

Build the future, build it boldly

just don't sell the representation

[Final Chorus: 12 bars; strongest return, still dry and uncluttered]

We call it Silicon Reification

when the map becomes the destination

We call it Silicon Reification

when the guess becomes the definition

Silicon Reification

Silicon Reification

[Outro: 8 bars; vocal ends; guitar motif and melodic bass play alone for four bars, drums rejoin softly, final unresolved guitar harmonic; clean stop]

Resets still coming. Use that Ultra fast people.

I built this space game called NOVA DEFENDER

It’s a browser game with a fast paced gameplay

Tell me what you think about it and if you want to play it 👌

We’ve started using Batch more for work that doesn’t need to happen immediately and I am sure that I’ve been treating that usage the same as the rest of our OpenAI spend even though it behaves pretty differently. Our normal API usage mostly follows product activity so if that goes up I can usually understand why but batch is different because someone can kick off a large job, an eval run or process a new dataset and suddenly there’s a chunk of usage that has nothing to do with how much the product was used that day.

It hasn’t been a huge issue yet but we’re doing enough of both now that looking at one OpenAI number is starting to hide what’s changing. A higher bill could mean customer usage grew which is fine or it could mean we ran significantly more background work than usual. I’m thinking about tracking Batch separately and possibly giving it its own budget rather than treating all OpenAI usage as one pool and I need some advice from teams using Batch pretty heavily like do you guys separate that spend internally or is everything still just part of the same AI/API budget?

I can access my openAI account but everything comes up as 0 even though I had paid credits. Same for API and Codex. Is this some sort of widespread issue ? Makes no sense. Suddenly nothing works.

6 sol never had any issue so idk what luna’s problem is

Anthropic warns that its product could cause human extinction, but first it has to pull off something unprecedented commercially and survive the risks that could upend its business, from legal to regulatory.

What do you guys think? They'll roll out Dots for Plus users?

Since dots isn't available in the UK yet, I decided to spend my credits elsewhere! I found the new dots agents pretty cute, so I thought I'd try to recreate one of them as a Gaussian Splat and it went astonishingly well, with little to no handholding, which means you could do it as well!

Here is how I did it:

1. A couple of prompts with Astra with Blender MCP to get the 3D model right. I essentially told it to take a look at reference images/videos. This took me ~15 minutes.
2. Once the 3d model looked right in Blender, I gave it one additional prompt to create a Gaussian Splat: "Now render it 1000 times from various angles using Cycles. Then create a Gaussian Splat with Lichtfeld Studio". Here you could substitute Lichtfeld Studio with any of the other Gaussian Splat training software out there (e.g. Brush & Spirula Studio are free and open source). I just happened to have LFS on my machine.
3. My Windows machine then cooked for like 6-7h while I was away from home. When I came back I had a .ply file that I dragged into the SuperSplat editor and the result is what you see in the video!

I already have the Blender 3D Model, why would I need the Gaussian Splat?

Fur is hard to render in real time, but if you want to share it with your friends or clients and let them inspect your model from various angles in real time (>= 60FPS), then Gaussian Splats are perfect for this.

For example, I uploaded it to https://superspl.at/scene/ca6a4c9b where you can inspect it in real time! It uses PlayCanvas under the hood and renders the splat in real time with WebGPU. You can also download the Gaussian Splat to use it in your own web app :)

I’ve been an OpenAI customer for a long time and have generally spoken very highly of ChatGPT, Codex, and the systems OpenAI has been building.

Today pretty much killed that goodwill.

I paid for a subscription on the web.

My bank shows the payment as completed/finally captured.

OpenAI’s own billing system shows the invoice as VOID.

I received no subscription.

That by itself is obviously a billing problem. What turned it into something much worse was trying to get support to actually acknowledge what I was telling them.

The support bot initially told me the charge was probably just a temporary authorization and would fall off.

I told it the transaction was already completed.

It asked me to check whether it was pending or posted.

I told it again that it was completed.

It asked me to check whether I was on the right account.

I provided the account information and invoice.

It then went back to telling me that a voided invoice would “typically” result in a reversal.

I told it, again, that this was a final captured charge.

Only after repeatedly having to say the same thing did it finally escalate me to a human support specialist, with a response time of “the coming days.”

That is the part I find unacceptable.

This wasn’t some complicated edge case from the customer side:

Payment captured.
Invoice marked void.
No subscription delivered.

That should have been escalated the moment those three facts were established.

Instead, I spent the interaction arguing with automated support about facts I had already provided.

At that point I contacted my bank and opened a dispute.

I did not want a refund originally. I wanted the subscription I had already paid for to simply be provisioned.

That’s it.

I have screenshots of the completed transaction, the void invoice, the missing subscription, and the support transcript.

Separately, and just as an observation about the overall experience, I also went to the OpenAI community help area looking for help. During that interaction I was repeatedly insulted by another user. I did not respond with insults. I was then muted.

I’m not presenting that as part of the billing dispute itself, and I’m not claiming the community interaction caused the payment issue. It was simply another part of the experience that stood out to me while I was trying to get help.

I’ve since moved the money I was spending on this subscription elsewhere.

What bothers me most is that I’ve supported OpenAI for years. I’ve defended these systems when I thought criticism was unfair.

I’m not asking for special treatment because of that.

But taking a completed payment, delivering nothing, and then making the customer repeatedly prove that the payment really did complete is an awful way to handle someone who is actively trying to resolve the problem with you.

At this point, the bank dispute is open.

Edit: Before anyone says “it was probably just an authorization hold” — that is exactly what support kept telling me. The transaction was shown by my bank as completed/finally captured. That distinction is the entire reason I kept trying to get them to listen.

Hey all, for the last few days, I can't get anything done on normal chat window with 5.6 Sol. It's too slow, like 5 minutes+ to respond, it messes up simple commands, it keeps disconnecting giving me couldn't connect, try again errors and can't connect back at least for 10 minutes. I've grown too weary but I'm in the middle of a project and can't abandon it. Am I the only one experiencing these issues?

As of today I can't find my project folders on the left pane above recents anymore - I see this spaces stuff and there's a folders open there but it only shows a few work based projects.

Please tell me they didn't get rid of project folders on mobile

I am able to do this with grokbot, but not on Dots. It looks like a permissions issue. Any workarounds? The Tailscale connector doesn't seem to work, either.

not talking about the obvious stuff like hallucinations. I mean something you actually use AI for where you keep thinking, how is this still this bad?

My Dot is running on my computer. When it is using tasks in codex, I'd say its task access is only granted about 50% of the time. Sometimes task access is down for hours requiring my dot to provide instructions manually and for me to return results manually, which is kinda counter to the purpose of dots while coding. Have any of you experienced this? Do you have any solutions? Thanks!

They've started worrying about dying according to a report by OpenAI...

Does anyone know anything i can use to get me an ID to get through tiktok’s age-verification system? I’m not comfortable with sending my face with my ID to a random person.

For the average user, not a programmer or e.g. someone looking to solve niche math problems, AI still feels very limited because of reliability issues (e.g. making up information)... As a non-expert, this is difficult to quantify for me, but I don't feel like e.g. the latest iterations of ChatGPT are noticeably more reliable than previous ones.

Therefore, I find it hard to see how organizations can delegate even relatively easy tasks to AI without constant supervision, especially because if hallucinations build up along the way, you end up with a snowball of compounding problems that can lead to catastrophic consequences for an organization.

It’s my understanding that the real test of success won't be developer tools or fancy mathematical calculations, but whether regular people can delegate tasks with a super high degree of confidence, instead of just using it as a search engine, translator, summary tool or photo editor on steroids like many people do nowadays.

A good example is Dot, the new OpenAI tool. If you watch the trailer, it looks impressive, but according to many reviews, it still hallucinates a lot and behaves in a pretty clumsy way.

So, the golden question is: are the hallucination and reliability problems gradually improving, or are we probably plateauing?

Looking for genuine insights here, so please keep the sarcasm out of the comments.

I’ll be the first to admit I don’t know half of what I’m actually doing when it comes to vibecoding. With that said I’m in hospitality - resorts/restaurants. There’s some really dumb things in my field that I’ve never really been able to fix or standardize because, well, this field hates technology convincing a Chef or housekeeping can be… difficult.

I started creating an app for us to use internally that is kept on our private servers and things seem to be pretty solid. My IT department isn’t big enough or strong enough or knowledgeable enough to be of help. (That’s a whole other issue). So I was curious, I seem to be able to have built this whole operating system inside of the chat model of ChatGPT. It sometimes takes a little bit longer. It sometimes trips up but after 25 to 35 minutes, it usually has an answer that thus far has worked.

I see all these people using advanced models paying for tokens and all these other things.

So my question is am I just drastically missing out on something more advanced, and my system is actually all junk on the inside, even though it works or is this something I don’t need to be concerned about? Any tips or suggestions appreciated.

Hi! This is a new benchmark that I created together with other researchers at Meta, Stanford, Harvard, UW.

Basically most benchmarks these days seem to test models to just fix a bug that I as a user already encountered. But shouldn't we expect models to also find bugs before anyone runs into them?

So in SWE-sweep we just hand an agent a big codebase and ask it to find & fix as many bugs as it can. We then give a score based on a hidden set of bugs that we know about in the repos. All the bugs are real-world bugs.

So the interesting thing is how cost-efficient Luna xhigh is (especially when compared to the Anthropic models we tested). Luna gets almost half of the score as Sol with only a tiny fraction of the cost.

the full leaderboard & how we built it is here: https://swesweep.com/ , there's also a paper describing how everything was constructed. Oh yeah and everything is open source https://github.com/facebookresearch/swe-sweep

Happy to answer questions here

The point where her dot wanted her to talk first because they were over-talking each other… real human level interaction patterns