Dessa is a full-duplex speech-to-speech model that you can run on consumer GPUs.

This is a GPT3 moment for speech.

Hey everyone,

I wanted to share my situation with OpenAI’s automated moderation and chain-banning systems, as it just completely disrupted my daily workflow.

On August 20th, a secondary account of mine was flagged and banned for alleged "election interference", which I only noticed today. My usage in Germany was strictly related to legal, democratic civil engagement and anti-extremism projects. Nno spam, no bots, no real-world election manipulation.

Today, my main working account which I rely on daily and had zero violations was suddenly deactivated out of nowhere due to system-level linking to that previously banned account.

I submitted an appeal for the working account, explaining the situation and the legal context in Germany. Less than 3 minutes later, I received an automated email stating that my account had been "carefully reviewed", the decision was final, and further inquiries would be ignored. No human being ever looked at this.

To make matters worse, I am now completely locked out of exporting my projects, chat history, and work data. When trying to access the privacy / data export tools, the system requires a login, which is blocked due to the account suspension.

Under EU law (Article 15 GDPR), companies are legally required to grant data access regardless of whether an account is active or suspended. Blocking data access behind a disabled login is a blatant compliance failure under European law.

If you are an EU user relying on OpenAI for daily work, be aware that trigger-happy automated security filters have zero understanding of local European political or legal context, and a single false positive on one account can retroactively destroy your main working environment weeks later. Once the bot loops you, there is zero human support, and your data is held hostage.

I am now filing formal GDPR data access requests directly via privacy@openai.com and escalating this to the national Data Protection Authority (Datenschutzbehörde). Has anyone successfully retrieved their data or unbanned a main account in a similar chain-ban situation?

Im pissed.

On 26 October OpenAI said its internal models proved three results. The first is the local smoothing conjecture in every dimension, which would also settle Kakeya and Stein’s restriction conjecture. The second is a disproof of the Exponential Time Hypothesis. The third is a rigorous proof that quantum chromodynamics exists, with pure Yang-Mills existence along the way. All three were formalised in Lean, and the Lean proofs for the maths and the ETH results are public on their GitHub. This is crazy progress.

None of it has been checked by the wider community yet. The ETH group is Impagliazzo and Paturi, who proposed it in 1999, with Ryan Williams, and their open letter says their involvement “should not be taken as certification of the claim”. ETH being false doesn’t mean P equals NP. The Yang-Mills result claims existence only, not the mass gap, so it isn’t the Millennium Prize. I wrote up what each claim means in plain words, the dates, and the question of who gets the credit, https://www.anchorterminal.com/blog/openai-three-results

In every benchmark other than Agents' Last Exam, GPT 6.1 Sol outperforms 6.1 Terra at almost same costs.

I have been running local models for a while now and got tired of watching the power meter go up every time I wanted to ask a question. Data centers use ridiculous amounts of electricity and water just so people can chat with an AI. I decided I did not want to be part of that anymore.

So I connected the hamster wheel. Wally runs, the model runs. That is the entire setup. Right now the speed is sitting at 0.1 and the energy reading is at 1019 with the AI load around 22 percent. It is not fast by any normal standard, but it works and it does not require any extra power from the grid. The only thing I have to do is keep the water bottle full and the seeds topped up.

He has no idea he is the reason I can run inference completely offline. He just likes the wheel. I like not needing a data center or a bigger PSU or any of the usual excuses people give for why local AI is hard. He provides enough. I do not need more power. The model answers, the hamster keeps spinning, and nothing leaves the house.

It is surprisingly stable too. He takes breaks when he wants, but when he is on the wheel the tokens keep coming. No cloud fees, no rate limits, no waiting for some distant server farm to free up capacity. Just one small animal doing what he already does all night anyway.

Has anyone else found a way to run their local models without constantly needing more power?

More on github:
https://github.com/kMegapnbedt

OpenAI claims its models produced three major results: proofs resolving long-standing problems in harmonic analysis, a disproof of the Exponential Time Hypothesis, and existence proofs related to quantum field theories including QCD. The mathematics and computing work has been published and formalized in Lean, while independent experts are now reviewing the claims; the physics materials have yet to be released publicly. If even one result survives scrutiny, how much could AI change the way advanced mathematical research is conducted and verified?

I know this is a relatively tiny feature compared to things like Dot and all the other announcements, but I'm genuinely impressed by how useful these suggested follow-up prompts have become.

Look at the example in my screenshot. It's not just suggesting some generic question or offering to summarize something. It's understanding the context of what I'm working on, identifying the next decision that needs to be made, and even preserving an important constraint from the project.

It's basically anticipating what I was about to ask, except sometimes it articulates the request better than I would have.

There's something wonderfully practical about a feature that removes friction rather than introducing another elaborate workflow or agent to manage. Dot has shown no initiative for handling any of my projects. It will say the status of a project and then just zone out. I have to constantly say "continue", "whats next", "go ahead", "why didnt you start yet". It's EXTREMELY lazy.

Anyone else finding these suggestions surprisingly good?

Half the token price for "similar" intelligence to sol/medium, much better than luna on some benches like terminal bench... but the issue is pretty plane as day...

You need to go from medium to xhigh to get to that level of "similar" usage but still slightly worse... and guess what that 2x cheaper cost doesnt make up for the 2-3x more token usage, so it ends up being more expensive than just using sol-medium for the slightly better performance AND cheaper lol

Has the need for cash/money/investment just moved more towards marketing and sales? Is it actually now harder for the little guy to make it with a great idea?

Hey everyone,
Like a lot of developers building AI applications, I spent months looking at standard leaderboards (Chatbot Arena Elo, GPQA, etc.) to figure out which foundation model to use. But when it came time to actually push to production, the leaderboard scores stopped mattering—and the infrastructure realities took over.
Specifically, I kept running into two massive bottlenecks:
1. The API vs. Self-Hosting Breakeven Line: At what exact monthly token volume and prompt-caching hit rate does paying OpenAI or Anthropic stop making financial sense compared to renting Spot GPUs and running quantized weights?
2. Real VRAM Sizing: Model weights are only half the story. Once you factor in context windows and KV cache memory overhead, standard sizing charts fall apart, leading to unexpected Out-Of-Memory crashes in vLLM or Ollama.
Because I got tired of doing this math across 15 different tabs and spreadsheets, I built a free, zero-login telemetry and FinOps workbench that tracks 280+ models to solve it (happy to share the link in the comments if anyone wants to test it, keeping it anonymous here to respect no-promo rules).
It lets you:
Run Live Token Arbitrage Simulations: Drag sliders for monthly token volume and caching (0% to 95%) to find your exact dollar breakeven between commercial APIs and self-hosted cloud GPUs.
Calculate Exact VRAM Footprints: Check memory requirements across FP16, FP8, INT8, and Q4, and generate 1-click copyable vllm and ollama CLI launch commands.
Model Multi-Agent Routers: Simulate how much you save (typically 60% to 80%) by routing triage prompts through smaller models before escalating to frontier models.
For those of you shipping LLMs to production right now: how are you currently calculating your token spend at scale, and do you default to APIs or self-hosting? Curious to hear what your engineering stack looks like!

Three fields. Three reported breakthroughs. A lot for researchers to unpack.
 
On October 26, OpenAI announced AI-produced results covering:
 
• Local smoothing in all dimensions, which it says also resolves the Kakeya and Stein restriction conjectures.
• A refutation of the Exponential Time Hypothesis, a major assumption in computational complexity.
• Rigorous existence proofs for quantum field theories, including QCD and Yang–Mills existence.
 
OpenAI reports Lean formalizations and independent academic examination. Refuting ETH does not itself settle P versus NP, and Yang–Mills existence alone does not resolve the full Millennium Prize problem, which also requires a mass gap.
 
Read OpenAI’s announcement

[Intro - 8 bars; instrumental; prominent deep melodic electric bass, dry dance drums, distant warm analog synthesizer]

[A Motif - 8 bars; intimate, lightly reverberant, rhythmic melodic singing]

Every time I look, the colors move

Every little change becomes a clue

Every time I look, the colors move

Every little change becomes a clue

[B Motif - 8 bars; gentler melodic response, sustained final vowels]

So tell me what you see

Beyond the silver haze

Is that a part of me

Or something that we made?

[Instrumental Groove - 16 bars; prominent punchy fingerstyle electric bass plays a distinctive syncopated melodic riff; staccato ghost notes and upper-register answers; steady drums, muted guitar and slowly modulating warm polysynth; no vocals]

[A Motif - 8 bars; same melodic identity, subtle vocal doubles]

Every time I look, the colors move

Every little change becomes a clue

Every time I look, the colors move

Every little change becomes a clue

[B Motif - 8 bars; complete recurring response]

So tell me what you see

Beyond the silver haze

Is that a part of me

Or something that we made?

[Instrumental Development - 16 bars; full bass-led dance groove continues; bass introduces small octave variations; clipped rhythm guitar answers; Juno-like synthesizer filter opens into a smooth wobbling motif, then recedes; no vocals]

[Reflective Turn - 8 bars; close and conversational; drums and bass continue softly]

I watched a face inside the glass

And called it something I could keep

But when you moved the light an inch

The colors opened underneath

[A Motif - 8 bars; familiar vocal melody, final line changes]

Every time I look, the colors move

Every little change becomes a clue

Every time I look, the colors move

I can show the shape, not swear it's true

[B Motif - 8 bars; warmer harmonies, subtly changed ending]

So tell me what you see

Beyond the silver haze

Is that a part of me

Or something we can change?

[Outro - 16 bars; long bass-forward groove, short airy vocal fragments]

Turn the light

Let it move

Another angle

Another view

Turn the light

Let it move

Another angle

Another view

[Final instrumental vamp; original melodic bass riff returns unchanged, warm synth chords slowly recede, muted guitar and drums resolve together; clean musical ending]

I emailed [security@openai.com](mailto:security@openai.com) in September to report account abuse. Still no response.

A couple of days ago, I sent another email to the same address documenting how another instance of abuse happened. Nothing back on that one either.

Honestly, I am done wasting my time. It feels like I’m talking to a wall. If you don’t give a shit, why the fuck should I.

r/OpenAI! I am starting a channel where I'd post AI tutorials and tests. I came up with 3 names:

- theAIbench

- theAIroom

- theAIdesk

They're all on the theme of sitting and watching AI tutorials, and I'm confused which of them sounds the best, or if they even sound good. What's your opinion? Or do you have any other name ideas?

I really appreciate any help you can provide. 😄

I'm a $20 plan user and was just offered the fast mode, which increases plan usage. In my work I'd be glad to sacrifice some time and speed for the same result if it can be achieved with less tokens. That way could optimize my work based on tokens, which are pretty scarse for the time being.