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

This is a GPT3 moment for speech.

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

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.

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

Results grouped by problem, sorted by solve time (fastest first).

The problems

These problems are very challenging for human contestants. The higher the score, the harder one is to solve. Small models like Luna, Haiku are struggling with problems like 2271H2, which are around 200 points.

These problem are quite new from the September and October contents, so they are unlikely being trained.

Problem 2271G

Problem 2271H2

Problem 2273F

Problem 2261F2

Fastest Model per Problem

Observations

• Sol 6.1 achieved the fastest solve time on 3 out of 4 problems.
• Terra 6.1 Max was fastest on 2271H2, despite being a larger model at max reasoning, so lower TPS.
• On 2273F, Terra 6.1 High was 4m 10s faster than Terra 6.1 Max, but Max produced a better solution that is twice faster and twice less memory.
• On lower reasoning levels, Terra 6.1 refuses to solve problem quickly, if it can solve. This might be an annoyance to some, but might be a great feature since it doesn't waste your time and tokens, just being straight up honest:

Conclusion

Sol 6.1 remains the most intelligent model of the bunch. However, for problems that can be solved with lower models, it would be more costly. Using Sol 6.1 is like having a mathematician writing code: it really determines to prove your code work systematically, that might lead to overengineering. On the other hand, Terra 6.1 might be considered under-engineering. So, I suspect that with Sol creates a slightly overengineered plan and Terra implements slightly lazy, they could balance out their weaknesses.

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 run Codex workers on my own Apple Silicon Mac, signed in with a ChatGPT plan, and the hard part of leaving them alone was never the work. It was the morning: a quiet screen and no idea what actually finished.

What I've settled on so far:

1. Done is something I can open. A code task counts when I see the real test output (one run: 6 tests, OK, exit 0, 55 seconds). A research task counts when there's a saved file I can read, not a message saying it's done.

2. A third state between done and failed. Someone in another thread called it unverified, and it stuck. If a check timed out or got cut off, it lands in front of me as unverified instead of quietly retrying.

3. Small tasks, each with its own check. A bad turn costs one task, not the whole night.

4. The boring limits are the real ones. The computer has to stay on, and every task counts toward my ChatGPT plan's limits, so a loop that keeps retrying overnight is spending plan, not just time.

The line I keep coming back to: silence is not a status.

Honest limits: one Mac, a handful of runs, not a study.

The part I haven't solved: after a restart or a crash, telling a task that finished from one that was cut off halfway. Logs tell me what started, not what ended.

What do you actually let an agent run overnight, and how do you tell finished from cut off the next morning?

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

“Mostly consumer” bots, inside 6 of the biggest financial institutions. Executing transactions. taking steps beyond what human users explicitly asked….mostly consumer.

…Tyler durden couldn’t have set this one up any better.

https://www.americanbanker.com/news/banks-are-blocking-external-ai-agents-is-this-sustainable

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

Hi everyone,

I’m having a strange issue with the ChatGPT desktop app on my iMac. The Chat/Work toggle is completely missing.

The top-left menu lets me choose between ChatGPT and Codex, but selecting ChatGPT only gives me the “What should we build?” screen shown in the screenshot. There’s no option to start a normal Chat conversation.

Normal chats created in the app on another device still work on the iMac. I just can’t start a new normal chat here.

What makes this confusing:

• Everything works correctly on my laptop.
• Both Macs run version 26.1021.31345.
• I’ve tried multiple downloads.
• I even copied the exact installer file from the working laptop to the iMac and installed it there. The problem stayed.
• I tried changing the iMac app’s language to German to match the laptop, then fully quitting and reopening it. That didn’t help either.
• The update checker says the app is up to date.

Has anyone else experienced this, particularly on macOS? Did you find a fix for the missing Chat/Work toggle? Am I just missing something?

Screenshot attached - help appreciated.

Hey, my computed use hasn't been available to be on my laptop for the past week. Has anyone been experiencing this? Did openai pass a weird rule for plus users?