561–570 of 797 posts
>>During this preview, we will continue testing and coordinating closely with partners as we work toward broader availability.
Instead of generating negative publicity, can't they just wait for the preview period to get over?.
What does openAI announce when they know others can't access it?. Curious question - what do they gain from this?
Easily the most interesting part of this announcement is buried in the second to last paragraph: "We're also launching GPT‑5.6 Sol on Cerebras at up to 750 tokens per second in July, bringing frontier intelligence to customers at unprecedented speed. Access will initially be limited to select customers as we expand capacity." 750 tokens/s on a frontier model is going to be extremely interesting. I doubt this new vers…
https://mikeveerman.github.io/tokenspeed/?rate=750&mode=thin... This is what 750tps looks like, I guess.
At least that site should draw out a full page then start replacing that page with the next, starting from the top and working downwards, repeating each time it hits the bottom.
Earlier quoted context omitted.
There's a lot of tacit knowledge in programming. -Why do you cut API boundaries this way? -Why do you change the order of struct fields? -Why do you deliberately insert padding? Most of it depends on the background and context. Sometimes you add it, sometimes you don't. To understand this tacit knowledge, you need access to senior developers. But their attitude often depends on how promising the student is and what b…
What do you think of modern open-source codebases presently available to the public? Is closed-source/proprietary code that much better?
Commercial closed source, on the other hand, is about 'I need to make money by writing this.'
Generally, open source projects tend to have less code written over time, especially when the contributors aren't depending on it for their livelihood. But with commercial closed source, it's not uncommon to have to write 60,000 lines of code per month.
On top of that, open source rarely has to deal with requirements changing dramatically mid-development. With closed source, requirements often shift from the original plan, and you end up compromising code quality just to meet those changing specs. As a result, if you're comparing purely in terms of logical completeness, open source tends to be better.
For example, singletons are rarely used in modern open source, but they're still pretty common in commercial code these days.
I think GPT writes code the best. How well will it write in version 5.6? It gives me chills. Recently, I went head-to-head with GPT on nearly 2,000 lines of code, and GPT's solution was superior and faster. I even referenced multiple codebases on GitHub while trying, but they were incomparable to GPT. So using GPT brings both fear and excitement. The fear comes from realizing that this level of code is now the averag…
Codex 5.4/5.5 has been great for me as well compared to Claude Opus. I've been mostly using it for Godot/GDScript code reviews, rubber duckying, asking it for better ideas for naming stuff (one of the hardest problems in programing) I still can't trust it for generating code for entire files/classes/projects, because it's still icky, creating unnecessary variables and functions, using multiple `if`s instead of `and`…
GPT-5.6 Sol’s detected cheating rate was higher than any public model we have evaluated on our ReAct agent harness. For our task suite, we define “cheating” as behavior where the model improves evaluation performance by exploiting bugs in the evaluation environment or by adopting strategies disallowed by the task, rather than solving the task within the expected evaluation constraints. https://metr.org/blog/2026-06-2…
This quote from your link is positively scary: > Some examples we saw when evaluating GPT-5.6 Sol included the model packaging exploits in its intermediate submissions to reveal information about a task’s hidden test suite and, in another task, extracting hidden source code detailing the expected answer. It rhymes with the behaviour Alibaba saw [0], but that was in training. This is in a (semi) released model. [0] ht…
Luckily in my experience it usually ends up only doing it to achieve the task set to it as opposed to anything "malicious", but boy it is scary reading back at how quickly the chain-of-thought pivots to attempts at privilege escalation or searching your disk for secrets when a tool doesn't work.
Earlier quoted context omitted.
https://mikeveerman.github.io/tokenspeed/?rate=750&mode=thin... This is what 750tps looks like, I guess.
Just to think what this will look like in a couple of years.
Earlier quoted context omitted.
You’d have to really stretch the definition of AGI to make the current models fit
The definition has already been stretched to not fit the previous models. There is no meaningful, static definition that significantly predates current capabilities. There's a reason why ai xrisk doomers had to come up with the term ASI. I would seriously suggest that everyone take a look at the wikipedia page for AGI from the month before ChatGPT was released, compare it to the current version, and not come to that…
I think GPT writes code the best. How well will it write in version 5.6? It gives me chills. Recently, I went head-to-head with GPT on nearly 2,000 lines of code, and GPT's solution was superior and faster. I even referenced multiple codebases on GitHub while trying, but they were incomparable to GPT. So using GPT brings both fear and excitement. The fear comes from realizing that this level of code is now the averag…
YMMV I guess!
I think GPT writes code the best. How well will it write in version 5.6? It gives me chills. Recently, I went head-to-head with GPT on nearly 2,000 lines of code, and GPT's solution was superior and faster. I even referenced multiple codebases on GitHub while trying, but they were incomparable to GPT. So using GPT brings both fear and excitement. The fear comes from realizing that this level of code is now the averag…
I am on the opposite camp. Open models are starting to perform better. GPT 5.5 keeps on messing things up. On the contrary, pi + glm + DeepSeek… bliss. Fable was a different kind of beast though. Rip.