Is it just me or are all the AI players somehow lining up their announcements to be on the same day?
First the Gemini thing. Now this. (Or vice versa?)
Is there any reason they're doing this?
GPT‑5.3‑Codex‑Spark
301–310 of 415 posts
Re: GPT‑5.3‑Codex‑Spark
#302Is it just me or are all the AI players somehow lining up their announcements to be on the same day? First the Gemini thing. Now this. (Or vice versa?) Is there any reason they're doing this?
I doubt they coordinate it, but my guess it’s an attempt to undercut their competition. When a competitor announces a new model, immediately announcing your own new and improved model reduces the length of time your competitor can claim theirs is the latest and greatest.
Re: GPT‑5.3‑Codex‑Spark
#303Earlier quoted context omitted.
There’s an expected amount of defects per wafer. If a chip has a defect, then it is lost (simplification). A wafer with 100 chips may lose 10 to defects, giving a yield of 90%. The same wafer but with 1000 smaller chips would still have lost only 10 of them, giving 99% yield.
As another comment referenced in this thread states, Cerebras seems to have solved by making their big chip a lot of much smaller cores that can be disposed of if they have errors.
Indeed, the original comment you replied to actually made no sense in this case. But there seemed to be some confusion in the thread, so I tried to clear that up. I hope I’ll get to talk with one of the cerebras engineers one day, that chip is really one of a kind.
Re: GPT‑5.3‑Codex‑Spark
#304Wow, I wish we could post pictures to HN. That chip is HUGE!!!! The WSE-3 is the largest AI chip ever built, measuring 46,255 mm² and containing 4 trillion transistors. It delivers 125 petaflops of AI compute through 900,000 AI-optimized cores — 19× more transistors and 28× more compute than the NVIDIA B200. From https://www.cerebras.ai/chip : https://cdn.sanity.io/images/e4qjo92p/production/78c94c67be9... https://cd…
>Wow, I wish we could post pictures to HN. That chip is HUGE!!!! Using a waffer sized chip doesn't sound great from a cost perspective when compared to using many smaller chips for inference. Yield will be much lower and prices higher. Nevertheless, the actual price might not be very high if Cerebras doesn't apply an Nvidia level tax.
Cerebras addresses this in a blog post: https://www.cerebras.ai/blog/100x-defect-tolerance-how-cereb...
Basically they use very small cores compared to competitors, so faults only affect small areas.
Re: GPT‑5.3‑Codex‑Spark
#305Earlier quoted context omitted.
Designing to tolerate the defects is well trodden territory. You just expect some rate of defects and have a way of disabling failing blocks.
So you shoot for 10% more cores and disable failing cores?
Well, it's more like they have 900,000 cores on a WSE and disable whatever ones that don't work.
Seriously, that's literally just what they do.
Re: GPT‑5.3‑Codex‑Spark
#306Continue to believe that Cerebras is one of the most underrated companies of our time. It's a dinner-plate sized chip. It actually works. It's actually much faster than anything else for real workloads. Amazing
Technically, Cerebras solution is really cool. However, I am skeptical that it will be economically useful for models that are larger in size, as the requirements on the number of racks scales with the the size of the model to fit the weights in SRAM.
Re: GPT‑5.3‑Codex‑Spark
#307Earlier quoted context omitted.
Designing to tolerate the defects is well trodden territory. You just expect some rate of defects and have a way of disabling failing blocks.
So you shoot for 10% more cores and disable failing cores?
More or less, yes. Of course, defects are not evenly distributed, so you get a lot of chips with different grades of brokenness. Normally the more broken chips gets sold off as lower tier products. A six core CPU is probably an eight core with two broken cores.
Though in this case, it seems [1] that Cerebras just has so many small cores they can expect a fairly consistent level of broken cores and route around them
[1]: https://www.cerebras.ai/blog/100x-defect-tolerance-how-cereb...
Re: GPT‑5.3‑Codex‑Spark
#308I've been using Perplexity for small, fast queries almost exclusively for the last year or so. Their Sonar model is Llama running on top of a Cerebras chip, and searches the internet in an incredible speed. Its results are astonishingly good (for a Llama model), although in more niche areas it still makes mistakes, so in those areas I usually double-check its sources or do an extra ddg search myself.
Actually I've never used chat gpt, I went straight to Perplexity after having discovered it. Their free tier is extremely generous (not even requiring an account). Not affiliated.
OP currently doesn't look it will affect that, seems like Open AI touts it for agentic coding only, not as an alternative to chat gpt, although that will probably change.
Re: GPT‑5.3‑Codex‑Spark
#309Wow, I wish we could post pictures to HN. That chip is HUGE!!!! The WSE-3 is the largest AI chip ever built, measuring 46,255 mm² and containing 4 trillion transistors. It delivers 125 petaflops of AI compute through 900,000 AI-optimized cores — 19× more transistors and 28× more compute than the NVIDIA B200. From https://www.cerebras.ai/chip : https://cdn.sanity.io/images/e4qjo92p/production/78c94c67be9... https://cd…
Why is the CEO some shady guy? though https://daloopa.com/blog/analyst-pov/cerebras-ipo-red-flags-...
"AI" always has some sleazy person behind it for some reason
Re: GPT‑5.3‑Codex‑Spark
#310First thoughts using gpt-5.3-codex-spark in Codex CLI: Blazing fast but it definitely has a small model feel. It's tearing up bluey bench (my personal agent speed benchmark), which is a file system benchmark where I have the agent generate transcripts for untitled episodes of a season of bluey, perform a web search to find the episode descriptions, and then match the transcripts against the descriptions to generate f…
Yea it's been butchering relatively easy to moderate tasks for me even with reasoning set to high. I am hoping it's just tuning that needs to be done since they've had to port it to a novel architecture. If instead the model is performing worse due to how much they had to shrink it just so it will fit on Cerebras hardware, then we might be in for a long wait for the next gen of ginormous chips.
> If instead the model is performing worse due to how much they had to shrink it just so it will fit on Cerebras hardware
They really should have just named it "gpt-5.3-codex-mini" (served by Cerebras). It would have made it clear what this model really is.