Earlier quoted context omitted.
Thus it always was. I’m old enough to remember when “if AI could beat a grandmaster at chess” was considered the finish line.
Over fitting to the benchmarks since 1996
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Our eighth generation TPUs: two chips for the agentic era
211–220 of 240 posts
Re: Our eighth generation TPUs: two chips for the agentic era
#212Earlier quoted context omitted.
Thus it always was. I’m old enough to remember when “if AI could beat a grandmaster at chess” was considered the finish line.
Well, yeah… turns out that goal wasn’t a good indicator for AGI, so we re-evaluated. That’s changing your hypothesis in the face of evidence, not “moving the goalposts” in the fallacious sense.
What’s the indicator for AGI now? We are so far past the Turing Test it isn’t funny. In fact the models now are too intelligent, you would never think a human would have that much knowledge quickly about a subject you chose at random.
Re: Our eighth generation TPUs: two chips for the agentic era
#213Earlier quoted context omitted.
> as long as humans keep producing new content and innovation Well.. we won't have to as we'll have models to do it for us!
I'm sure you were kidding, but seriously, the fact that AI-produced music pretty much all sounds the same is a good indicator that AI isn't particularly creative.
It’s not about creativity. The incentive to produce drops to zero when an LLM is just going to slurp it up and regurgitate it without some form of compensation (notoriety, money, whatever).
Re: Our eighth generation TPUs: two chips for the agentic era
#214Earlier quoted context omitted.
The benchmarks don’t seem to say that language ability has gotten worse?
That's the thing with benchmarks, without evals and actual hands-on experience they can give you false confidence. Claude now sounds almost clinical, and is unable to speak in different styles as easily. Claude 4+ uses a lot more constructions borrowed from English than Claude 3, especially in Slavic languages where they sound unnatural. And most modern models eventually glitch out in longer texts, spitting a few gar…
Btw samplers do in fact help with this. Random tokens deep in your output context are due to accumulated sampling errors from using shit samplers like top_p and top_k with temperature.
Use a full distribution aware sampler like p-less decoding, top-H, or top-n sigma, and this goes away
Yes the paper for this will be up for review at NeurIPS this year.
Re: Our eighth generation TPUs: two chips for the agentic era
#215Earlier quoted context omitted.
People who say Gemini is bad at long contexts are so wrong. You can put whole 50,000 - 70,000 LOC codebase into Gemini 3.1 Pro context making it 800,000+ tokens, give it detailed task and ask for whole changed files back and it will execute it sometimes in one shot, sometimes in two. E.g depend on whatever stack you work with let you see all the errors at once so it can fix everything on single reply. Yes it will giv…
This! And with AI studio you get a couple of free calls per day (it has gotten less and less). I have had days where I would be able to get 100 USD worth of tokens from AI studio for free. 1m tokens in and great code out.
You can even turn most of the censorship off in the AI studio (but not the hidden top_k of 64 they force in there).
AI studio is where you go if you want an actually good mostly uncensored model. Gemini 3.1 is fully and somehow still quietly coomer approved.
Re: Our eighth generation TPUs: two chips for the agentic era
#216Earlier quoted context omitted.
In what way do we not already have AGI?
in all of them
Peter norvig is smarter than you are: https://www.noemamag.com/artificial-general-intelligence-is-...
Re: Our eighth generation TPUs: two chips for the agentic era
#217I already felt that gemini 3 proved what is possible if you train a model for efficiency. If I had to guess the pro and flash variants are 5x to 10x smaller than opus and gpt-5 class models. They produce drastically lower amount of tokens to solve a problem, but they haven't seem to have put enough effort into refinining their reasoning and execution as they produce broken toolcalls and generally struggle with 'agent…
> If I had to guess the pro and flash variants are 5x to 10x smaller than opus and gpt-5 class models. I really doubt it, especially Pro. If anything I wouldn't be surprised if their hardware lets them run bigger models more cheaply and quickly than the others. Pro is probably smaller than GPT 5.4 and Opus 4.6 (looks like 4.7 decreased in size), but 5x seems way too much. IMO Gemini 3 Pro is the most "intelligent" in…
3/3.1 Pro appears to have knowledge about eccentric topics with no obvious sources that often turns out to be right.
It does hallucinate a lot though, and is the most affected by context rot in multi-turn conversations
Re: Our eighth generation TPUs: two chips for the agentic era
#218> A single TPU 8t superpod now scales to 9,600 chips and two petabytes of shared high bandwidth memory, with double the interchip bandwidth of the previous generation. This architecture delivers 121 ExaFlops of compute and allows the most complex models to leverage a single, massive pool of memory. This seems impressive. I don't know much about the space, so maybe it's not actually that great, but from my POV it look…
it is. itll still not create AGI without some breakthrough in instruction vs data separation of concerns
Does non-artificial intelligence have clean instruction/data separation?
Re: Our eighth generation TPUs: two chips for the agentic era
#219I already felt that gemini 3 proved what is possible if you train a model for efficiency. If I had to guess the pro and flash variants are 5x to 10x smaller than opus and gpt-5 class models. They produce drastically lower amount of tokens to solve a problem, but they haven't seem to have put enough effort into refinining their reasoning and execution as they produce broken toolcalls and generally struggle with 'agent…
> the pro and flash variants are 5x to 10x smaller than opus and gpt-5 class models.
The rumor is that Gemini Pro is the largest model being served today (or at least was prior to Mythos)
Source: some podcast where they were discussing TPU vs Nvidia cluster topologies, and how Google is exploiting their topology to allow this. But I can't remember exactly which podcast, so hopefully someone else will know.
Re: Our eighth generation TPUs: two chips for the agentic era
#220Earlier quoted context omitted.
I've been trying Gemini Pro using their $20-ish Goole One subscription for a couple of months, and I also find it consistently does fewer web searches to verify information than say ChatGPT 5.4 Pro which I have through work. I was planning on comparing them on coding but I didn't get the Gemini VSCode add-in to work so yeah, no dice. The Android and web app is also riddled with bugs, including ones that makes you los…
I don't sweat sources and almost never check them. I usually prefer to manually check information after it's provided, to prevent the model from borking it's context trying to find sources that justify it's already computed output. Almost all the knowledge is already baked into the latent space of the model, so citing sources generally is a backwards process. I see it like going to the doctor and asking them to cite…
Good luck all-in.
But seriously what are you doing that this works? I guess if you are writing pop culture articles this might work.
For anything where the output has consequences I can’t imagine finding success like this.