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OpenAI declares 'code red' as Google catches up in AI race

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Re: OpenAI declares 'code red' as Google catches up in AI race

#941

Post by deaux »

curioussquirrel wrote: post #924
deaux wrote: post #831

Earlier quoted context omitted.

This goes way back. Even back in the 1.5 days it was the best multilingual model, when HN still treated it as entirely uncompetitive all-around. Just because, exactly as you're saying, it's not a core concern of people here. The two fields Gemini models have been number one at for years now are A. multilinguality B. image understanding. At no point since the release of Gemini 1.5 Pro way back has any Anthropic or Ope…

In our previous tests, when it was 1.5 Pro against GPT 4o and Claude Sonnet 3.7, Gemini wasn't winning in the multilingual race, but it was definitely competitive. 2.5 and 3.0 seems to be big leaps from the 1.5 days. That said, it also depends on the testing methodology; we tested a bunch of use cases mostly to test core linguistic proficiency. Not as much complex tasks in language or cultural knowledge.

Which languages, how popular, how many? The biggest difference has been for low-resource or far-from-English languages. Thai, Korean, Vietnamese, and so on. For something like German or French all of them were of course good enough that general intelligence and other factors overruled any language differences. I didn't take screenshots, maybe archive.org has them, but during the entire period of that generation of models on the LMArena leaderboard there was this large gap between 1.5 Pro rankings on such languages vs on English, which was backed up by our experience including feedback from groups of native speakers.

Re: OpenAI declares 'code red' as Google catches up in AI race

#942

Post by shridharxp »

fragmede wrote: post #677
shridharxp wrote: post #658

Earlier quoted context omitted.

Few months ago, the founder was talking about "AGI" and ridiculous universal basic compute. At this point, I don't even know whom to believe. My first hand experience tells ChatGPT and even ClaudeCode are no where near the expertise they are touted to be. Yet, the marketing by these companies is so immense that you get washed away, you don't know who are agents and who are putting their true opinions.

> My first hand experience tells ChatGPT and even ClaudeCode are no where near the expertise they are touted to be Not doubting you, but where specifically have the latest models fallen short for you?

ClaudeCode:

- Making functions async without need; it doesn't know the difference between the two or in which scenarios to use them.

- Consistently fails to make changes to the frontend if a project grows above 5000 LOC or a file goes near 1000 LOC.

- The worst part is it lies after making changes.

ChatGPT:

- Fails to implement mid-complex functionality such as scrolling to the bottom when new logs are coming in and not scrolling when the user is checking historical logs.

These models are good at mainstream tasks, the snippets of which you find a lot in repositories. Try to do something off-beat such as algorithmic trading; they fail spectacularly.

Re: OpenAI declares 'code red' as Google catches up in AI race

#943

Post by rprend »

array_key_first wrote: post #939
rprend wrote: post #932

Earlier quoted context omitted.

Which brands lose money on ads? Why are they still in business? > consumers have a lot of money that they dole out. More ads wont increase the cut of money Consumer spending is not a fixed pie chart or a zero sum game. US consumer spending has grown from $14 to $19 trillion since 2020. $5 trillion in new pie!! Your model of ads is: “I, a consumer, have decided to buy a bluetooth speaker, and the ads push and pull me…

> US consumer spending has grown from $14 to $19 trillion since 2020. $5 trillion in new pie!! All that's telling you is the economy is not doing nearly as well as some of our metrics would have you believe. Real wages are about the same as before, probably lower. Consumers are buying the same amount of stuff - no value has been created. Rather, the dollar has been devalued, much more than we're willing to let on. Th…

Look it's fine to have contrarian opinions that left is right, everything is backwards, whatever. But when it comes to business and money, these things are quantitative and falsifiable. If you have a better understanding than the idiots in charge, then go be rich! If you have a better model for real value, you'll outcompete them. Until you do that, you are playing word games, ones which have somehow deluded you into believing that the most profitable company on earth is not valuable.

Re: OpenAI declares 'code red' as Google catches up in AI race

#944

Post by ckrapu »

SR2Z wrote: post #911
qdotme wrote: post #891

Earlier quoted context omitted.

No, I just realize these for what they are - reasonable projects at the exploitation (rather than exploration) stage of any industry. I’d say I have an average CV in the EECS world, but also relatively humble perspective of what is and isn’t bleeding edge. And as the industry expands, the volume „inside” the bleeding edge is exploitation, while the surface is the exploration. Waymo? Maybe; but that’s acquisition and…

> No, I just realize these for what they are - reasonable projects at the exploitation (rather than exploration) stage of any industry. I get that bashing on Google is fun, but TensorFlow was the FIRST modern end-user ML library. JAX, an optimizing backend for it, is in its own league even today. The damn thing is almost ten years old already! Waymo is literally the only truly publicly available robotaxi company. I d…

I think Theano takes the crown as first modern end-user library for autodiff and tensor operations.

Re: OpenAI declares 'code red' as Google catches up in AI race

#945

Post by littlestymaar »

adgjlsfhk1 wrote: post #934
littlestymaar wrote: post #933

Earlier quoted context omitted.

Please tell me how being the third and 7th biggest companies in the world is “not even 1/10 enough” … “Enough” for what exactly?

It's not enough to pay for the size of the rollout the AI companies are doing. The difference between Google and OpenAI is that Google's add revenue comes at basically 0 cost. Google serves multiple adds for every search, and actually completing the search costs a tiny fractions of a cent (the majority of which is the cost to figure out what add to display). OpenAI is in a totally different boat. They get a similar n…

> OpenAI is in a totally different boat. They get a similar number of adds per search, but each query will cost them far more than a simple web search. A paragraph or a single image costs OpenAI over 1c to generate

First of all, your numbers a off by an order of magnitude at least: even GPT-5 can generate 1000 tokens for 1c, which is much more than a paragraph.

And then again that's why my entire argument revolved around the fact that OpenAI would need to stop aiming for the technological edge. Deepseek generates 25k tokens for a cent and it's still a gigantic model. I'd you use a model comparable in size to gpt-oss-120b you can even increase that up to 100-200k tokens per cent (going from 32GB worth of active parameters, 32B at q8 for Deepseek, to 4GB, 8B using MXFP4 for gpt-oss-120b). That would mean being able to serve more than 100 answers per cent spent on inference.

If they can serve .1c worth of ads per request, that's 90% gross margin for you.

Re: OpenAI declares 'code red' as Google catches up in AI race

#946

Post by opwdym »

tim333 wrote: post #77
techblueberry wrote: post #47

Earlier quoted context omitted.

Far be it from me to backseat drive for Sam Altman, but is the problem really that the core product needs improvement, or that it needs a better ecosystem? I can't imagine people are choosing they're chatbots based on providing the perfect answers, it's what you can do with it. I would assume google has the advantage because it's built into a tool people already use every day, not because it's nominally "better" at g…

ChatGPT's thing always seems to have been to be the best LLM, hence the most users without much advertising and the most investment money to support their dominance. If they drop to second or third best it may cause them problems because they rely on investor money to pay the rather large bills. Currently they are not #1 in any of the categories on LLM arena, and even on user numbers where they have dominated, Google…

800M for chatgpt is WAU

Re: OpenAI declares 'code red' as Google catches up in AI race

#947

Post by SR2Z »

qdotme wrote: post #923
SR2Z wrote: post #911

Earlier quoted context omitted.

> No, I just realize these for what they are - reasonable projects at the exploitation (rather than exploration) stage of any industry. I get that bashing on Google is fun, but TensorFlow was the FIRST modern end-user ML library. JAX, an optimizing backend for it, is in its own league even today. The damn thing is almost ten years old already! Waymo is literally the only truly publicly available robotaxi company. I d…

True, for some definition of first and some definition of modern. I’d say it builds extremely heavily on the works inside XTX (and prior to that, XFactor etc) on general purpose linear algebra tooling, and still doesn’t change the fact that it remains shallow, even including JAX. Google TPUs change this equation a bit, as they are starting to come to fruition; but for them to reach the level of depth of NVDA, or even…

You think that Tesla, which has not accepted liability for a single driverless ride, has "gotten there?" I'm not even going to look up how many Waymo does in a month, I'm sure it's in the millions now.

Come on, man.

> Google's TPUs change this equation a bit

Google has been using TPUs to serve billions of customers for a decade. They were doing it at that scale before anyone else. They use them for training, too. I don't know why you say they don't own the stack "from silicon to apps" because THEY DO. Their kernels on their silicon to serve their apps. Their supply chain starts at TSMC or some third-party fab, exactly like NVIDIA.

Google's technical moat is a hundred miles deep, regardless of how dysfunctional it might look from the outside.

Re: OpenAI declares 'code red' as Google catches up in AI race

#948

Post by SR2Z »

ckrapu wrote: post #944
SR2Z wrote: post #911

Earlier quoted context omitted.

> No, I just realize these for what they are - reasonable projects at the exploitation (rather than exploration) stage of any industry. I get that bashing on Google is fun, but TensorFlow was the FIRST modern end-user ML library. JAX, an optimizing backend for it, is in its own league even today. The damn thing is almost ten years old already! Waymo is literally the only truly publicly available robotaxi company. I d…

I think Theano takes the crown as first modern end-user library for autodiff and tensor operations.

Ok, that's fair.

Re: OpenAI declares 'code red' as Google catches up in AI race

#949

Post by dumah »

Miraste wrote: post #842
matwood wrote: post #708

Earlier quoted context omitted.

Are you saying that Google, Meta, Amazon, etc... can't do software? It's the bread and butter of these companies. The CUDA moat is important to hold off the likes of AMD, but hardware like TPUs for internal use or other big software makers is not a big hurdle. Of course Huang will lean on the software being key because he sees the hardware competition catching up.

Meta makes websites and apps. Historically, they haven't succeeded at lower-level development. A somewhat recent example was when they tried to make a custom OS for their VR headsets, completely failed, and had to continue using Android.

You're generalizing a failure at delivering one consumer solution and ignoring the successful infrastructure research and development that occurs behind the scenes.

Meta builds hardware from chip to cluster to datacenter scale, and drives research into simulation at every scale, all the way to CFD simulation of datacenter thermal management.

Re: OpenAI declares 'code red' as Google catches up in AI race

#950

Post by dumah »

qdotme wrote: post #797
matwood wrote: post #708

Earlier quoted context omitted.

Are you saying that Google, Meta, Amazon, etc... can't do software? It's the bread and butter of these companies. The CUDA moat is important to hold off the likes of AMD, but hardware like TPUs for internal use or other big software makers is not a big hurdle. Of course Huang will lean on the software being key because he sees the hardware competition catching up.

Essentially, yes, they haven’t done deep software. Netflix probably comes closest amongst FAANG. Google, Meta, Amazon do “shallow and broad” software. They are quite fast at capturing new markets swiftly, they frequently repackage OpenSource core and add the large amount of business logic to make it work, but essentially follow the market cycles - they hire and layoff on a few year cycle, and the people who work ther…

These companies innovate in all of those areas and direct those resources towards building hyper-scale custom infrastructure, including CPU, TPU, GPU, and custom networking hardware for the largest cloud systems, and conduct research and development on new compilers and operating system components to exploit them.

They're building it for themselves and employ world-class experts across the entire stack.

How can NVIDIA develop "more integrated" solutions when they are primarily building for these companies, as well as many others?

Examples of these companies doing things you mention as being somehow unique to or characteristic of NVIDIA:

Complex kernel drivers or modules:

- AWS: Nitro, ENA/EFA, Firecracker, NKI, bottlerocket

- Google: gasket/apex, gve, binder

- Meta: Katran, bpfilter, cgroup2, oomd, btrfs

Hardware simulators:

- AWS: Neuron, Annapurna builds simulations for nitro, graviton, inferentia and validates aws instances built for EDA services

- Google: Goldfish, Ranchu, Cuttlefish

- Meta: Arcadia, MTIA, CFD for thermal management

Optimizing Compilers:

- Amazon: NNVM, Neo-AI

- Google: MLIR, XLA, IREE

- Meta: Glow, Triton, LLM Compiler

Acceleration Libraries:

- Amazon: NeuronX, aws-ofi-nccl

- Google: Jax, TF

- Meta: FBGEMM, QNNPACK

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