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Google “We have no moat, and neither does OpenAI”

semianalysis.com

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Re: Google “We have no moat, and neither does OpenAI”

#411

Post by netdur »

contravert wrote: post #360
hospitalJail wrote: post #102

Earlier quoted context omitted.

>Midjourney is more popular (from what I'm seeing) than Stable Diffusion at the moment because it's better at the moment. Midjourney is closed-source. Midjourney is easier, its not better. The low barrier to entry has it popular, but it isnt as realistic, doesnt follow the prompt as well, and has almost no customization. SD is the holy grail of AI art, if you can afford a computer or server to run SD + have the abili…

I just want to add my $0.02 currently working at a games studio that is integrating AI generated art into our art pipelines. Midjourney definitely generates really high quality art based on simple prompts, but the inability to really customize the output basically kills its utility. We heavily use Stable Diffusion with specific models and ControlNet to get customizable and consistent results. Our artists also need to…

use https://github.com/deep-floyd/IF, it uses LLM to generate exact art you need.

Re: Google “We have no moat, and neither does OpenAI”

#412

Post by eulers_secret »

sbrother wrote: post #394
eulers_secret wrote: post #331

Earlier quoted context omitted.

If you use the web interface (oobabooga), then training a LoRa is as easy as clicking the "training" tab, keeping all the defaults, and giving it a flat text file of your data. The defaults are sane enough to not begin undermining any instruction tuning too much. Takes 3-5 hours on a 3080 for 7B, 4bit model (and ~1KWh). So far I've trained 3: 2 on the entire text of ASOIAF (converted from e-books) and 1 on the Harry…

Will it distribute training across multiple GFX cards? I have a 4x 2080Ti box I would love to be able to use for this sort of thing.

Not for training with the webui: https://github.com/oobabooga/text-generation-webui/issues/11...

It does seem to work using alpca-lora directly, though.

Re: Google “We have no moat, and neither does OpenAI”

#413

Post by randomdata »

jononor wrote: post #387
randomdata wrote: post #369

Earlier quoted context omitted.

> Linux won in servers and supercomputing, but not in end user computing. It seems just about every computing appliance in my home runs Linux. Then you have Android, ChromeOS, etc. which are also quite popular with end users, the first one especially. It may not have won, but I think it is safe to say that it is dominating.

Appliances are not end user computing, but embedded computing - the OS is incidental and under full control of the manufacturer. Some might argue that even mobile phones are not sufficiently under the control of end users to qualify.

> Appliances are not end user computing

They are when the end user is using them. Think things like TVs or even thermostats.

> the OS is incidental and under full control of the manufacturer.

For all intents and purposes Linux has won where those conditions aren’t met.

Re: Google “We have no moat, and neither does OpenAI”

#414

Post by picometer »

“Some of the most interesting questions about CAS [Complex Adaptive Systems] have to do with their relations to one another. We know that such systems have a tendency to spawn others. Thus biological evolution gave rise to thinking, including human thought, and to mammalian immune systems; human thought gave rise to computer-based CAS; and so on.”

- Murray Gell Mann, “Complex Adaptive Systems”

Re: Google “We have no moat, and neither does OpenAI”

#415

Post by yayr »

airstrike wrote: post #400
narrator wrote: post #396

Earlier quoted context omitted.

I think the problem with AI being everywhere and ubiquitous is that AI is the first technology in a very long time that requires non-trivial compute power. That compute power costs money. This is why you only get a limited number of messages every few hours from GPT4. It simply costs too much to be a ubiquitous technology. For example, the biggest LLama model only runs on an A100 that costs about $15,000 on ebay. The…

Time for a dedicated "AI box" at home with hotswapping compute boards? Maybe put it inside a humanoid or animal-like robot with TTS capabilities? Sign me up for that kickstarter! EDIT: based on some quick googling (should I have asked ChatGPT instead?), Nvidia sells the Jetson Xavier Nx dev kit for ~$610 https://www.electromaker.io/shop/product/nvidia-jetson-xavie... Just need the robot toy dog enclosure (See https:/…

each billion parameters using 16 bit floats requires around 2 GB of GPU or TPU RAM. ChatGPT is expected to have around 1000 billion. Good open source LLMs have around 7-20 billion currently. Consumer GPUs currently max out at 24 GB. You can now quantize the model to e.g. 4 bits instead of 32 per parameter and do other compressions, but still there is quite a limit what you can do with 24 GB of RAM. The Apple unified memory approach may be a path forward to increase that... so one box gives you access to the small models, for a GPT4 like model you'd need (for inference and if you had the model and tools) probably 100 of those 4090s or 25 of H100 with 96 GBs I guess to fit in 2 TB of model data.

Re: Google “We have no moat, and neither does OpenAI”

#416

Post by hintymad »

> They are doing things with $100 and 13B params

Not that I disagree with the general belief that OSS community is catching up, but this specific data point is not as impactful as it sounds. Llama cannot be used for commercial purposes, and that $100 was spent on ChatGPT, which means we still depended on proprietary information of OpenAI.

It looks to me that the OSS community needs a solid foundation model and a really comprehensive and huge dataset. Both require continuous heavy investment.

Re: Google “We have no moat, and neither does OpenAI”

#417

Post by not2b »

kelipso wrote: post #397
dahwolf wrote: post #389

The current paradigm is that AI is a destination. A product you go to and interact with. That's not at all how the masses are going to interact with AI in the near future. It's going to be seamlessly integrated into every-day software. In Office/Google docs, at the operating system level (Android), in your graphics editor (Adobe), on major web platforms: search, image search, Youtube, the like. Since Google and other…

To be fair, the open source model has been what's been working for the last few decades. The concern with LLMs was that open source (and academia) couldn't do what the big companies are doing because they couldn't get access to enough computing resources. The article is arguing (and I guess open source ML groups are showing) you don't need those computing resources to pave the way. It's still an open question whether…

But none of the "open source" AI models are open source in the classic sense. They are free but they aren't the source code; they are closer to a freely distributable compiled binary where the compiler and the original input hasn't been released. A true open source AI model would need to specify the training data and the code to go from the training data to the model. Certainly it would be very expensive for someone else to take this information, build the model again, and verify that the same result is obtained, and maybe we don't really need that. But if we don't have it, then I think we need some other term than "open source" to describe these things. You can get it, you can share it, but you don't know what's in it.

Re: Google “We have no moat, and neither does OpenAI”

#418

Post by vosper »

dahwolf wrote: post #389

The current paradigm is that AI is a destination. A product you go to and interact with. That's not at all how the masses are going to interact with AI in the near future. It's going to be seamlessly integrated into every-day software. In Office/Google docs, at the operating system level (Android), in your graphics editor (Adobe), on major web platforms: search, image search, Youtube, the like. Since Google and other…

> OpenAI faces the existential risk, not Google.

Yes, but the quickest way for anyone to get themselves to state-of-the-art is to buy OpenAI. Their existential risk is whether they continue to be (semi)independent, not whether they shutdown or not. Presumably Microsoft is the obvious acquirer, but there must be a bunch of others who could also be in the running.

Re: Google “We have no moat, and neither does OpenAI”

#419

Post by titzer »

dahwolf wrote: post #389

The current paradigm is that AI is a destination. A product you go to and interact with. That's not at all how the masses are going to interact with AI in the near future. It's going to be seamlessly integrated into every-day software. In Office/Google docs, at the operating system level (Android), in your graphics editor (Adobe), on major web platforms: search, image search, Youtube, the like. Since Google and other…

> It's going to be seamlessly integrated into every-day software.

I...kinda don't want this? UIs have already changed in so many different fits, starts, waves, and cycles. I used to have skills. But I have no skills now. Nothing works like it used to. Yeah they were tricky to use but I cannot imagine that a murky AI interface is going to be any easier to use, and certainly impossible to master.

Even if it is easier to use, I am not sure I want that either. I don't know where the buttons are. I don't know what I can do and what I can't. And it won't stay the same, dodging my feckless attempts to commit to memory how it works and get better at it...?

Re: Google “We have no moat, and neither does OpenAI”

#420

Post by Animats »

narrator wrote: post #396
dahwolf wrote: post #389

The current paradigm is that AI is a destination. A product you go to and interact with. That's not at all how the masses are going to interact with AI in the near future. It's going to be seamlessly integrated into every-day software. In Office/Google docs, at the operating system level (Android), in your graphics editor (Adobe), on major web platforms: search, image search, Youtube, the like. Since Google and other…

I think the problem with AI being everywhere and ubiquitous is that AI is the first technology in a very long time that requires non-trivial compute power. That compute power costs money. This is why you only get a limited number of messages every few hours from GPT4. It simply costs too much to be a ubiquitous technology. For example, the biggest LLama model only runs on an A100 that costs about $15,000 on ebay. The…

It's a win for Google that LLMs are getting cheaper to run. OpenAI's service is too expensive to be ad-funded. Google needs a technology that's cheaper to provide to maintain their ad-supported business model.
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