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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”

#501

Post by jldugger »

TeMPOraL wrote: post #409
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…

Honestly, I can't see Google failing here. Like other tech giants, they're sitting on a ridiculously large war chest. Worst case, they can wait for the space to settle a bit and spend a few billion to buy the market leader. If AI really is an existential threat to their business prospects, spending their reserves on this is a no-brainer.

> Honestly, I can't see Google failing here. Like other tech giants, they're sitting on a ridiculously large war chest. Worst case, they can wait for the space to settle a bit and spend a few billion to buy the market leader.

It seems incredibly likely that the FTC will block that. New leadership seems to be of the opinion that consumer harm is the wrong standard. Buying the competition with profits from a search monopoly leaves all parties impoverished.

Anyways, I don't think the risk is failure, but of non-success. The article claims meta won but it seems like nvidia is the winner: everyone uses their chipsets for training, fine tuning and inference. And the more entrants and niche applications show up the more demand there is for their product. TPUs theoretically play into this, but the "leak" doesn't mention them at all.

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

#502

Post by bburnett44 »

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…

The problem is that the llms are better at search (for an open ended question) than Google is and that’s where most of googles revenue comes from. So it actually gives a new company like openai the opportunity to change consumers destinations from google

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

#503

Post by Izkata »

amelius wrote: post #430
titzer wrote: post #419

Earlier quoted context omitted.

> 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 t…

An AI interface in Office brings back memories of Clippy.

Now imagine Clippy on a car touchscreen.

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

#504

Post by neilk »

baryphonic wrote: post #447
unicornmama wrote: post #439

Earlier quoted context omitted.

Google makes almost all its money from search. These platforms are all there to reinforce its search monopoly. ChatGPT has obsoleted search. ChatGPT will do to Google search what the Internet did to public libraries - make them mostly irrelevant.

How has ChatGPT obsoleted search, when hallucination and the token limits are major problems? It's (sort of) obviated search for certain kinds of queries engineers make, but not normies. I say sort of, because IMO it's pretty bad at spitting out accurate (or even syntactically correct) code for any nontrivial problem. I have to give it lots of corrections, and often it will just invent new code that also is broken in…

Let's consider what Google did to the previous paradigm: libraries and books.

Books had editors and were expensive to publish, which imparted some automatic credibility. You might even have involved a librarian or other expert in your search. So a lot of the credibility problem was solved for you, up-front, once you got the information source.

Google changed the game. It gave you results instantly, from sources that it guessed looked reliable. But you still had to ascertain credibility yourself. And you might even look at two or three pages on the same topic, quickly.

Google has been mostly defeated now and often none of the links it suggests are any good. That trade-off seems to be done.

Here comes LLMs. Now it's transferring even more of the work of assessing credibility to the end user. But the benefit is that you can get very tailored answers to your exact query; it's basically writing a web page just for you in real time.

I think the applications that win in this new era will have to make that part of their business model. In science fiction, AIs were infallible oracles. In the real world it looks like they'll be tireless research assistants with an incredible breadth of book-learning to start from but little understanding of the real world. So you'll have a conversation as you both converge on the answer.

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

#505

Post by tyree731 »

deegles wrote: post #499
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…

I was in Japan recently and they sell these pocket size translator devices with a microphone, camera and screen. You can speak to it or take pictures and it will translate on the fly. Maybe $100 usd range for a nice one. It's only a matter of time before someone makes a similar device with a decent LLM on it, and premium ones will have more memory/cpu power.

I think we as humans have a tendency to extrapolate from our present position to a position we can imagine that we’d like, even if there isn’t a foreseeable path from here to there. I believe this may end up being one of those cases.

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

#506

Post by se4u »

eulers_secret wrote: post #331
lysecret wrote: post #144

Fantastic article if you are quick to just go to the comments like I usually do, don't. Read it. One of my favorites: LoRA works by representing model updates as low-rank factorizations, which reduces the size of the update matrices by a factor of up to several thousand. This allows model fine-tuning at a fraction of the cost and time. Being able to personalize a language model in a few hours on consumer hardware is…

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…

I am surprised that people aren't using google colab pro/pro+ in this context. You basically get access to multiple A100 for $10/month and with some simple javascript tricks, you can get a session to last for 24hrs at least.

Pro+ is more expensive at $50/mo but it allows for more simplified background execution. if you are only just getting started and don't expect to be training for multiple months, then colab or other cloud-notebook providers are really great to start.

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

#507

Post by bbor »

seydor wrote: post #156

Not only they have no moat, Open source models are uncensored and this is huge. Censorship is not just political , it cripples the product to basically an infantile stage and precludes so many applications. For once, it is a liability But this article doesn't state the very obvious: When will google (the inventor of Transformer, and "rightful" godfather of modern LLMs) , release a full open source, tinkerable model b…

My very naive opinion is that the best way to predict the big-picture actions of Google is a simple question: WWIitND - What Would IBM in the Nineties Do?

In more direct terms, their sole, laser focus seems to be on maintaining short-term shareholder value, and I really don't trust the typical hedge fund manager to approve of any risky OSS moves for a project/tech that they're surely paying a LOT of attention to.

Giving away transformer tech made Google look like "where the smartest people on the planet work", giving away full LLM models now would (IMO) make them look like arrogant and not... well, cutthroat enough. At least this is my take in a world where financial bigwigs don't know or care about OSS at all; hopefully not the case forever!

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

#508

Post by heliophobicdude »

No moat? Where's the creativity? Google has the ability to create lock-in for users and lock-out for competitors by integrating their proprietary, existing products with natural language querying and reasoning. That's their advantage. Academics and "open"-source models making it cheaper and more efficient to inference?? That's a blessing!

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

#509

Post by sroussey »

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…

Or you can quantize the model and run it on your laptop.

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

#510

Post by rektide »

The Simon Willison coverage is great. Simon is cited in the "why we should have seen it coming" section, for his Stable Diffusion Moment piece. He nicely covers the key points of this paper:

> The premise of the paper is that while OpenAI and Google continue to race to build the most powerful language models, their efforts are rapidly being eclipsed by the work happening in the open source community.

Not to dilute from this beloved point, but also covers other key notes well too:

> Where things get really interesting is where they talk about “What We Missed”. The author is extremely bullish on LoRA—a technique that allows models to be fine-tuned in just a few hours of consumer hardware, producing improvements that can then be stacked on top of each other

https://simonwillison.net/2023/May/4/no-moat/

Overall I take this as fairly happy news. It's a trend humanity stubbornly keeps trying to resist: open source wins.

It's great the barrier to innovation is so much less than expected, that so much experimentation is possible from atop the existing models.

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