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AWS Aligns With Hugging Face for GenerativeAI

The Six Five team discusses AWS’s alignment with Hugging Face for GenerativeAI.

If you are interested in watching the full episode you can check it out here.

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Transcript:

Daniel Newman: It’s been a big topic though, large language models, Pat. Of course we’ve seen what’s happened over the last few weeks with Microsoft and of course with Google and Bard, and AWS being the third to come up with a story here. And so, AWS isn’t a browser company. They don’t have a search tool in the traditional way that you think about it. But one of the biggest opportunities, and you and I think talked about this on the last couple of podcasts, is large language models aren’t going to be just about the open internet. I look at what we’re seeing right now as a bit of a parlor trick. It’s going to be a consistent set of information that every company has access to through the browser. Bing is optimizing the way you ask a question to a search engine, but Google, if you type the search in using traditional search methods will still find you pretty good data.

But we’re starting to see what can happen. I think the big inflection point is we’re starting to have conversations with our AI or with the machine instead of searching in a very specific way that’s machine friendly. But the future of generative AI I think has a lot more to do with the way customers and businesses can create and optimize workflows or processes or built-in automations using big sets of data that live inside of systems of record and ERP and inside of business CRM, transaction data, employee data through an HCM system, or a supply chain management system that’s talking about your supply chain operations.

And right now, the ability to be able to train those models and use those models in the cloud is going to be something enterprises are looking to. So yes, open AI provides a large language model, that’s where we get ChatGPT. Of course, Google is building their large language model, which is going to be Bard. Amazon is basically saying, “We’re going to partner with Hugging Face,” and this may not be the only thing they do, but Hugging Face to basically democratize and make available it’s open source large language model for AWS users. So that could be through SageMaker, that could be done through container services, Pat. And so, there’s a few different ways that this is going to be able to be done. I think this is, A, really important for Amazon to have a claim to stake in terms of how they’re planning to participate in the large language model space and towards generative AI.

I think that this has got to be competitive. And of course, like I said, is Amazon has tons of data but needed a partner to help build and make it openly available, an LLM that could be utilized by all of its AWS user base. And so that’s what I think is going on here. I think it’s going to be more utilized and important for what I would call enterprise business applications, customer interactions, conversations, and chatbots, but not the kind that we’re all getting really accustomed to with ChatGPT where it’s using open internet data. This is all about that data that sits below the corporation in the company’s databases, in the systems of revenue, like I mentioned.

So interesting, like I said, interesting because I think it’s timely. I think everybody’s pulling forward their announcements. I have a feeling that Microsoft reconfigured the pace of generative AI by coming out and announcing the ChatGPT 3.5, the one that you and I went to the event, and that pushed for Bard, and now a AWS feels a bit obligatory to have an answer. Having said that, building development tools for these enterprise workloads to use large language models is pretty interesting and pretty exciting. And of course it should be beneficial for the company’s tools including SageMaker, but also including Inferentia and Trainium.

Patrick Moorhead: Yeah, so first off, this announcement was an expanded relationship. AWS had a relationship with Hugging Face. I don’t think it was reactive. What they did do is they had to talk about them doubling down. The other thing I want to point out to our listeners is that AWS hosts more machine learning workloads than anybody else out there. It’s funny, while most of the focus was on Google versus Microsoft on the consumer side, very few people were talking about the Azure versus AWS versus GCP. As Daniel said, this is where a lot of the heat is. And, oh by the way, a lot of these startups who are out there who want to take advantage of generative AI, AWS will be a place that they will be looking.

The other thing, it’s important like Microsoft and similar to Google, AWS has a ton of examples with AI. I mean, all of Alexa that serves all of its devices are based on NLPs and low latency operations that they run off their own silicon, called Inferentia. But what the company’s doing is they are integrating Hugging Face into all of its AI workflow, specifically SageMaker. That’s a key one right there. I’m super interested to see what they do with Amazon CodeWhisperer, which is essentially AI creating code. Azure talked a lot about that as well. So net net, a ton of excitement. You have Microsoft aligning with OpenAI, you have Google aligning with Anthropic… I need to know a little bit more about Anthropic… and then AWS aligning with Hugging Face. So Dan, which company has yet to even talk about generative AI or align with a major partner here?

Daniel Newman: Well, there’s a few, but I mean, I think if you-

Patrick Moorhead: Apple has not.

Daniel Newman: Okay, well, I was actually going to say IBM’s using different words. Oracle really hasn’t said anything yet despite the fact they have a number. You’re right, and obviously that’s the freaking obvious one. I should be fired.

Patrick Moorhead: No, no, but that was just the one on my mind and the one that I put in my tweet. I was trying to lead you there.

Daniel Newman: We used to be closer. It appears we’ve grown apart.

Patrick Moorhead: Yeah. It’s funny, on IBM I did look at the words that they used, and they didn’t use the words that AWS, Google, and Microsoft used, but I think they did a better job explaining the entire landscape of natural languages. Yeah, so Apple, where the heck is Apple? Who are they going to partner with? A, I don’t think they know how to do it on their own. They’re not good at cloud and doing things in the cloud. They’re very good at device. I think they’ll probably partner with AWS in what they do. You had Intel based, Mac-

Daniel Newman: Wait, hold on, prognostication, Pat, Apple and AWS tie up?

Patrick Moorhead: Yeah, I think AWS and Apple are going to tie up based upon their prior relationship. I don’t think Apple’s going to wake up and get good at the cloud. They’ve sucked at doing stuff in the cloud for years. It’s not a core competency.

Daniel Newman: I think they know how to route all the data through China. I don’t know what you’re talking about.

Patrick Moorhead: Do they? I didn’t know that. I didn’t know that. Can I quote you on that-

Daniel Newman: I don’t know.

Patrick Moorhead: …in one of my Forbes articles?

Daniel Newman: That’s a true story I made up.

Patrick Moorhead: Yeah. Anyways, yeah, I think it’s going to be AWS and Apple. Apple’s going to be writing huge checks to AWS to figure out what they do. As soon as Google and Microsoft start popping out more consumer goodness, Apple’s going to be on the hook for something.

Author Information

Daniel is the CEO of The Futurum Group. Living his life at the intersection of people and technology, Daniel works with the world’s largest technology brands exploring Digital Transformation and how it is influencing the enterprise.

From the leading edge of AI to global technology policy, Daniel makes the connections between business, people and tech that are required for companies to benefit most from their technology investments. Daniel is a top 5 globally ranked industry analyst and his ideas are regularly cited or shared in television appearances by CNBC, Bloomberg, Wall Street Journal and hundreds of other sites around the world.

A 7x Best-Selling Author including his most recent book “Human/Machine.” Daniel is also a Forbes and MarketWatch (Dow Jones) contributor.

An MBA and Former Graduate Adjunct Faculty, Daniel is an Austin Texas transplant after 40 years in Chicago. His speaking takes him around the world each year as he shares his vision of the role technology will play in our future.

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