AI Hustle: News on Open AI, ChatGPT, Midjourney, NVIDIA, Anthropic, Open Source LLMs: Amazon Unveils Public Access to Bedrock Generative AI Service

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Today, Amazon has officially launched Bedrock, which is its centralized service for curated

selection of generative AI models.

This is really, I think, opening the door for AWS customers to incorporate these AI

models into their applications and operations.

First introduced in April.

This is not new.

This is something that Amazon, I think when the whole AI wave started, they made the announcements

and started talking about way back in April.

This is a trend I think we're seeing a lot in the industry.

Even today, I'm seeing announcements out of Google and Microsoft where they're like,

yeah, we're going to do this really cool thing, but it's going to launch in Q1 of next

year.

I think people are kind of, there's a lot of hype around AI.

They're making their announcements now, marking their territory, and then they kind of work

towards those.

That's kind of what Amazon did.

But Bedrock now is live, and it offers a fusion of Amazon's own generative AI models

and those from third party partners, which is all accessible through an API.

The service aims to provide businesses with the tools they need to develop AI agents that

can perform tasks ranging from booking travel to managing inventories, and even things like

processing insurance claims.

Amazon's Bedrock appears at a, I think, really critical time in the adoption of AI.

It's definitely providing a big array of options to brands and developers.

According to the company, the platform is soon going to feature Lama 2, which of course

is an open source large language model developed by Meta.

This is going to be alongside models from other industry players.

I think they have AI 21 labs, Anthropic, Cohere, Stability AI, a lot of these big players.

Amazon purports that Bedrock will be the first, quote, unquote, fully managed generative AI

service to essentially offer both the 13 billion and 70 billion parameter version of Lama 2.

For the uninitiated on this, parameters essentially constitute the part of an AI model that are

learned from historical data, so determining the models, efficacy and problem solving tasks

like text generation, for example.

However, all that being said, I think it's a noteworthy, the Lama 2 isn't a newcomer

to cloud-based generative AI services.

It's also available on Google's Vertex AI, so Google kind of beat Amazon and AWS to

that.

But when we're kind of looking, I think, to the future, looking at the difference between

Bedrock versus Vertex AI, Vertex AI is definitely kind of like Google's platform for this,

but it's something I've talked about a lot in the past.

I wanted to talk a little bit about what I think is perhaps the AWS edge here.

And so I think while comparisons between Bedrock and Google Vertex AI are inevitable, Amazon

makes a really compelling case for its platform's unique advantages.

So Swamy, Cvesse Abramian is the VP of data and AI at AWS, and they kind of pointed out

that Bedrock seamlessly integrates with existing AWS services such as AWS private link.

So this enables a secure connection between Bedrock and a company's virtual private cloud.

And so Swamy was recently saying, quote, over the last year, the proliferation of data access

to scalable compute and advancements in machine learning have led to a surge in interest in

generative AI, sparking new ideas that could transform entire industries and reimagine

how work gets done.

So I think it is worth noting that this supposed edge might be more perception than reality.

The purported advantages kind of depend largely on a customer's current cloud infrastructure,

which is an aspect that I think Swamy does not kind of directly acknowledge.

So when we're kind of looking at this, I think at the end of the day, this really does provide

more tools in the arsenal.

And so what I mean by that is that right now in tandem with Bedrock's announcement, Amazon

has also rolled out its Titan embedding models.

So this first party model focuses on converted text into numerical representations known as

embeddings.

And this is done to enhance search and personal personalization applications.

So the Titan embeddings model boasts support for around 25 languages and it can process

text chunks or even entire documents of up to over 8,000 tokens, which roughly is around

6,000 words.

So this place is at right on par with the latest embedding models from OpenAI.

But you know, sometimes we're seeing bigger ones in other places.

In any case, there's definitely a lot of hurdles to overcome here.

And some of these initial ones, I think they're really focusing on.

So Amazon's Bedrock Services definitely has not been without its challenges.

They've reported in May that the platform struggled in its early days, lacking widespread

access among cloud customers.

And this was six weeks after its debut with an ambitious kind of press release and a,

I think just one testimonial.

But in any case, Amazon appears to be doubling down on its investment in AI, especially following

its recent multi-billion dollar stake in AI startup Anthropoc.

I think originally they gave Anthropoc over a billion dollars and said they'll invest

up to four billion dollars.

And this is kind of through AWS making sure that Anthropoc is on AWS's platform for their

compute.

So I think today's announcement kind of marks Amazon's aggressive play into this growing

market for generative AI, a sector which is seeing increasing interest and investment

across industries.

I think with Bedrock, Amazon is really aiming to kind of democratize access to generative

AI models.

It's offering a really robust platform for businesses ranging from startups to established

enterprises.

I think it's going to make a big difference in the industry moving forward because AWS,

of course, is the number one cloud provider for a majority of businesses.

And I think having these tools built right in is going to really accelerate adoption

and make it a lot easier for businesses to implement a lot of these tools.

So very interesting to see how this progresses in the future, but definitely big steps from

Amazon.

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Machine-generated transcript that may contain inaccuracies.