Amid all of the groundbreaking advances that are taking place right now, it’s clear that companies need to work quickly to stay at the forefront of their industries, using what’s possible in artificial intelligence implementations.
One thing that’s happening, to a great extent, is corporate allegiances.
We have companies that dominate in their verticals, but they don’t often have that full stack in-house. They collaborate with others to stay ahead in whatever they’re offering to enterprise or consumer customers.
Now, for example, Amazon is doubling down when it comes to its partnership with AI startup Anthropic, to enable AWS customers in using services based on Anthropic’s new models.
After a $4 billion investment in September of last year, Amazon is now announcing a second round at the same price.
What does this mean?
It means that Amazon Web Services, the managed web services division of Amazon, is going to integrate Anthropic products and capabilities into its platforms.
AWS in the Cloud Era
During the era of the cloud and virtualization, Amazon Web Services became a household name, and to a large extent, dominant in the cloud industry. It offers object storage, server capacity, and more on the premise of virtualization and distributed infrastructure. There’s a lot of plug and play opportunity for companies. So in the rush to go to the cloud, AWS mushroomed.
Here’s a professional talking about what the norm was in the days before virtualization:
“In the pre-virtualization era, infrastructure deployment was manual. Infrastructure took months to be provisioned, racked, stacked, wired, installed, and configured,” writes Stephen Orban for the AWS Cloud Enterprise Strategy Blog. “Most applications were monolithic, with tight inter-dependencies and manual deployment. Installation and configuration guides commonly ran dozens, if not hundreds, of pages long. Data center efficiency was also a challenge. With such long provisioning cycles, businesses would often provision 25–40% more than what was needed during peak usage. With so much wasted capacity, utilization rates were often less than 10%. In this model, the development, infrastructure and operations teams all operated in silos, requiring weeks or months of planning for every change. Operations itself became a major challenge since everything was managed and operated manually, with little standardization across environments.”
Then everything changed.
As the cloud took over, all of a sudden, companies could simply outsource all of their data center needs. They could put workloads and data sets into the cloud, and access them as necessary. They could get elastic on-demand service levels for scaling or dynamic use.
And so they did, in a multitude. AWS grew quickly, gaining a legion of enterprise customers, leading to continued success. Here’s this from Statista:
“AWS raked in over 90 billion U.S. dollars in net sales revenue, forming a significant portion of Amazon’s net total for 2023.”
So now, with AI, all of these customers can seamlessly access Anthropic models, like Claude, which is learning to use a computer like a human being and perform agentic tasks as an AI entity.
If you think about it, this partnership makes a lot of sense, and it’s likely to be a template for other companies. In other words, a cloud services provider works with a particular AI company to utilize its models in bringing AI capability to customers.
There’s also a lot of potential in announcing these partnerships, too. It boosts recognition and the reputation of companies in the tech world.
A Giant in Tech and Beyond
It’s interesting to note, however, that Amazon didn’t start from a place of inconspicuousness. In addition to dominating cloud services, the same company name is also synonymous with package delivery, obviously. Its founder is worth many billions of dollars as the company boasts not one but two monolithic divisions.
But whether your company is the biggest around or a scrappy SMB, the principal remains the same – startups like Anthropic and big names like OpenAI are offering the power of their models to the enterprise world. That’s going to shape how the business world evolves quickly, as we realize what large language models and neural networks can do. Let’s just enumerate some of the new skills they’ve picked up in just a couple of years:
· Reasoning and delivering chains of thought, explaining multi-step processes
· Generating all kinds of high-quality graphics and text
· Working on high-level tasks independently with minimal human supervision
· Aggregating and processing massive data sets to develop targeted recommendations for specific use cases
That’s just a start, but you can see how transformative all of this is going to be, and first movers like Amazon are going to benefit immensely.
