A modern faith that is likely to pay off

Amidst all the groundbreaking advancements taking place right now, it’s clear that companies need to work quickly to stay at the forefront of their industries by leveraging everything possible in AI applications.

One thing that happens, to a large extent, is corporate commitments.

We have companies that dominate their industries, but they don’t often have that full stack internally. They work with others to stay ahead of anything they offer business or consumer customers.

Now, for example, Amazon is doubling down on its partnership with AI startup Anthropic to enable AWS customers to use services based on Anthropic’s new models.

After a $4 billion investment in September last year, Amazon now announcesin a second round at the same price.

What does this mean?

It means that Amazon Web Services, Amazon’s managed web services division, is going to integrate Anthropic products and capabilities into its platforms.

AWS in the Cloud Era

In the era of cloud and virtualization, Amazon Web Services has become a household name and, to a large extent, dominant in the cloud industry. It offers object storage, server capacity and more with the premise of virtualization and distributed infrastructure. There are many plug and play opportunities for companies. So, in the rush to go cloud, AWS sprung up.

Here’s a professional talking about what was the norm in the days before virtualization:

“In the pre-virtualization era, infrastructure deployment was manual. The infrastructure took months to envision, stockpile, stack, wire, install and configure,” writes Stephen Orban on AWS Cloud Enterprise Strategy Blog. “Most applications were monolithic, with tight interdependencies and manual development. Setup and configuration wizards typically ran tens, if not hundreds, of pages. Data center efficiency was also a challenge. With such long provisioning cycles, businesses often provision 25-40% more than was needed during peak usage. With so much wasted capacity, utilization rates were often less than 10%. In this model, development, infrastructure, and operations teams all operated in silos, requiring weeks or months of planning for each change. The operations themselves became a big challenge, as everything was managed and operated manually, with little standardization across environments.”

Then everything changed.

As the cloud took over, suddenly companies could simply outsource all their data center needs. They could put workloads and datasets in the cloud and access them as needed. They could receive elastic service levels on demand for scaling or dynamic use.

And so they did, in a crowd. AWS grew rapidly, gaining a legion of enterprise customers, leading to continued success. Here’s this from Statista:

“AWS has raised over US$90 billion to net sales revenuemaking up a significant portion of Amazon’s net total for 2023.”

So now, with AI, all these customers can have seamless access to Anthropic models, like Claude, who learns to use a computer like a human and perform agentic tasks as an AI entity.

If you think about it, this partnership makes a lot of sense and is likely to be a model for other companies. In other words, a cloud service provider works with a specific AI company to use their models to provide customers with AI capability.

There are also many possibilities for announcing these partnerships. It enhances the recognition and reputation of companies in the technology world.

A giant in technology and beyond

It is interesting to note, however, that Amazon did not start from a point where it did not appear. Besides dominating cloud services, the same company name is also synonymous with package delivery, apparently. Its founder is worth several billion dollars as the company has not one but two monolithic divisions.

But whether your company is the world’s largest or a scrappy SMB, the principle remains the same – startups like Anthropic and big names like OpenAI bring the power of their models to the business world. This will shape the way the business world rapidly evolves as we realize what large language models and neural networks can do. Let’s list some of the new skills they have acquired in just a few years:

· Reasoning and delivering chains of thought, explaining multi-step processes

· Create all kinds of high quality graphics and text

· Work on high-level tasks independently with minimal human supervision

· Collect and process massive data sets to develop targeted recommendations for specific use cases

This is just the beginning, but you can see how transformative this will all be, and first movers like Amazon will benefit immensely.