Marc Andreessen saw that software was consuming the world a little over a decade ago. We can clearly update his quote: “Software ate the world.” The software has taken over our businesses and how we create value for our consumers.
Consider this: We are a software factory, and we are assisting you in becoming a software factory. You can create the future you want with these powers. With hybrid cloud flexibility, you may pick where to execute your apps based on your business needs (grounded in Linux and open source). Using a shared platform like OpenShift, find repeatability in software production workflows to prevent hand-crafted errors. You may use Ansible to automate distributed system complexity and technologies like ACS to de-risk security in software supply chains from development to production.
Your business is software, and no one could be in the software industry without developers. A high-velocity development team is distinguished by its ability to move quickly from experiment to production. When dealing with the edge, this talent becomes even more vital.
Some of our data-overload difficulties are comparable to those we’ve faced in software development, but we’re now working in a new, more sophisticated environment. In other words, whereas software ate the world, AI is now devouring software.
This is happening due to the fact that so much software is now connecting with the outside world. Businesses seek data insights in the same way that they do with software. Businesses want to be more data-driven and are embracing data and AI to get there – as indicated earlier, this is how we can allow our people to make smarter decisions. We can not only make better use of data to make better decisions, but we can also provide better customer experiences by embedding intelligence in the goods and services our consumers use.
What do you think? Red Hat had similar issues, and as we sought to meet our own requirements – or scratch our itch – we realized we weren’t alone. True to our roots, we made our work public by launching a community initiative. And it was there that we could share our knowledge of data science and machine learning with clients and partners. Open Data Hub is a plan for creating an AI-as-a-service platform.
It serves as the cornerstone for the Red Hat OpenShift Data Science platform, which we debuted last year. And, as we’ve seen, AI isn’t a one-and-done project. You’ve got your software development process in place. Do you have a plan for AI development?
Consider this: your source code is data, and your deployed apps are deployed machine learning models. The discipline of transitioning from source code via testing to large-scale software production is widely established. But, with AI, are you following the same process from development through deployment? And it must happen on a large scale.
If you think that the average organization has a few thousand apps, it also has thousands of machine learning models. As judgments become more reliant on AI/ML – I don’t know about you, but I want to have confidence in the model making those decisions before taking action.
Part of creating trust entails:
- Collaboration – helping in the creation of the model
- Transparency – understanding how the model was created
- Auditability – determining what changes were made to models and their effects on the outcomes
The security provided by data centers and IT assets being safely behind the four walls of headquarters is long gone for CIOs. The cloud, lightning-fast computers, wireless network advances, and the development of far-flung yet critical remote activities have all contributed to this. However, the technological liberties we have today are not without their drawbacks. We believe edge computing will be transformational in this area.
Edge computing refers to the capacity to derive insights from data and act on them locally, where they are needed. Intelligent devices are pushing the limits of where computing may take place — on the ground, in space, and everywhere else there is a value to a company or, perhaps, humanity itself.
Edge computing may now take place at or near the actual location of either the user or the data source — whether that’s a speeding SUV on the highway, sensors monitoring a natural-gas pipeline in the middle of nowhere, or onboard a satellite circulating the planet.
That is the future of hybrid technology.
Your workloads may span the usual IT footprints of data centers, clouds, and the edge with Red Hat. We bring open source community innovation to you, giving you the freedom to select where and how you create and distribute your apps and machine learning models securely.
Let us discuss security. There’s a lot of danger out there: the Apache log4j flaws showed that businesses need to be cautious of what open source they’ve installed and how actively they’re monitoring it.
In practically all audited codebases, open-source is present. Now that I think about it, “open-source software ate the globe.” But your ubiquity makes you a target: software supply chain assaults aiming at exploiting vulnerabilities in upstream, open-source ecosystems increased by 650% year over year in 2021.
Without a doubt, this is a major concern for software firms like Red Hat. And, of course, for you: as you continue to use software to grow your business and differentiate yourself. It’s at the top of government agendas all across the world, especially with ransomware and protest-ware on the increase. Throughout the development lifecycle, we must guarantee that the integrity of software upgrades is secured and confirmed.
To put it another way, the key to adopting open source in the workplace is to be aware of what you’re using, where it’s being used, and how it’s being utilized. Obviously, Red Hat is concerned about the origin and security of the open-source code used in our products. We’re also creating and supplying tools for independent work.