Where Are We in the Evolution to Software 2.0?
April 09, 2020

Glenn Gruber
Anexinet

A recent MIT/BCG study revealed that 84% surveyed feel AI is critical to obtain or sustain competitive advantage, and three out of four surveyed believe that Machine Learning provides an opportunity to enter new businesses and that AI will be the basis for new entrants into their industry. Which shouldn't come as a surprise to anyone, seeing as how advances in GPU/TPU technology, and the development of new platforms and frameworks have enabled an explosion in AI and Machine Learning, while new platforms from Amazon, Microsoft and others have put pre-built frameworks firmly in the grasp of developers. Despite all this movement, however, we are still definitely very early in the transition to using AI to transform software development — commonly referred to as Software 2.0, or AIOps. 

Tesla is one shining example that emphasizes how early we are, and just how much expertise is required in an organization in order for the enterprise to gain the level of maturity necessary to take on this advanced, yet still esoteric, technology. Tesla uses computer vision, and other Machine Learning algorithms, to enable their vehicles to make literally thousands of decisions a millisecond. Most companies don't have anywhere near the comparable expertise in Artificial Intelligence and/or Machine Learning to take on this level of complexity on their own. But we remain optimistic, since Tesla's success thus far does inform what's possible in the near future.
 
The difficulty inherent in the transformation of DevOps to AIOps is that the two methodologies are not even close to being the same thing. Algorithmia, a company intent on "building the future of Machine Learning infrastructure," is one other organization that has already developed a flagship DevOps platform for AI. This tweet from Diego Oppenheimer, CEO/founder of Algorithmia, (quoting Mike Anderson, also of Algorithmia) illustrates what I mean when I say DevOps and AIOps are not one and the same: "Expecting your engineering and DevOps teams to deploy ML models well is like showing up to Seaworld with a giraffe, since they are already handling large mammals."
 
The low-code Lego models may be faster, but that doesn't mean they are optimized or efficient when you piece all the Legos together into a full-blown application. Though over time it's possible these components will improve. Some of the advantages of this approach can also be achieved (but perhaps without the continuous improvement of evaluating the quality of the code) through Reusable Component Libraries.
 
Many companies that may be eager to start down on the AI path will necessarily be relying on those familiar platform providers that are immediately available to them to improve/optimize code — such as the Microsoft Intellicode. We've also seen Apple launch SwiftUI, CreateML, and Reality Composer — all products aimed at reducing the coding effort as well as a significant investment in Swift (a far more efficient and declarative syntax that intrinsically requires less code) and the underlying ML and AR frameworks to pull it off. But like the Microsoft example, this is being led by the platform providers.

Glenn Gruber is a Senior Digital Strategist at Anexinet
Share this

Industry News

October 29, 2020

Cisco announced new software-delivered solutions designed to simplify IT operations across on-premise data centers and multicloud environments.

October 29, 2020

Bugsnag announced availability of user stability analytics, which will help developers gain a clearer understanding of how application errors are impacting the user experience and other key performance indicators (KPIs) for the business, as well as offer insights on whether to fix bugs or build new features.

October 29, 2020

HAProxy Technologies announced an open-source release of a VMware Open Virtual Appliance (OVA) virtual machine image of the HAProxy load balancer for vSphere, which HAProxy Technologies will maintain on GitHub.

October 28, 2020

Progress announced a number of new innovations designed to facilitate adoption and at-scale deployment of Chef offerings for both new and experienced users of the DevSecOps portfolio.

October 28, 2020

StackRox announced the release of KubeLinter, its new open source static analysis tool to identify misconfigurations in Kubernetes deployments.

October 28, 2020

Vercel announced Next.js 10 featuring a number of new capabilities that accelerate frontend developers’ ability to enrich end users’ web experiences globally.

October 27, 2020

ThinkTank has released a suite of applications designed to keep distributed agile teams aligned and engaged, regardless of physical location.

October 27, 2020

Cloudify, a Service Orchestration and Automation Platform, announced its latest 5.1 product release which aims to take one step further to permanently remove silos and roadblocks that are consistently associated with migration to the public cloud.

October 27, 2020

WhiteSource announced its new native integration for Microsoft Azure DevOps services.

October 26, 2020

NetApp unveiled a new serverless and storageless solution for containers from Spot by NetApp, a new autonomous hybrid cloud volume platform, and cloud-based virtual desktop solutions.

October 26, 2020

GeneXus released GeneXus 17, a new version of its platform that empowers enterprises to create and evolve new applications at unprecedented speed.

October 26, 2020

Alcide announced the company’s security solutions are now integrated with AWS Security Hub, sending real-time threat intelligence and compliance information to Amazon Web Services (AWS) for easy consumption by Security and DevSecOps teams.

October 22, 2020

Puppet announced Puppet Comply, a new product built to work with Puppet Enterprise aimed at assessing, remediating, and enforcing infrastructure configuration compliance policies at scale across traditional and cloud environments.

October 22, 2020

Harness announced two new modules: Continuous Integration Enterprise and Continuous Features.

October 22, 2020

Render announced automatic preview environments which are essential for rapid and collaborative development of modern applications.