Algorithmia Integrates AI Model Governance with GitOps

Algorithmia integrates AI model governance with GitOps, integrating ML and code development into DevOps workflows that use Git as a source-code repository. With this announcement, Algorithmia has made it easier to use GitHub to break down the silos that traditionally have kept ML developers and application coders from integrating tightly within today’s continuous DevOps workflows.

The Retirement of DAWNBench — What’s Next for Benchmarking the Next Gen Infrastructure for Industrialized Data Science

With the retirement of DAWNBench, I decided to take a look at what’s next for not only the Stanford DAWN project as it reaches its midway point, but also for benchmarking the next gen infrastructure for industrialized data science.

With the Rise of PyTorch TensorFlow’s Deep Learning Dominance May Be Waning

With the rise of PyTorch, TensorFlow’s dominance may be waning. While PyTorch scale advantages are tipping the scales, deployability is still TensorFlow’s strength. Here’s a look at what I think is ahead with these two for deep learning dominance.

NVIDIA’s GeForce NOW Launches — Streaming Cloud Gaming Taking On Google and Others

NVIDIA’s GeForce NOW launched this week, the company’s much-anticipated subscription-based game streaming service. Here’s a look at how it stacks up against competitors Google Stadia and Sony PlayStation, as well as what I think is ahead for these brands in game streaming service offerings.

Alphabet’s Fiscal Q4 and Year-End 2019 Results Show Strong Growth Under Competitive Pressure

Alphabet’s fiscal Q4 and year-end 2019 results show strong growth under competitive pressure. As the company attempts to diversify beyond its consumer focus into enterprise opportunities, Google’s cloud business and the continued courting of enterprise cloud customers may become a crucial failsafe for the company. More on that here.

IBM Post-Rometty — The Immediate Future Lies in Multi-cloud AIOps

It’s clear that IBM with Krishna and Whitehurst at the helm have their work cut out for them, and if they can deliver results short-term, that will be a big win for the company. The battle will be fought for relevance on key fronts including Cloud and AI. Later it will be about market leadership, and where IBM can stake its claim. That is the blueprint for Big Blue. Meanwhile, we will be watching this develop with interest.

Launchable Draws on DevOps to Deliver AI-Powered Software Test Automation

Launchable has emerged from stealth mode to introduce its AI-driven software test automation solution. This is exciting news for the DevOps community, as key industry figures—most notably, the Jenkins CI/CD automation server’s creator—have essentially validated that AI-driven test automation is coming big time into every software development shop.

In a CI/CD context, Launchable’s adaptive AI can drive automated testing of source code changes upon check-in as well as notification of development and operations personnel when the tests fail. It can ensure that developers never have to wait more than a few minutes for feedback on their latest code changes. It can also help testers to keep pace with the growing volume, velocity, and variety of code changes, so that the most relevant changes can be tested 24×7.

The challenge for Launchable is how quickly the company can gain traction in the developer community before incumbent startups in this promising niche solidify their first-mover advantage. Here are thoughts on how the company should move forward so as to quickly take advantage of this opportunity.

Apple’s Acquisition of Xnor.ai Aims to Deliver TinyML to Edge Devices

Bringing Xnor.ai into its product portfolio provides Apple with an edge app development tool geared for a wide range of programmers, not just those who are knowledgeable about AI, DL, and ML. Xnor.ai’s SDK allows programmers to easily drop AI-centric code and data libraries into device-based apps. The tool provides a unified abstraction layer for building, compilation, and training of edge AI models that frees developers from having to worry about target-device CPUs and AI accelerators. Beyond that, let’s take a look at what we think is on the horizon for Apple on the acquisition front.

AWS Releases AutoGluon, an Innovative Open-Source Tooling for Automated Machine Learning

AWS released AutoGluon, an open source toolkit for automated machine learning, designed specifically for software developers, promising the ability to simplify deep learning for non-experts. If AWS were to release AutoGluon as a commercial solution within its flagship data science DevOps solution, it would be the first of the leading vendors to do so. Here’s what we think is essential moving forward if that’s where this is going.

CES 2020: Making Sense of the Glut of Innovation on Display

AI was both a big “winner” and a big “loser” at CES 2020 this week. A winner because just about every vendor’s messaging touted AI as a key feature, but there are a few key reasons that that trend could be troublesome—and brands should take note. My prediction is that AI, though it will remain a core solution capability in coming years, will be a less salient feature in next year’s vendor messaging surrounding CES. Instead, we’ll be immersed in 5G mania. Here’s more on that front.

CES 2020: Consumer-Facing Opportunities Accelerate Evolution of the AI DevOps Toolchain

CES is not an enterprise-oriented tech event. It hosts a wide range of exhibitors and features a fair number of products and technologies. Chief among these versatile technologies is artificial intelligence (AI), which is in abundance at CES 2020.

CES 2020: It Might As Well Stand for Connected Ecosystems Showcase

CES originally stood for “Consumer Electronics Show” but hasn’t gone by that name in years. That’s all for the best, considering that many of the technologies on display at the annual event–such as AI, robotics, and drones—have just as many business, industrial, and scientific applications as uses in the consumer realm.