In the field of natural language processing (NLP), large language models (LLMs) have become crucial for various applications. These models are widely adopted by enterprises, signaling a shift in how we use and gain insights from available data. However, putting these...
Organizations are dedicating significant resources to produce and distribute top-quality software at a more accelerated pace due to the growing competition in the software market (source). To achieve this goal, they use practices such as Continuous Integration (CI),...
If you missed the Red Hat NEXT! event back in September, or if you just want to refresh your memory on some of the amazing content that was presented there, here's a complete listing of all of the talks. Follow the links to see the recordings on the Red Hat Community...
In recent years, “edge devices” have evolved from simple IoT sensors to autonomous drones driven by powerful artificial intelligence (AI) software. Similarly, the processes to develop and deploy AI software to “the edge” have also seen a rapid evolution. Today, data...
Open source software communities have many choices when it comes to modes of communication. Among those choices, mailing lists have been a long standing common choice for connecting with other members of the community. Within mailing lists, the sentiment and...
It was the talk title that caught my eye - “Developer Insights: ML and Analytics on src/”. I was intrigued. I had a few ideas of how machine learning techniques could be used on source code, but I was curious to see what the state of the art looked like now. I...
With an increase in the number of applications being deployed on Red Hat OpenShift, there is a strong need for application monitoring. A number of these applications are monitored via Prometheus metrics, resulting in an accumulation of a large number of time-series...
When developing a new technology, it really helps if you are also a user of that new tech. This has been an approach of Red Hat around artificial intelligence and machine learning -- develop openly on one hand, exchanging knowledge across the organization to use the...
A well-known tactic for figuring out how to identify the root cause of a problem that has caused an outage in a production environment is to go back and see what the environment has been doing so far. Through the analysis of logs, developers and operators alike can...
The prospect of true machine learning is a tangible goal for data scientists and researchers. It has been long known that the platform on which such ML apps can run have to be fast and hyper efficient so that learning can be that much faster. This is the motivation...
As machine learning becomes more interesting to technology companies, it is hardly surprising that a company like Red Hat is going to approach the challenges of this aspect of artificial intelligence with an open source methodology in mind. The immediate benefits to...
The concept of artificial intelligence, which seemed so much like science fiction a few decades ago, has made real, practical inroads in producing results that organizations can find useful. What’s making those results happen, though, isn’t esoteric pie-in-the-sky...
Red Hat’s AI Center of Excellence and PerceptiLabs wanted a way to demonstrate a TensorFlow model to the public during the 2019 Red Hat Summit. The plan was for this model to take images as input, and then respond with the likelihood of a Red Hat fedora being in that...
(There’s a great new conference in the U.S., DevConf.US, returning in 2019 to Boston University (15 to 17 Aug). This highly-technical conference is interested in drawing a diverse group of speakers and attendees, with a specific emphasis on people who are new to...
Analytics, Machine Learning, and AI represent a fundamental transformation that over the coming decade will affect every aspect of society, business, and industry. It will fundamentally change, how we interact with computers - and how we develop, maintain, and operate...
Digital transformation is more than just a fancy buzzword. With 85 percent of Global 2000 CEOs believing in digital innovation as a driver of business success, it is estimated that nearly $2.1 trillion will be invested in digital transformation technologies in 2019....
Experimenting with machine learning algorithms or integrating such techniques into an existing environment often presents challenges, like selecting and deploying the right infrastructure, in addition to having the necessary data science background and skills, etc. In...
Red Hat's work within the field of artificial intelligence is primarily taking three directions right now. First, our engineers see the inclusion of AI features as a workload requirement for our platforms, as well as AI being applicable to Red Hat’s existing core...
Open source software is good. Open source plus open data is even better. That makes initiatives such as the Open Data Hub both useful in and of themselves and as a template for maintaining control over your data. Access to, and the ability to collaboratively build...
The challenges of maintaining persistent storage in environments that are anything but persistent should not be taken lightly. My recent conversation with Ceph founder Sage Weil certainly made that clear. Thus far, the conversation with Sage has highlighted key areas...