Up until the last 10 years or so, artificial intelligence was the stuff of science fiction: machines that could learn from a variety of interactions to make decisions and take actions that would normally require a human to execute. Because of that science fiction, there are those who fear AI as the beginning of the rise of intelligent robots. So, ethical development of AI has become an important issue in the IT community.
Artificial intelligence is having a big impact on application development. Today, we see AI in many different computing environments. It is also popping up in customer service call centers, in dialog boxes on websites, in the Industrial Internet of Things, as well as in our children’s toys, our homes and businesses. When coupled with automated processes, machines can take over many of the more mundane tasks businesses have to complete on a daily basis.
Of course, applications of AI are much broader and more sophisticated. AI can be found in automotive controls, such as applying the brake when your car is quickly approaching the one ahead. It’s found in data analytics, processing and management, where AI can learn to spot anomalies in data and trigger alerts and actions to remediate the issue.
With the release of TIBCO WebFOCUS 9.0.0, the company announced stronger data access, AI/ML capabilities, and developer tools. “Valuable data and AI/ML algorithms flow through absolutely every corner of an organization. The use of visual discovery and improved data management enables users and developers to turn that raw data into truly meaningful insights,” said Mark … continue reading
Indico Data, the unstructured data company, unveiled Indico 5 to allow companies to better make use of automation and intelligent document processing (IDP) on unstructured data. Despite 90% of enterprise data being unstructured according to a December 2021 IDC report, only 2% of it is being utilized based on additional Google research. The platform uses … continue reading
U.S.A., March 14, 2021 — Olive, the automation company creating the Internet of Healthcare, today announced an alliance with NTT DATA, a global digital business and IT services leader. The collaboration will fast track the creation of new healthcare solutions to transform the health experience for humans — both in the traditional healthcare setting and … continue reading
While the amount of data in the world is infinite, our attention span is not. That’s why AI is becoming a valuable tool for data integration to create concise analysis from data and to make it more accessible to everyone throughout an organization. According to SnapLogic’s Ultimate Guide to Data Integration, AI and ML capabilities … continue reading
Earlier this week, at an event on AI in the Metaverse, Meta (previously Facebook) announced that it was open-sourcing TorchRec. TorchRec is a PyTorch library for recommendation systems. According to PyTorch, the TorchRec library includes modeling primitives, optimized recommendation system kernels, a sharder for partitioning tables, a planner than can generate sharding plans, GPU inference … continue reading
Microsoft Azure has been showing faster growth than any other cloud provider over the last few years, and its vast ecosystem of partnerships and integrations continually make it an appealing platform for existing and prospective customers. The platform currently stands as the second largest cloud offering in the world with 21% market share, following AWS’s … continue reading
Elyra is a set of AI-centric extensions to JupyterLab Notebooks that includes features like an AI pipelines visual editor; the ability to run a notebook, Python, or R script as a batch job; reusable code snippets, and more. To create pipelines using the Visual Pipeline Editor, users need to open the JupyterLab Launcher and select … continue reading
If the adage “data is the new oil” stands true, then Integration Platform as as Service (iPaaS) is the machinery you need to drill and tap it. The allure of iPaaS is that it offers the integration needed to knit and integrate the data and processes of multiple business applications and the actual applications themselves. … continue reading
ZenML is an extensible open-source MLOps framework designed to create reproducible pipelines. The framework enables data scientists to write their code as automated pipelines from day one. It is built to encourage the iterative and experimental nature of machine learning work, but also to provide a path to an automated, production-ready software base that can … continue reading
Developers can now fine-tune GPT-3 on their own data, creating a custom version tailored to their application, which allows for faster and cheaper running of models. GPT-3 is a natural language programming tool developed by AI research laboratory OpenAI. Users have to run a single command in the OpenAI CLI tool with the file that … continue reading
While we’re not quite fully there yet, we may not be too far away from AI being a major part of the development process, helping developers eliminate some of the more mundane tasks of coding by suggesting code, autocompleting code, and making other useful suggestions. According to Chandra Kalle, VP of engineering at LeanTaaS, a … continue reading
Testing in DevOps is as much about the people that are behind the tools as it is about the tools themselves. When they work in synchrony, organizations can see major benefits in the quality of their applications and software development life cycle processes. A recent report called The Role of Testing in a DevOps Environment … continue reading