IBM Journey to AI blog

JUNE 5, 2024

However, SaaS architectures can easily overwhelm DevOps teams with data aggregation, sorting and analysis tasks. Modern SaaS analytics solutions can seamlessly integrate with AI models to predict user behavior and automate data sorting and analysis; and ML algorithms enable SaaS apps to learn and improve over time.

DevOps 236

DevOps Automation ML Machine Learning 236

IBM Journey to AI blog

MARCH 20, 2024

Cloud-native applications and DevOps A public cloud setting supports cloud-native applications—software programs that consist of multiple small, interdependent services called microservices , a crucial part of DevOps practices. When developers finish using a testing environment, they can easily take it down.

DevOps 281

DevOps Big Data Artificial Intelligence Artificial Intelligence 281

Unite.AI

NOVEMBER 17, 2023

During the coding and testing phases, AI algorithms can detect vulnerabilities that human developers might miss. Automated Code Review and Analysis AI can review and analyze code for potential vulnerabilities. AI recommends safer libraries, DevOps methods, and a lot more.

Artificial Intelligence 299

Artificial Intelligence Artificial Intelligence DevOps Automation 299

Unite.AI

JUNE 19, 2024

In world of Artificial Intelligence (AI) and Machine Learning (ML), a new professionals has emerged, bridging the gap between cutting-edge algorithms and real-world deployment. CI/CD Pipelines : Setting up continuous integration and delivery pipelines to automate model updates and deployments.

Software Engineer 182

Software Engineer DevOps Machine Learning ML 182

AWS Machine Learning Blog

MARCH 21, 2025

However, by using Anthropics Claude on Amazon Bedrock , researchers and engineers can now automate the indexing and tagging of these technical documents. Renu has a strong passion for learning with her area of specialization in DevOps. samples/2003.10304/page_0.png' samples/2003.10304/page_0.png'

Metadata 116

Metadata Convolutional Neural Networks Generative AI Data Scientist 116

IBM Journey to AI blog

SEPTEMBER 19, 2023

DevOps , SRE , Platform, I TOps, and developer teams are all under pressure to keep applications performant while operating faster and smarter than ever. Once the telemetry data is collected, Instana uses advanced analytics and machine learning algorithms to automatically detect and diagnose issues.

Automation 236

Automation DevOps Artificial Intelligence Artificial Intelligence 236

IBM Journey to AI blog

AUGUST 11, 2023

Machine learning engineers take massive datasets and use statistical methods to create algorithms that are trained to find patterns and uncover key insights in data mining projects. It advances the scalability of ML in real-world applications by using algorithms to improve model performance and reproducibility. What is MLOps?

Data Science 170

Data Science DevOps Machine Learning Data Scientist 170

IBM Journey to AI blog

FEBRUARY 14, 2024

McDonald’s is building AI solutions for customer care with IBM Watson AI technology and NLP to accelerate the development of its automated order taking (AOT) technology. For example, Amazon reminds customers to reorder their most often-purchased products, and shows them related products or suggestions.

Computer Vision 247

Computer Vision NLP Robotics Automation 247

Unite.AI

OCTOBER 4, 2023

Hallucinations stem from the way statistics are used in the implementation of the algorithms. The second is optimizing the operations, particularly through the use of automation and FinOps. What are some of the challenges behind Generative AI hallucinations and how is Amdocs addressing this to reduce or mitigate these?

Generative AI 278

Generative AI DevOps Machine Learning Automation 278

IBM Journey to AI blog

FEBRUARY 13, 2024

Optimize performance through automation Turbonomic revolutionizes application performance optimization by leveraging AI and machine learning algorithms to analyze real-time performance data and give insight into application response time and transaction time.

Automation 208

Automation DevOps Machine Learning Algorithm 208

AI News

AUGUST 29, 2023

The operationalisation of data projects has been a key factor in helping organisations turn a data deluge into a workable digital transformation strategy, and DataOps carries on from where DevOps started. And everybody agrees that in production, this should be automated.”

Data Ingestion 245

Data Ingestion Big Data Explainability ETL 245

IBM Journey to AI blog

OCTOBER 25, 2023

But simultaneously, generative AI has the power to transform the process of application modernization through code reverse engineering, code generation, code conversion from one language to another, defining modernization workflow and other automated processes. Much more can be said about IT operations as a foundation of modernization.

Generative AI 243

Generative AI Automation ESG AI 243

AWS Machine Learning Blog

APRIL 8, 2025

Additionally, the integration of SageMaker features in iFoods infrastructure automates critical processes, such as generating training datasets, training models, deploying models to production, and continuously monitoring their performance. This integration not only simplifies complex processes but also automates critical tasks.

Machine Learning 98

Machine Learning ML Auto-complete Data Scientist 98

AWS Machine Learning Blog

JANUARY 5, 2024

Data science and DevOps teams may face challenges managing these isolated tool stacks and systems. AWS also helps data science and DevOps teams to collaborate and streamlines the overall model lifecycle process. MLOps – Model monitoring and ongoing governance wasn’t tightly integrated and automated with the ML models.

Data Science 134

Data Science Data Drift DevOps Auto-complete 134

Pickl AI

APRIL 17, 2023

How can a DevOps team take advantage of Artificial Intelligence (AI)? DevOps is mainly the practice of combining different teams including development and operations teams to make improvements in the software delivery processes. So now, how can a DevOps team take advantage of Artificial Intelligence (AI)?

DevOps 52

DevOps Artificial Intelligence Artificial Intelligence Machine Learning 52

IBM Journey to AI blog

SEPTEMBER 20, 2023

They use self-supervised learning algorithms to perform a variety of natural language processing (NLP) tasks in ways that are similar to how humans use language (see Figure 1). IBM watsonx.governance is an end-to-end automated AI lifecycle governance toolkit that is built to enable responsible, transparent and explainable AI workflows.

Large Language Models 238

Large Language Models DevOps Data Science AI Modeling 238

IBM Journey to AI blog

AUGUST 16, 2023

Proper financial management requires FinOps—a combination of financial personnel and DevOps. Intelligent tools based on machine learning algorithms and other predictive technologies can assist in this regard. Embracing cloud optimization tools and automation can keep costs down, especially for periods of low resource usage.

Automation 187

Automation DevOps Algorithm Machine Learning 187

IBM Journey to AI blog

AUGUST 15, 2023

Recent AI developments are also helping businesses automate and optimize HR recruiting and professional development, DevOps and cloud management, and biotech research and manufacturing. Companies can create automated customer service workflows with customized AI models built on customer data.

Artificial Intelligence 234

Artificial Intelligence Artificial Intelligence Natural Language Processing AI 234

IBM Journey to AI blog

JUNE 10, 2024

Many of these platforms use automation and machine learning (ML) tools to automate the process of remediation or identify issues before they arise. These systems deploy machine learning algorithms to monitor large data sets and use them to identify anomalous data.

Automation 189

Automation Machine Learning DevOps Chatbots 189

ODSC - Open Data Science

JANUARY 9, 2024

Focus on Automation and DevOps Practices Automation and DevOps practices are becoming increasingly important in data engineering. Automation can help to reduce the time and cost of data engineering tasks, while DevOps practices can help to improve the reliability and scalability of data pipelines.

DevOps 97

DevOps Data Science Algorithm Natural Language Processing 97

IBM Journey to AI blog

JULY 11, 2024

Developments in machine learning , automation and predictive analytics are helping operations managers improve planning and streamline workflows. It can also streamline workflows through automation, improve procurement, reduce disruptions and provide better end-to-end visibility and transparency.

Artificial Intelligence 122

Artificial Intelligence Artificial Intelligence Automation DevOps 122

ODSC - Open Data Science

JANUARY 31, 2023

Getting insight into your system allows you to detect and resolve issues quickly — and it’s an essential part of DevOps best practices. This is especially important for companies moving toward DevOps practices, where production environments have become more automated and continuous delivery pipelines are more complex.

DevOps 105

DevOps Machine Learning Data Science Automation 105

Heartbeat

FEBRUARY 1, 2023

MLOps is a highly collaborative effort that aims to manipulate, automate, and generate knowledge through machine learning. They may also be involved in the deployment process’s automation. It can assist you in simplifying and automating the creation and operation of machine-learning models.

DevOps 96

DevOps Machine Learning Data Scientist Software Engineer 96

Becoming Human

MAY 11, 2023

Machine learning operations, or MLOps, are the set of practices and tools that aim to streamline and automate the machine learning lifecycle. It is a discipline that seeks to automate the various stages of the machine learning lifecycle, from data acquisition and cleaning to model training, deployment, and monitoring.

Machine Learning 78

Machine Learning DevOps Software Development Data Scientist 78

DataRobot Blog

SEPTEMBER 1, 2022

You need full visibility and automation to rapidly correct your business course and to reflect on daily changes. Imagine yourself as a pilot operating aircraft through a thunderstorm; you have all the dashboards and automated systems that inform you about any risks. Autoscaling Deployments with MLOps. See DataRobot MLOps in Action.

Data Drift 145

Data Drift Data Science AI AI 145

Becoming Human

APRIL 19, 2024

Automated Testing: By automating the creation of test cases, generative AI can expedite the software development process’ testing phase. This automated testing method improves software products’ overall reliability and quality. Higher quality of software and more customer happiness are the results of AI incorporation.

Software Development 103

Software Development Generative AI DevOps Automation 103

IBM Journey to AI blog

JULY 11, 2024

Developments in machine learning , automation and predictive analytics are helping operations managers improve planning and streamline workflows. It can also streamline workflows through automation, improve procurement, reduce disruptions and provide better end-to-end visibility and transparency.

Artificial Intelligence 100

Artificial Intelligence Artificial Intelligence Automation DevOps 100

Pickl AI

JANUARY 30, 2023

Data Automation: Automate data processing pipelines and workflows using Python scripting and libraries such as PyAutoGUI and Task Scheduler. Scripting: Use Python as a scripting language to automate and simplify tasks and processes. Python helps in this process. to build and implement Machine Learning models.

Python 97

Python DevOps Machine Learning Data Science 97

AWS Machine Learning Blog

AUGUST 26, 2024

MMPose is a member of the OpenMMLab Project and contains a rich set of algorithms for 2D multi-person human pose estimation, 2D hand pose estimation, 2D face landmark detection, and 133 keypoint whole-body human pose estimations. He is passionate about building home automation and AI/ML solutions.

Generative AI 123

Generative AI DevOps AI AI 123

AWS Machine Learning Blog

OCTOBER 23, 2024

Wittly uses advanced AI algorithms, overseen and enhanced by the expertise of human educators and engineers, to generate instructional recommendations. Roy Gunter , DevOps Engineer at Curriculum Advantage, manages cloud infrastructure and automation for Classworks.

DevOps 91

DevOps Generative AI LLM Large Language Models 91

Unite.AI

JUNE 24, 2024

It combines principles from DevOps, such as continuous integration, continuous delivery, and continuous monitoring, with the unique challenges of managing machine learning models and datasets. As the adoption of machine learning in various industries continues to grow, the demand for robust MLOps tools has also increased.

Data Drift 124

Data Drift Machine Learning Data Scientist ML 124

Bugra Akyildiz

JANUARY 25, 2025

They mainly supported this effort through: New Operators : NVIDIA added new operators and exposed existing ones to support ReDrafter's beam search and tree attention algorithms, which were previously unused in TensorRT-LLM. ZeroBAS has the following capabilities: 1.

LLM 52

LLM Large Language Models Neural Network DevOps 52

AWS Machine Learning Blog

NOVEMBER 19, 2024

These sessions, featuring Amazon Q Business , Amazon Q Developer , Amazon Q in QuickSight , and Amazon Q Connect , span the AI/ML, DevOps and Developer Productivity, Analytics, and Business Applications topics. Attendees will learn practical applications of generative AI for streamlining and automating document-centric workflows.

ML 98

ML Generative AI AI AI 98

Viso.ai

DECEMBER 20, 2023

Modern vision systems use algorithms based on machine learning, deep learning especially, that need to be trained on images annotated by humans (supervised learning). Therefore, the CVAT tool was designed to accelerate the process of annotating videos and images for use in training computer vision algorithms.

Computer Vision 98

Computer Vision Deep Learning Neural Network Machine Learning 98

Marktechpost

DECEMBER 4, 2023

Trained on a large open-source code dataset, it suggests snippets to full functions, automating repetitive tasks and enhancing code quality. The ‘Notion AI is an AI system that may be used to automate a wide variety of writing tasks, from blogs and lists to brainstorming sessions and creative writing.

AI Tools 134

AI Tools Auto-complete Artificial Intelligence Artificial Intelligence 134

AWS Machine Learning Blog

MAY 16, 2024

Therefore, we decided to introduce a deep learning-based recommendation algorithm that can identify not only linear relationships in the data, but also more complex relationships. Recommendation model using NCF NCF is an algorithm based on a paper presented at the International World Wide Web Conference in 2017.

Deep Learning 123

Deep Learning Auto-complete Algorithm ML 123

Marktechpost

MAY 3, 2024

Trained on a large open-source code dataset, it suggests snippets to full functions, automating repetitive tasks and enhancing code quality. The ‘Notion AI is an AI system that may be used to automate a wide variety of writing tasks, from blogs and lists to brainstorming sessions and creative writing.

Artificial Intelligence 113

Artificial Intelligence Artificial Intelligence AI Tools Auto-complete 113