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 222

Automation DevOps Machine Learning Algorithm 222

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 133

Data Science Data Drift DevOps Auto-complete 133

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

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 261

Computer Vision Robotics Automation NLP 261

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 240

Automation DevOps Artificial Intelligence Artificial Intelligence 240

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 124

Artificial Intelligence Artificial Intelligence Automation DevOps 124

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 Automation 78

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

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?

DevOps 278

DevOps Generative AI Machine Learning Automation 278

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 247

Generative AI Automation ESG AI 247

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 Automation Data Science 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

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 202

Automation Machine Learning DevOps Chatbots 202

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 189

Automation DevOps Algorithm Machine Learning 189

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 Artificial Intelligence 103

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 240

Large Language Models DevOps AI Modeling Automation 240

Mlearning.ai

JULY 31, 2023

Extension Of Devops MLOps is an extension of DevOps. DevOps aims to streamline the development and operation of software applications, while MLOps focuses on the machine learning lifecycle. MLOps extends DevOps by including data science practices, like model training and data preprocessing.

DevOps 52

DevOps Machine Learning Data Scientist Automation 52

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 165

Data Ingestion Big Data Explainability ETL 165

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

Snorkel AI

JUNE 22, 2023

They presented “Automating Data Quality Remediation With AI” at Snorkel AI’s The Future of Data-Centric AI Summit in 2022. Transparency is a critical ingredient in improving the quality and changing data through automated approaches. But the risks are real, and governance is critical to this process. So, how do you tackle this?

Data Quality 52

Data Quality Automation Data Scientist ML 52

Snorkel AI

JUNE 22, 2023

They presented “Automating Data Quality Remediation With AI” at Snorkel AI’s The Future of Data-Centric AI Summit in 2022. Transparency is a critical ingredient in improving the quality and changing data through automated approaches. But the risks are real, and governance is critical to this process. So, how do you tackle this?

Data Quality 52

Data Quality Automation Data Scientist ML 52

Snorkel AI

JUNE 22, 2023

They presented “Automating Data Quality Remediation With AI” at Snorkel AI’s The Future of Data-Centric AI Summit in 2022. Transparency is a critical ingredient in improving the quality and changing data through automated approaches. But the risks are real, and governance is critical to this process. So, how do you tackle this?

Data Quality 52

Data Quality Automation Data Scientist ML 52

AWS Machine Learning Blog

NOVEMBER 7, 2024

The markdown pricing algorithmic solution Zalando relies on is a forecast-then-optimize approach (Kunz et al. Operating such large-scale forecasting requires resilient, reusable, reproducible, and automated machine learning (ML) workflows with fast experimentation and continuous improvements. 2023 and Streeck et al.

ML 111

ML Machine Learning Automation Data Scientist 111

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

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 DevOps 124

Marktechpost

JULY 5, 2024

These courses cover foundational topics such as machine learning algorithms, deep learning architectures, natural language processing (NLP), computer vision, reinforcement learning, and AI ethics. The curriculum also includes classical search, automated planning, and probabilistic graphical models for comprehensive AI training.

Data Science 64

Data Science Machine Learning Software Engineer Data Analysis 64

ODSC - Open Data Science

OCTOBER 9, 2024

By automating repetitive tasks and generating boilerplate code, these tools free up time for engineers to focus on more complex, creative aspects of software development. Well, it is offering a way to automate the time-consuming process of writing and running tests. Just keep in mind, that this shouldn’t replace the human element.

Software Engineer 40

Software Engineer Software Development DevOps ETL 40

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 Neural Network Deep Learning Machine Learning 98

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 AI AI Data Science 145

Mlearning.ai

DECEMBER 21, 2023

It defines a family of algorithms, encapsulates each one, and makes them interchangeable. Used in sorting algorithms where the sorting strategy can be switched dynamically. This makes sorting algorithms interchangeable and easily extendable. The team sets up an automated pipeline for continuous integration and deployment.

Software Engineer 52

Software Engineer Software Development DevOps Algorithm 52

Marktechpost

JULY 14, 2023

Generative AI is a common term for any type of process that uses an algorithm to generate, manipulate, and synthesize data. It blends the features of both DevOps and ML to help organizations design robust ML pipelines with minimal resources and maximum efficiency. What is Generative AI?

Generative AI 52

Generative AI AI Developer AI Development DevOps 52

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 116

Artificial Intelligence Artificial Intelligence AI Tools Auto-complete 116

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

ODSC - Open Data Science

JULY 24, 2023

This firm is a leader in AI and NLP-powered no-code solutions that help build AI co-workers that help “automate complex people- and process-centric processes across functions.” This push for what they call “AI co-workers” allow companies to automate complex business processes that would normally keep their human employees focused.

Data Science 52

Data Science Chatbots Automation Big Data 52

Marktechpost

JULY 17, 2023

It relates to employing algorithms to find and examine data patterns to forecast future events. Algorithms and models Predictive analytics uses several methods from fields like machine learning, data mining, statistics, analysis, and modeling. Machine learning and deep learning models are two major categories of predictive algorithms.

Data Mining 98

Data Mining Machine Learning Data Scientist Artificial Intelligence 98

AWS Machine Learning Blog

JULY 18, 2024

streamlined the analysis of over 70,000 vulnerabilities, automating a process that would have been nearly impossible to accomplish manually. As these advanced models continue to evolve and mature, their capabilities will expand, opening up new frontiers in automating vulnerability analysis, threat detection, and incident response.

Generative AI 118

Generative AI Automation Categorization Software Architect 118

Viso.ai

MARCH 29, 2024

MLflow can be seen as a tool that fits within the MLOps (synonymous with DevOps) framework. Machine learning operations (MLOps) are a set of practices that automate and simplify machine learning (ML) workflows and deployments. ML Tasks – source Automating these ML lifecycle steps is extremely difficult.

Machine Learning 52

Machine Learning ML Automation Data Scientist 52