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 Robotics NLP 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

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

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 135

Data Science Data Drift DevOps Auto-complete 135

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

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

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 213

Data Ingestion Big Data Explainability ETL 213

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

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

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

Marktechpost

DECEMBER 18, 2024

AI-powered tools have become indispensable for automating tasks, boosting productivity, and improving decision-making. It automates code documentation and integrates seamlessly with AWS services, simplifying deployment processes. It automates model development and scales predictive analytics for businesses across industries.

Software Development 103

Software Development AI Tools DevOps Machine Learning 103

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 Automation 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

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

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

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

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 128

Deep Learning Auto-complete Algorithm ML 128

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 131

Generative AI Automation Categorization Software Architect 131

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 112

Artificial Intelligence Artificial Intelligence AI Tools Auto-complete 112

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.

Machine Learning 98

Machine Learning Data Mining Data Scientist Data Science 98

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 NLP 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

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

MAY 8, 2024

Concurrently, the ensemble model strategically combines the strengths of various algorithms. By conducting experiments within these automated pipelines, significant cost savings could be achieved. million subscribers, which amounts to 57% of the Sri Lankan mobile market. It also helps maintain an experiment version tracking system.

ML 127

ML Categorization AI AI 127

The MLOps Blog

JUNE 27, 2023

For example, if your team works on recommender systems or natural language processing applications, you may want an MLOps tool that has built-in algorithms or templates for these use cases. This includes features for hyperparameter tuning, automated model selection, and visualization of model metrics.

Machine Learning 134

Machine Learning Metadata Data Scientist Data Quality 134

DataRobot Blog

MARCH 16, 2023

That focus often leads to over-rotatation on building a better algorithm or neural-network or finding more data to improve model performance as opposed to the improvement of business performance. This narrow focus can lead to accurate and true insights that are not really useful, leaving business stakeholders feeling frustrated.

AI 98

AI AI DevOps Neural Network 98

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 61

Data Science Machine Learning Data Analysis Software Engineer 61

AWS Machine Learning Blog

APRIL 26, 2023

This includes AWS Identity and Access Management (IAM) or single sign-on (SSO) access, security guardrails, Amazon SageMaker Studio provisioning, automated stop/start to save costs, and Amazon Simple Storage Service (Amazon S3) set up. MLOps engineering – Focuses on automating the DevOps pipelines for operationalizing the ML use case.

ML 117

ML Machine Learning Data Science Data Drift 117