IBM Journey to AI blog

SEPTEMBER 17, 2024

Generative AI is not only changing the way applications are built, but the way they are envisioned, designed, tested, documented, and deployed. The appearance of mobile apps and the cloud incorporated new levels of automation and agility into the development lifecycle.

Software Development 125

Software Development Generative AI DevOps AI 125

IBM Journey to AI blog

FEBRUARY 2, 2024

Is it automated? Today’s networks are driven by DevOps, edge computing, and serverless architectures, all of which require an API-first approach to infrastructure. It’s not enough for APIs to simply be available, they should also be well-documented and easy to use. The mechanics of failover matter.

DevOps 290

DevOps Automation 290

IBM Journey to AI blog

JANUARY 11, 2024

And there’s no reason why mainframe applications wouldn’t benefit from agile development and smaller, incremental releases within a DevOps-style automated pipeline. The Intellyx take We are generally skeptical of most vendor claims about AI, as often they are simply automation by another name.

Generative AI 329

Generative AI AI AI DevOps 329

AWS Machine Learning Blog

SEPTEMBER 4, 2024

DevOps engineers often use Kubernetes to manage and scale ML applications, but before an ML model is available, it must be trained and evaluated and, if the quality of the obtained model is satisfactory, uploaded to a model registry. The JSON document can be stored and versioned in an Amazon Simple Storage Service (Amazon S3) bucket.

DevOps 88

DevOps ML Engineer Metadata ML 88

IBM Journey to AI blog

JUNE 2, 2023

Automate routine tasks to free up time to provide personalized services and build relationships with families. improved document management capabilities, web portals, mobile applications, data warehouses, enhanced location services, etc.) Business functional equivalence is essential for automation and project speed.

Auto-complete 265

Auto-complete DevOps Automation Knowledge Model 265

IBM Journey to AI blog

JANUARY 15, 2024

Trend: Automation Like AI and ML, automation will be a huge driver of human productivity. Organizations undergoing digital transformations are likely to uncover wide swaths of manual work that can and should be automated. But organizations still need humans to decide what actions to take based on what the ML-analyzed data shows.

Automation 230

Automation Machine Learning DevOps Artificial Intelligence 230

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

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

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

AUGUST 1, 2023

Organizations have embraced advanced development operations ( DevOps ) procedures to minimize incidents, but they need a resolution process for when they occur. Individual processes can break down, disrupting the service they provide to customers, costing the business money and creating reputational issues.

Automation 189

Automation Categorization DevOps Explainability 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. This ultimately results in software development that is more precise and user-focused.

Software Development 103

Software Development Generative AI DevOps Artificial Intelligence 103

AWS Machine Learning Blog

JANUARY 22, 2024

Amazon Textract is a machine learning (ML) service that enables automatic extraction of text, handwriting, and data from scanned documents, surpassing traditional optical character recognition (OCR). Amazon Textract Queries allows you to specify and extract only the piece of information that you need from the document. What is Name?

DevOps 110

DevOps ML Automation Machine Learning 110

AWS Machine Learning Blog

MARCH 26, 2024

In this post, we show how to automate the accounts payable process using Amazon Textract for data extraction. We also provide a reference architecture to build an invoice automation pipeline that enables extraction, verification, archival, and intelligent search. Now let’s dive into each of the document processing steps.

IDP 102

IDP Metadata Data Extraction DevOps 102

Pickl AI

JANUARY 30, 2023

They keep on adding tutorials and documentation that help the developers and the learner to use this programming language. Data Automation: Automate data processing pipelines and workflows using Python scripting and libraries such as PyAutoGUI and Task Scheduler. to visualize and understand data and model performance.

Python 97

Python DevOps Machine Learning Data Science 97

AWS Machine Learning Blog

JANUARY 12, 2023

In this post, The Very Group shows how they use Amazon Comprehend to add a further layer of automated defense on top of policies to design threat modelling into all systems, to prevent PII from being sent in log data to Elasticsearch for indexing. Engineering squad-level overrides are documented in GitHub on how to use them.

DevOps 119

DevOps Natural Language Processing Metadata Automation 119

AWS Machine Learning Blog

MARCH 27, 2024

This is achieved through practices like infrastructure as code (IaC) for deployments, automated testing, application observability, and complete application lifecycle ownership. Lead time for changes and change failure rate KPIs aggregate data from code commits, log files, and automated test results.

DevOps 99

DevOps Generative AI Automation Software Development 99

AWS Machine Learning Blog

NOVEMBER 7, 2023

Instead of relying solely on their pre-trained knowledge, RAG allows models to pull data from documents, databases, and more. Utilizing natural language processing (NLP), Amazon Kendra comprehends both the content of documents and the underlying intent of user queries, positioning it as a content retrieval tool for RAG based solutions.

Large Language Models 105

Large Language Models Generative AI LLM AI 105

AWS Machine Learning Blog

OCTOBER 8, 2024

Sonnet on Amazon Bedrock, we build a digital assistant that automates document processing, identity verifications, and engages customers through conversational interactions. As a result, customers can be onboarded in a matter of minutes through secure, automated workflows. Using Anthropic’s Claude 3.5

Automation 97

Automation Prompt Engineering Prompt Engineer Computer Vision 97

Pickl AI

OCTOBER 3, 2024

DevOps Practices Cloud Architects should integrate DevOps principles to automate workflows, improve team collaboration, and ensure smooth cloud deployments using tools like Jenkins and Kubernetes. Additionally, possessing cloud security, DevOps practices, and networking skills can further enhance earning potential.

DevOps 52

DevOps Continuous Learning Automation 52

AWS Machine Learning Blog

MAY 1, 2024

This post presents a solution for developing a chatbot capable of answering queries from both documentation and databases, with straightforward deployment. For documentation retrieval, Retrieval Augmented Generation (RAG) stands out as a key tool. The code used in this solution is available in the GitHub repo. Virginia) AWS Region.

Chatbots 113

Chatbots Automation Machine Learning DevOps 113

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. See DataRobot MLOps in Action. Request a Demo.

Data Drift 145

Data Drift AI AI DevOps 145

Viso.ai

DECEMBER 20, 2023

CVAT provides automatic labeling and semi-automated image annotation to speed up the annotation process and expedite annotation services (more about this later). Limitation #2: Lack of source code documentation can make it challenging to understand the tool’s inner workings. Find more here.

Computer Vision 98

Computer Vision Neural Network Deep Learning Automation 98

AWS Machine Learning Blog

JUNE 4, 2024

In this post, we provide guidance on how to create an Amazon Bedrock custom model using HashiCorp Terraform that allows you to automate the process, including preparing datasets used for customization. Terraform provides the benefits of automation, versioning, and repeatability. Add the following Terraform code to your main.tf

Python 122

Python DevOps Automation Artificial Intelligence 122

Heartbeat

FEBRUARY 29, 2024

Furthermore, the software development process has evolved to embrace Agile methodologies, DevOps practices, and continuous integration/continuous delivery (CI/CD) pipelines. These tools have evolved to support the demands of modern software engineering, offering features like real-time collaboration, code analysis, and automated testing.

Software Engineer 52

Software Engineer Software Development LLM Large Language Models 52

Marktechpost

JULY 4, 2023

Regex generation Regular expression generation is time-consuming for developers; however, Autoregex.xyz leverages GPT-3 to automate the process. Automated code reviews & code quality improvement Codiga provides automatic code reviews, and Mutable AI has industrialized Jupyter notebooks.

Large Language Models 104

Large Language Models BERT Natural Language Processing Categorization 104

AWS Machine Learning Blog

MAY 19, 2023

In our previous blogpost Enable the Visually Impaired to Hear Documents using Amazon Textract and Amazon Polly , we showed you our Text to Speech application called “Read for Me”. After containerizing your inference script, the model is ready to be deployed behind a SageMaker endpoint as described in the SageMaker documentation.

Generative AI 93

Generative AI Machine Learning AI AI 93

AWS Machine Learning Blog

DECEMBER 13, 2023

ML operations, known as MLOps, focus on streamlining, automating, and monitoring ML models throughout their lifecycle. Data scientists, ML engineers, IT staff, and DevOps teams must work together to operationalize models from research to deployment and maintenance.

ML 112

ML Automation Metadata Software Development 112

Unite.AI

JUNE 19, 2024

MLOps, or Machine Learning Operations, is a multidisciplinary field that combines the principles of ML, software engineering, and DevOps practices to streamline the deployment, monitoring, and maintenance of ML models in production environments. Design Requirements Engineering : Identifying and documenting the requirements for ML solutions.

Software Engineer 182

Software Engineer DevOps Machine Learning ML 182

AWS Machine Learning Blog

SEPTEMBER 1, 2023

After the completion of the research phase, the data scientists need to collaborate with ML engineers to create automations for building (ML pipelines) and deploying models into production using CI/CD pipelines. All the produced models and code automation are stored in a centralized tooling account using the capability of a model registry.

Generative AI 115

Generative AI Prompt Engineer Prompt Engineering AI 115

IBM Journey to AI blog

SEPTEMBER 5, 2024

Emerging technologies and trends, such as machine learning (ML), artificial intelligence (AI), automation and generative AI (gen AI), all rely on good data quality. Automation can significantly improve efficiency and reduce errors. Be safe Strong data security is a fundamental best practice for any data governance framework.

Metadata 189

Metadata Data Quality Auto-classification DevOps 189

AWS Machine Learning Blog

FEBRUARY 13, 2023

Toolkits to automate the infrastructure become essential for horizontal scaling of AI/ML efforts within a corporation. In the past, AWS CloudFormation templates have been created to automate the creation of these services. Still, not all companies meet their expected returns on their AI/ML journey.

ML 77

ML Artificial Intelligence Machine Learning Artificial Intelligence 77

IBM Journey to AI blog

DECEMBER 1, 2023

The initial use of generative AI is often for making DevOps more productive. AIOps integrates multiple separate manual IT operations tools into a single, intelligent and automated IT operations platform. On the other hand, self-supervised learning is computer powered, requires little labeling, and is quick, automated and efficient.

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Generative AI DevOps Automation Neural Network 300

The MLOps Blog

MARCH 28, 2023

The DevOps and Automation Ops departments are under the infrastructure team. This is the phase where they would expose the MVP with automation and structured engineering code put on top of the experiments they run. “We We are using the internal automation tools we already have to make it easy to show our model endpoints.

Machine Learning 59

Machine Learning Automation Data Scientist ML 59

AWS Machine Learning Blog

AUGUST 1, 2024

Challenges in document understanding for underwriting Document understanding is a critical and complex aspect of the underwriting process that poses significant challenges for insurers. This is a complex task when faced with unstructured data, varying document formats, and erroneous data.

Generative AI 112

Generative AI Natural Language Processing AI AI 112

Bugra Akyildiz

JUNE 9, 2024

MLRun integrates into your development and CI/CD environment and automates the delivery of production data, ML pipelines, and online applications, significantly reducing engineering efforts, time to production, and computation resources. With MLRun, you can choose any IDE on your local machine or on the cloud.

Deep Learning 52

Deep Learning Algorithm DevOps Data Science 52

IBM Journey to AI blog

JULY 16, 2024

To maintain consistency and expedited deployments, Kate’s code repository is configured to trigger Azure DevOps pipeline builds, which has automation capability to perform all deployment operations. As a result of these changes, the user interface was now modern and intuitive, and the processes were automated and efficient.

DevOps 100

DevOps Automation Software Development Generative AI 100

Marktechpost

AUGUST 30, 2024

On top of dealing with complicated documentation and software development kits (SDKs), existing cloud-native database services necessitate even more DevOps to orchestrate individual database instances: schema migrations, connection pooling, versioning across cases, etc.

DevOps 62

DevOps Software Development Automation Machine Learning 62