IBM Journey to AI blog

AUGUST 11, 2023

Machine learning (ML), a subset of artificial intelligence (AI), is an important piece of data-driven innovation. 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. What is MLOps?

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IBM Journey to AI blog

JANUARY 18, 2024

The latest artificial intelligence (AI) chatbots , also known as intelligent virtual assistants or virtual agents, not only understand natural conversations thanks to advanced language models but also proactively automate various tasks using conversational AI technology. ” The advantages of chatbots surround us.

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Chatbots Automation AI Chatbots Natural Language Processing 243

IBM Journey to AI blog

APRIL 18, 2024

Imagine a world where machines aren’t confined to pre-programmed tasks but operate with human-like autonomy and competence. AGI, sometimes referred to as strong AI , is the science-fiction version of artificial intelligence (AI), where artificial machine intelligence achieves human-level learning, perception and cognitive flexibility.

Neural Network 242

Neural Network LLM AI AI 242

IBM Journey to AI blog

SEPTEMBER 19, 2023

Overview: Data science vs data analytics Think of data science as the overarching umbrella that covers a wide range of tasks performed to find patterns in large datasets, structure data for use, train machine learning models and develop artificial intelligence (AI) applications.

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Data Science Data Scientist Machine Learning Data Mining 213

IBM Journey to AI blog

SEPTEMBER 6, 2023

From customized content creation to task automation and data analysis, AI has seemingly endless applications when it comes to marketing, but also some potential risks. Programmatic advertising: Programmatic advertising is the automation of the purchasing and placement of ads on websites and applications. What is AI marketing?

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Automation Data Scientist AI AI 218

IBM Journey to AI blog

FEBRUARY 14, 2024

Using machine learning (ML), AI can understand what customers are saying as well as their tone—and can direct them to customer service agents when needed. 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.

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IBM Journey to AI blog

FEBRUARY 23, 2024

NLP translates the user’s words into machine actions, enabling machines to understand and respond to customer inquiries accurately. Machine learning (ML) and deep learning (DL) form the foundation of conversational AI development. What makes a good AI conversationalist?

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Conversational AI Chatbots NLP AI 267

Ehud Reiter

MAY 5, 2024

Which I think is a mistake, we can learn from previous “booms” and “busts” in AI/Medicine (such as IBM Watson), while of course still hoping and expecting that things will be different this time. Obviously a letter is very short, so I thought I’d expand on the topic in a blog.

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AI AI ML Explainability 109

IBM Journey to AI blog

JANUARY 30, 2024

Automotive: Process vast amounts of data to support the design, development, testing and operation of connected and autonomous vehicles. Explore services for cloud migration The post Achieve Data Center Excellence with IBM and VMware appeared first on IBM Blog.

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Data Analysis Machine Learning Automation AI 202

Heartbeat

FEBRUARY 1, 2023

Machine learning has become an essential part of our lives because we interact with various applications of ML models, whether consciously or unconsciously. Machine Learning Operations (MLOps) are the aspects of ML that deal with the creation and advancement of these models.

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DevOps Machine Learning Data Scientist Software Engineer 96

IBM Journey to AI blog

OCTOBER 16, 2023

Machine learning (ML)—the artificial intelligence (AI) subfield in which machines learn from datasets and past experiences by recognizing patterns and generating predictions—is a $21 billion global industry projected to become a $209 billion industry by 2029.

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AWS Machine Learning Blog

DECEMBER 19, 2023

Artificial intelligence (AI) and machine learning (ML) are becoming an integral part of systems and processes, enabling decisions in real time, thereby driving top and bottom-line improvements across organizations. Machine learning operations (MLOps) applies DevOps principles to ML systems.

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Machine Learning ML Engineer DevOps ML 107

IBM Journey to AI blog

JUNE 26, 2023

By infusing artificial intelligence (AI) into IT operations , you can leverage the considerable power of natural language processing and machine learning models to automate and streamline operational workflows. You’ll also build trustworthy automation for your IT teams since every action is backed by data.

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DevOps Automation Natural Language Processing Artificial Intelligence 143

IBM Journey to AI blog

JULY 6, 2023

While data science and machine learning are related, they are very different fields. In a nutshell, data science brings structure to big data while machine learning focuses on learning from the data itself. What is machine learning? This post will dive deeper into the nuances of each field.

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Data Science Machine Learning Big Data Data Mining 151

IBM Journey to AI blog

MAY 17, 2023

Although AI and machine learning are often touted as the solution to all problems, it’s important to understand that automating a flawed process can make things worse. To stay ahead of potential service disruptions, processes must be optimized before they can be automated.

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Pickl AI

JANUARY 30, 2023

Hence for an individual who wants to excel as a data scientist, learning Python is a must. In this blog, we are going to explore details about a career in Python and what are the new Python jobs for freshers. In this blog, we are going to explore details about a career in Python and what are the new Python jobs for freshers.

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Python DevOps Machine Learning Automation 97

NVIDIA

MARCH 18, 2024

Implemented together, cuOpt, Omniverse and NVIDIA Metropolis for Factories can help optimize and create safe environments in logistics-heavy facilities that rely on complex automation, precise material flow and human-robot interaction, such as automotive factories, semiconductor fabs and warehouses. Learn more about Omniverse.

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Robotics Automation Machine Learning AI 95

IBM Journey to AI blog

JULY 19, 2023

The industry is under tremendous pressure to accelerate drug development at an optimal cost, automate time- and labor-intensive tasks like document or report creation to preserve employee morale, and accelerate delivery. Code creation: Code co-pilot, code conversion, create technical documentation, test cases and more.

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Generative AI Large Language Models AI AI 165

Pragnakalp

APRIL 29, 2024

In our blog, we are specifically focusing on leveraging Microsoft’s Phi-3 model as the Language Model for the RAG framework. This dataset included an equal number of nouns, verbs, and adjectives, providing a balanced and diverse set of linguistic elements for training and testing purposes. Let’s get started!

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Deep Learning Big Data LLM Data Science 59

AWS Machine Learning Blog

JANUARY 5, 2024

Many organizations have been using a combination of on-premises and open source data science solutions to create and manage machine learning (ML) models. The AWS portfolio of ML services includes a robust set of services that you can use to accelerate the development, training, and deployment of machine learning applications.

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IBM Journey to AI blog

JULY 26, 2023

The twin will continuously collect data from the physical asset and use predictive analytics and machine learning (ML) algorithms to predict future performance. New system design and testing : Designing and testing new equipment and systems can be a costly, labor-intensive process.

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Machine Learning Automation Algorithm Robotics 146

IBM Journey to AI blog

JANUARY 24, 2024

We offer the following services within Turbonomic to help:   Optimize on-prem plan to allow users to scale or move virtual machines and consolidate hardware Hardware refresh plan to allow users to see how many new hosts they will need when they upgrade. Figure 2: Turbonomic virtual machine rightsizing 3.

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IBM Journey to AI blog

JULY 11, 2023

Better machine learning (ML) algorithms, more access to data, cheaper hardware and the availability of 5G have contributed to the increasing application of AI in the healthcare industry, accelerating the pace of change. AI and automation can perform many of those mundane tasks, freeing up employee time for other activities.

Deep Learning 152

Deep Learning Natural Language Processing Artificial Intelligence Artificial Intelligence 152

Pickl AI

APRIL 17, 2023

The application of Artificial Intelligence (AI) in DevOps in recent years has increasingly become more popularised because of its ability to automate processes. Read the blog to find out! Accordingly, the accomplishment of these tasks is possible through machine learning, deep learning, and techniques for processing natural language.

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IBM Journey to AI blog

OCTOBER 9, 2023

It can do this primarily by helping automate government services offered to citizens, as well as create greater efficiencies in how agencies communicate internally and with people who rely on public services. In this way, AI-enhanced automation and efficiency could help enable government agencies to serve as a hub for citizens.

Automation 135

Automation AI AI Natural Language Processing 135

deepsense.ai

JULY 30, 2023

The recent strides made in the field of machine learning have given us an array of powerful language models and algorithms. In this blog post we will discuss the importance of LLMOps principles and best practices, which will enable you to take your existing or new machine learning projects to the next level.

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Large Language Models LLM Machine Learning Automation 76

AWS Machine Learning Blog

JANUARY 10, 2024

The large machine learning (ML) model development lifecycle requires a scalable model release process similar to that of software development. An ML model registered by a data scientist needs an approver to review and approve before it is used for an inference pipeline and in the next environment level (test, UAT, or production).

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ML Machine Learning ETL Data Scientist 101

Heartbeat

SEPTEMBER 22, 2023

I write about Machine Learning on Medium || Github || Kaggle || Linkedin. ? Introduction In the world of machine learning, where algorithms learn from data to make predictions, it’s important to get the best out of our models. These parameters significantly influence how the model learns and makes predictions.

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Machine Learning ML Algorithm Automation 64

AWS Machine Learning Blog

MAY 2, 2024

Amazon Personalize makes it straightforward to personalize your website, app, emails, and more, using the same machine learning (ML) technology used by Amazon, without requiring ML expertise. Highly automated operations – Our new recipes are designed to reduce your overhead for training and tuning the model.

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Metadata Software Engineer Large Language Models Machine Learning 93

IBM Journey to AI blog

MAY 26, 2023

Life sciences organizations are developing science/research/commercial clouds to automate mundane tasks associated with each of the areas, such as logging, monitoring, auditing, patching, and integration with an existing toolset, to name a few. Given the rise of AI, ChatGPT and Web3.0,

Automation 204

Automation Machine Learning Artificial Intelligence Artificial Intelligence 204

Towards AI

SEPTEMBER 28, 2023

The previous blog posts, “Data Acquisition & Exploration”, “Data Transformation and Feature Engineering” and “Experiments, Model Training & Evaluation”, explored how AWS SageMaker’s capabilities can help data scientists collaborate and accelerate the journey from data exploration to model creation. Source: Image by the author.

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Automation Data Scientist ML Machine Learning 78

The MLOps Blog

MARCH 28, 2023

In this second installment of the series “Real-world MLOps Examples,” Paweł Pęczek , Machine Learning Engineer at Brainly , will walk you through the end-to-end Machine Learning Operations (MLOps) process in the Visual Search team at Brainly. Watch this video to learn how the Content AI team does MLOps. “If

Machine Learning 59

Machine Learning Automation Data Scientist ML 59

AWS Machine Learning Blog

MARCH 1, 2024

Machine learning (ML) technologies continually improve and power the contact center customer experience by providing solutions for capabilities like self-service bots, live call analytics, and post-call analytics. To assist those who may be starting with a blank canvas, Amazon Lex provides the Amazon Lex automated chatbot designer.

Automation 97

Automation Chatbots ML Conversational AI 97

AWS Machine Learning Blog

APRIL 24, 2024

In this post, we share how we analyzed the feedback data and identified limitations of accuracy and hallucinations RAG provided, and used the human evaluation score to train the model through reinforcement learning. To increase training samples for better learning, we also used another LLM to generate feedback scores.

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Towards AI

MARCH 3, 2024

Ah, the wild world of data science and machine learning, where algorithms roam free, and models hold the keys to unlocking the mysteries of the universe. So, In this blog, we’ll demystify CI/CD, explore its role in data science, and discover how it can elevate your projects to new heights.

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Data Science Python Data Scientist Algorithm 106

AWS Machine Learning Blog

OCTOBER 2, 2023

In this post, we focus on how to automate the edge deployment part of the end-to-end MLOps pipeline. We show you how to use AWS IoT Greengrass to manage model inference at the edge and how to automate the process using AWS Step Functions and other AWS services. If you haven’t read it yet, we recommend checking out Part 1.

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Automation DevOps ML Machine Learning 92

TheSequence

MARCH 11, 2024

Peter Hayes, who holds a PhD in Machine Learning from University College London, is one of the world’s leading experts on this topic. This post is a shortened version of Peter’s original blog, titled 'Evaluating LLM Applications '. Typical makeup of a test suite in software development CI.

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LLM Categorization Software Development Prompt Engineer 52