IBM Journey to AI blog

OCTOBER 16, 2023

ML algorithms and data science are how recommendation engines at sites like Amazon, Netflix and StitchFix make recommendations based on a user’s taste, browsing and shopping cart history. Here are some real-world applications of machine learning that have become part of our everyday lives.

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Machine Learning ML Algorithm Chatbots 129

DataRobot Blog

JULY 13, 2022

DataRobot AIX 22 featured many of our customers and partners sharing their stories of growth and impact, including CVS Health, Phoenix Children’s, McLaren Racing, State of West Virginia, Google Cloud, and BCG. DataRobot is a category-defining company that has set an unmatched pace of innovation in the market.

Artificial Intelligence 105

Artificial Intelligence Artificial Intelligence Machine Learning Data Science 105

TensorFlow

FEBRUARY 3, 2023

After overindulging over the holidays, I resolve to eat healthier, exercise more, spend more time with friends and family, and prioritize my mental health…but they're not *New Year's* resolutions I swear! Model Maker is a low-code solution for customizing your MediaPipe Tasks to fit your app's needs.

Machine Learning 52

Machine Learning ML Categorization Python 52

John Snow Labs

APRIL 22, 2024

Regularly updated and built with cutting-edge algorithms, the Healthcare library aims to streamline information processing and empower healthcare professionals with deeper insights from unstructured medical data sources, such as electronic health records, clinical notes, and biomedical literature.

NLP 64

NLP Categorization Natural Language Processing BERT 64

Viso.ai

DECEMBER 18, 2023

Healthcare professionals can use artificial patient data while keeping the statistical properties of real-world health data. Access to synthetic data is valuable for developing effective artificial intelligence (AI) and machine learning (ML) models. Real-world data often poses significant challenges, including privacy, availability, and bias.

Computer Vision 52

Computer Vision Neural Network Auto-complete Data Scarcity 52

AWS Machine Learning Blog

SEPTEMBER 1, 2023

Nowadays, the majority of our customers is excited about large language models (LLMs) and thinking how generative AI could transform their business. In this post, we discuss how to operationalize generative AI applications using MLOps principles leading to foundation model operations (FMOps).

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Generative AI Prompt Engineer Prompt Engineering AI 103

Flipboard

JULY 31, 2023

In this post, we’ll show you the datasets you can use to build your machine learning projects. If you’re short on time, we’ll cut right to the chase here. We think the best datasets are available for free on Roboflow. After you create a free account, you’ll have access to the best machine learning datasets. Many call this software 2.0.

Machine Learning 104

Machine Learning Computer Vision Deep Learning Convolutional Neural Networks 104

Mlearning.ai

MAY 16, 2023

It is used to extract data from various sources, transform the data to fit a specific data model or schema, and then load the transformed data into a target system such as a data warehouse or a database. They have multiple data sources including electronic health records, claims data, and patient surveys.

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Explainability ETL Big Data Machine Learning 52

AWS Machine Learning Blog

SEPTEMBER 5, 2023

It plays an important role in identifying and safeguarding sensitive personal identifiable and health information (PII, PHI). We use the powerful generating capability of LLMs to generate the final decision including safe/unsafe labels and category type. This results in a poor user experience, high moderation costs, and brand risk.

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Mlearning.ai

FEBRUARY 24, 2024

Which AI technologies will be regulated and how? How will generative AI be dealt with? How bad is it? The final revisions are underway and the EU Parliament is expected to adopt the new EU AI Act in the coming weeks. What does this mean for the European AI scene? My article is about the following: What does the Act regulate?

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AI AI Generative AI ChatGPT 98

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). This enables enterprises to scale AI deployments at the edge, reducing the time and cost to deploy with faster response times. What are large language models?

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Large Language Models DevOps AI Modeling Automation 225

Topbots

MARCH 18, 2024

As we delve into the popular use cases for the custom GPTs, we uncover the breadth and depth of their impact across different sectors, showcasing their potential to further revolutionize how we engage with artificial intelligence in our daily lives and professional activities.

AI Tools 52

AI Tools Artificial Intelligence Artificial Intelligence Prompt Engineer 52

Unite.AI

JANUARY 15, 2024

Next, I'll show you how I instantly generated a spellchecker using Javascript and tested it directly on CodePal. In today's digital age, coding has become an essential skill across various industries. From app development to web design, coding is at the heart of many technological advancements. Generate code in 30+ languages!

Explainability 147

Explainability DevOps AI AI 147

Mlearning.ai

JUNE 2, 2023

To build modules How to See Like a Machine.ipynb Codes can be executed one by one. The answer is “Nature of the Task and how you will be approaching it.” Task can be modular , which means the code knows where exactly to fit and what to do. Task like training a Neural network fall under this category. It Depends.

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Python Neural Network Computer Vision Machine Learning 52

AWS Machine Learning Blog

NOVEMBER 14, 2023

In this post, we demonstrate how to fine-tune the Mistral 7B model using SageMaker JumpStart. Today, we are excited to announce the capability to fine-tune the Mistral 7B model using Amazon SageMaker JumpStart. This results in a need for further fine-tuning of these generative AI models over the use case-specific and domain-specific data.

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Natural Language Processing Python Machine Learning Algorithm 94

Snorkel AI

JUNE 22, 2023

In the last 12 years, how we build and how we do the work that we do has changed quite a few times. I’m joined by Brian Richardson, who’s an Associate Partner, and Senior Data Scientist at Quantum Black, and also leads our data-centric AI efforts across Quantum Black and McKinsey globally. The macro view will not be surprising.

Data Quality 52

Data Quality Automation Data Scientist ML 52

Snorkel AI

JUNE 22, 2023

In the last 12 years, how we build and how we do the work that we do has changed quite a few times. I’m joined by Brian Richardson, who’s an Associate Partner, and Senior Data Scientist at Quantum Black, and also leads our data-centric AI efforts across Quantum Black and McKinsey globally. The macro view will not be surprising.

Data Quality 52

Data Quality Automation Data Scientist ML 52

IBM Journey to AI blog

DECEMBER 20, 2023

Cloud computing services and management products fall into three primary categories: Software-as-a-Service (SaaS) offers applications hosted on a cloud server and distributed to end-users over the public internet. Yet navigating the complexities of building and managing a hybrid environment poses unique challenges.

DevOps 258

DevOps Machine Learning Automation Big Data 258

Heartbeat

MARCH 8, 2023

This article will look at how R can be used to execute text categorization tasks efficiently. Text Categorization Text categorization is a machine-learning approach that divides the text into specific categories based on its content. The goal is to automatically classify documents based on the textual information contained within them.

Machine Learning 52

Machine Learning Algorithm Categorization NLP 52

The MLOps Blog

JANUARY 23, 2023

They tackle the ugly problem in the canonical MLOps movement: How do all those MLOps stack components actually relate to each other and work together? In this article, I share how our reality as the MLOps tooling company and my personal views on MLOps agree (and disagree) with it. Some are my 3–4 year bets. Came to ML from software.

DevOps 59

DevOps Metadata Software Engineer Data Scientist 59

ODSC - Open Data Science

OCTOBER 27, 2023

In this article, I briefly discuss the various phases of IDP and how generative AI is being utilized to augment existing IDP workloads or develop new IDP workloads. The following diagram is how we visualize these IDP phases. It often involves manual labor taking time away from critical activities.

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IDP LLM Large Language Models AI 98

Cold Takes

FEBRUARY 10, 2023

I think it’s bad to rush into a mediocre fit with one of these jobs, and better (if necessary) to stay out of AI-related jobs while skilling up and waiting for a great fit. Click lower right to download or find on Apple Podcasts, Spotify, Stitcher, etc. What can you do to help things go well instead of poorly?

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AI AI Neural Network Deep Learning 40

AI Impacts

DECEMBER 22, 2022

An alternative or complementary kind of response is to try to avert such machines being built at all, at least while the degree of their apocalyptic tendencies is ambiguous. An alternative or complementary kind of response is to try to avert such machines being built at all, at least while the degree of their apocalyptic tendencies is ambiguous.

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AI AI AI Researcher AI Research 130

The MLOps Blog

OCTOBER 3, 2023

How to transition from data analytics to MLOps engineering Piotr: Miki, you’ve been a data scientist, right? How did you manage to jump from a more analytical, scientific type of role to a more engineering one? How did you manage to jump from a more analytical, scientific type of role to a more engineering one?

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ML Data Scientist Machine Learning Data Science 52

Unite.AI

MAY 17, 2024

Could you discuss these early days of launching your first company, and how you eventually exited? Yet, even with the strong customer demand in this category, the customer journey has not been touched by AI. How does Alberni, your AI agent, revolutionize the way HR tasks are traditionally managed?

Automation 246

Automation Conversational AI AI AI 246

The MLOps Blog

JUNE 27, 2023

How to evaluate MLOps tools and platforms Like every software solution, evaluating MLOps (Machine Learning Operations) tools and platforms can be a complex task as it requires consideration of varying factors. Open-source tools have gained significant traction due to their flexibility, community support, and adaptability to various workflows.

Machine Learning 134

Machine Learning Metadata Data Quality Data Scientist 134

Viso.ai

MARCH 11, 2024

Then, the Convolutional Neural Network (CNN) classified these regions into different object categories. How Does YOLOX Work? YOLOX (You Only Look Once) is a high-performance object detection model belonging to the YOLO family. YOLOX brings with it an anchor-free design, and decoupled head architecture to the YOLO family.

Explainability 52

Explainability Convolutional Neural Networks Neural Network Computer Vision 52

Unite.AI

MAY 9, 2024

These modifications, which can have significant implications for health and disease when disrupted, can now be studied with remarkable accuracy. For certain crucial categories of interactions, AlphaFold 3 has even doubled the prediction accuracy compared to traditional methods.

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AI Modeling AI AI Machine Learning 246

The MLOps Blog

MAY 9, 2023

One of the most prevalent complaints we hear from ML engineers in the community is how costly and error-prone it is to manually go through the ML workflow of building and deploying models. Building end-to-end machine learning pipelines lets ML engineers build once, rerun, and reuse many times. If all goes well, of course ?

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ML Machine Learning Metadata Automation 98

Topbots

APRIL 28, 2023

Note: These experiments aim not to measure how creative the models are, but rather to measure the level of creative process present in the model generations. Rather, I aim to show how the models respond to particular measures of creative processes. I use both a subjective and objective lens to understand the behavior of these models.

Large Language Models 52

Large Language Models Natural Language Processing Robotics Explainability 52

Google Research AI blog

JANUARY 24, 2023

These technological advances require that we are thoughtful and intentional in how they are developed and deployed. For natural language tasks, we similarly investigated how different data distributions improve generalization across different groups and how ensembles and pre-trained models can help.

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Responsible AI AI AI ML 99

Cold Takes

JANUARY 5, 2023

I’m looking for ways the future could look durably and dramatically different depending on how we navigate the development of transformative AI - such that doing the right things ahead of time could make a big, lasting difference. Click lower right to download or find on Apple Podcasts, Spotify, Stitcher, etc.

AI 52

AI AI AI Developer AI Development 52

AWS Machine Learning Blog

JANUARY 9, 2023

There is no one-size-fits-all approach, and it’s important for ML practitioners to look for tried-and-proven methods to address recurring ML hosting challenges. Machine learning (ML) applications are complex to deploy and often require the ability to hyper-scale, and have ultra-low latency requirements and stringent cost budgets.

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Marktechpost

MAY 2, 2024

It mentions how clear duties must be followed by high-risk AI systems in order to reduce possible harm, maintain openness, and provide human oversight. Numerous initiatives are influencing the ethical use of AI to prioritize human rights and innovation. Here are some of the top AI governance laws and frameworks.

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