IBM Journey to AI blog

APRIL 10, 2024

By 2026, approximately 80% of software engineering organizations will establish platform teams as internal providers of reusable services, components and tools for application delivery. Developer Experience: A truism is emerging in the software industry: good developer experience leads to great customer experience.

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Iguazio

MARCH 31, 2024

In this blog post, we dive deep into these use cases and their business and operational impact. For more details on this topic, you can watch the webinar this blog post is based on. Distinctive - Novel capabilities that leverage complex data orchestration and advanced engineering. This also helps with agent ramp-up.

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Heartbeat

FEBRUARY 13, 2023

Kangas, developed by the team at Comet , is an open source tool that allows data developers to load, sort, group, and visualize millions of images at once without the risk of crashing their notebooks. Developed by Comet engineers, Kangas is designed to make it easy for data developers to discover, analyze and display massive datasets.

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AWS Machine Learning Blog

MAY 5, 2023

Voxel51 is the company behind FiftyOne, the open-source toolkit for building high-quality datasets and computer vision models. To create this app, they need a high-quality dataset containing clothing images, labeled with different categories. A retail company is building a mobile app to help customers buy clothes.

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AWS Machine Learning Blog

SEPTEMBER 1, 2023

Our approach applies to both open-source and proprietary models equally. 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.

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Iguazio

AUGUST 3, 2023

For data scientists tasked with building and training machine learning models for retailers, open and free retail datasets are an important starting point. This blog post is here to help. Here are 13 excellent open datasets and data sources for retailer data for machine learning. Get the dataset here.

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Iguazio

FEBRUARY 20, 2024

The introduction of ChatGPT, Microsoft Copilot, Midjourney, Stable Diffusion and many more incredible tools have opened up new possibilities we couldn’t have imagined 18 months ago. Unconstrained, long, open-ended generation that may expose harmful or biased content to users, like legal document creation. View the entire webinar here.

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AWS Machine Learning Blog

FEBRUARY 13, 2024

Let’s demystify this using the following personas and a real-world analogy: Data and ML engineers (owners and producers) – They lay the groundwork by feeding data into the feature store Data scientists (consumers) – They extract and utilize this data to craft their models Data engineers serve as architects sketching the initial blueprint.

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Hacker News

JULY 12, 2023

This post is part of a short series about my experience in the VP of Engineering role at Honeycomb. In February of 2020, I was promoted from Director of Engineering to Honeycomb’s first VP of Engineering. Not the plan I didn’t join Honeycomb with the goal of becoming an engineering executive.

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Smart Data Collective

SEPTEMBER 23, 2020

This blog will reveal or show the difference between the data warehouse and the data lake. On the other hand, data lakes store from an extensive array of sources like real-time social media streams, Internet of Things devices, web app transactions, and user data. Engineers make use of data lakes in storing incoming data.

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IBM Journey to AI blog

MARCH 4, 2024

While many organizations have implemented AI, the need to keep a competitive edge and foster business growth demands new approaches: simultaneously evolving AI strategies, showcasing their value, enhancing risk postures and adopting new engineering capabilities. How can you master prompt engineering? Do you use gen AI out of the box?

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Heartbeat

SEPTEMBER 18, 2023

Data scientists and ML engineers rely heavily on these platforms because they provide the necessary resources to tackle large-scale and challenging ML problems. This key feature enables data scientists and engineers to work seamlessly with their preferred ML tools and frameworks, ensuring a familiar and efficient working environment.

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Google Research AI blog

JUNE 6, 2023

We fine-tuned a large language model to proactively suggest relevant visuals in open-vocabulary conversations using a dataset we curated for this purpose. We open sourced Visual Captions as part of the ARChat project, which is designed for rapid prototyping of augmented communication with real-time transcription. dataset.

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AWS Machine Learning Blog

NOVEMBER 15, 2023

Prompt engineering has become an essential skill for anyone working with large language models (LLMs) to generate high-quality and relevant texts. Although text prompt engineering has been widely discussed, visual prompt engineering is an emerging field that requires attention.

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Alation

DECEMBER 15, 2022

Source: Squarespace. As I reflected on this topic, it occurred to me that software categories should be no different. How Do You Determine the GOAT for a Software Category? But how do you determine the GOAT for a software category? Muhammad Ali for boxing. Serena Williams for tennis. Wayne Gretzy for hockey.

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AWS Machine Learning Blog

JANUARY 26, 2024

The goal of this post is to empower AI and machine learning (ML) engineers, data scientists, solutions architects, security teams, and other stakeholders to have a common mental model and framework to apply security best practices, allowing AI/ML teams to move fast without trading off security for speed.

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Heartbeat

MARCH 6, 2023

Source: [link] Computer vision is an interesting field in machine learning as it helps computers understand what they see. Image classification is a computer vision task that allows algorithms to understand an image’s contents and assign one or more categories to the image. Sign up for a free account to use Comet ML’s platform.

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Google Research AI blog

DECEMBER 13, 2022

Data collection is particularly expensive and challenging for robotics because dataset curation requires engineering-heavy autonomous operation , or demonstrations collected using human teleoperations. Finally, we’re open-sourcing the RT-1 code , and hope it will provide a valuable resource for future research on scaling up robot learning.

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DagsHub

AUGUST 15, 2023

Most of the time, tooling for an active learning pipeline needs to be either custom written, or cobbled together from several different open source tools. With the release of Data Engine, DagsHub has made it easier to create an active learning pipeline. The final imports are the DagsHub client library and the Data Engine.

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Heartbeat

FEBRUARY 15, 2023

Source: [link] Text classification is an interesting application of natural language processing. It is a supervised learning methodology that predicts if a piece of text belongs to one category or the other. Open R Studio and in the console, type in the following commands to install the dependencies needed.

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Data Science Dojo

AUGUST 22, 2023

Large language models, which are a prominent category of transformer models, have proven to be exceptionally versatile. Content creation: LLMs can be used to create marketing content, such as blog posts, articles, and social media posts. These abilities are harnessed by drawing upon extensive knowledge extracted from massive datasets.

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AWS Machine Learning Blog

NOVEMBER 7, 2023

By sourcing context-relevant data, the model can provide informed, up-to-date responses tailored to your use case. This integration provides precise and context-aware answers to complex queries by drawing from a diverse range of sources. The model then skillfully integrates this outside information into its generated text.

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Heartbeat

JANUARY 5, 2024

There have been great leaps in the LLMs space, from the introduction of Google’s “sentient” LaMDA chatbot, BLOOM, the first high-performance and open-source LLM, and the release of next-generation GPT-3.5 We have seen exploding interest in LLMs and in a broader discipline, Generative AI. models by OpenAI.

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AWS Machine Learning Blog

OCTOBER 18, 2023

It is already trained on tens of millions of images across many categories. Instead of thousands of images, you can upload a small set of training images (typically a few hundred images or less per category) that are specific to your use case. CodeBuild compiles source code, runs tests, and produces packages that are ready to deploy.

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Heartbeat

APRIL 11, 2023

Applications for image and video analysis, such as x-ray results, can be created using the open-source computer vision and machine learning software library known as OpenCV (Open Source Computer Vision). Open CV is an open-source library for carrying out computer vision, machine learning, and image processing.

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Heartbeat

APRIL 17, 2023

Classification: Each phrase is then classified into specific named entity categories, such as a person, organization, location, date, or numerical expression. The output is a list of named entities and their corresponding categories. SpaCy supports several categories of named entities, including PERSON, ORG, GPE, DATE, TIME, and MONE.

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Pickl AI

AUGUST 1, 2023

Here are seven benefits of text mining: Information Extraction Text mining enables the extraction of relevant information from unstructured text sources such as documents, social media posts, customer feedback, and more. Text Classification This technique is helpful in the classification of large volumes of text into predefined categories.

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DrivenData Labs

MARCH 30, 2023

Phase Prize Totals Phase 1: Concept Paper $55,000 Phase 2: Solution Development $360,000 Phase 3: Red Teaming $120,000 Open Source $140,000 Total $675,000 Read on for summaries of what we saw in Phase 2 and Phase 3 of the challenge, or skip ahead to meet the winning teams. What motivated you to participate? :

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Mlearning.ai

MARCH 19, 2023

Because of its wide range of applications in disciplines such as information retrieval, recommendation systems, and search engine optimization, this technique’s popularity has surged in recent years. In this blog, we will look at Learning to Rank, as well as evaluation metrics and optimise functions.

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AWS Machine Learning Blog

MARCH 22, 2023

Rekognition Custom Labels builds off of the existing capabilities of Amazon Rekognition, which is already trained on tens of millions of images across many categories. The workflow allows application developers and ML engineers to automate the custom label classification steps for any computer vision use case.

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Pickl AI

FEBRUARY 8, 2023

ChatGPT is an open-source Artificial Intelligence tool by OpenAI that works as a; language Chatbot. In the following blog, let’s look at how ChatGPT changes human function. For example, data visualisation tools can use ChatGPT to automatically generate labels for a bar chart, describing the categories and values represented.

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Flipboard

JULY 31, 2023

Helping You Find the Best Datasets In this blog post, we aim to empower both seasoned and novice data scientists by providing a comprehensive guide to the top machine learning datasets available in 2023. Image classification involves assigning a label to an image from a predetermined set of categories.

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Heartbeat

JANUARY 30, 2023

from comet_ml import Experiment comet_string = """[comet] api_key=K1fGCe5YL4XrwI01qoCSNvY3R project_name=Sentiment Analyis workspace=olujerry """ with open(' comet.config', 'w') as f: f.write(comet_string) Step 2: Import and install all libraries and dependencies. Have you tried Comet? value_counts().plot(kind

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IBM Journey to AI blog

JULY 12, 2023

What if your top three engineers all quit at the same time? Here’s an example of a contingency plan that would help them prepare to face this problem: Assess the severity and likelihood of the risk: A recent study by Open Gear showed that only 9% of global organizations avoid network outages in an average quarter.

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AWS Machine Learning Blog

NOVEMBER 30, 2023

With FM evaluations, we are introducing FMEval , an open-source LLM evaluation library, designed to provide data scientists and ML engineers with a code-first experience to evaluate LLMs for quality and responsibility while selecting or adapting LLMs to specific use cases. What is FMEval? How can you get started?

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Heartbeat

FEBRUARY 2, 2024

This opens up new possibilities for sophisticated interactions between machines and humans, heralding a transformative era in the field of artificial intelligence. incorporates images sourced from the widely used COCO (Common Objects in Context) dataset. Open Access. An extension of its predecessor, VQA v2.0 A., & Akata, Z.

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Smart Data Collective

SEPTEMBER 8, 2021

The ETL process is defined as the movement of data from its source to destination storage (typically a Data Warehouse) for future use in reports and analyzes. The data is initially extracted from a vast array of sources before transforming and converting it to a specific format based on business requirements.

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