Towards AI

JANUARY 11, 2024

Author(s): Towards AI Editorial Team Originally published on Towards AI. This week, we are excited to announce our AI Tutor chatbot with full access to 100+ lessons about RAG and LLMs from all three courses we’ve built and thousands of additional pages of helpful supporting tutorials and documentation. Let’s get right into it.

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AWS Machine Learning Blog

APRIL 18, 2024

We are excited to announce that Slack, a Salesforce company, has collaborated with Amazon SageMaker JumpStart to power Slack AI’s initial search and summarization features and provide safeguards for Slack to use large language models (LLMs) more securely. None of your data is used to train the underlying models.

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AWS Machine Learning Blog

JANUARY 5, 2024

This post was written in collaboration with Bhajandeep Singh and Ajay Vishwakarma from Wipro’s AWS AI/ML Practice. Many organizations have been using a combination of on-premises and open source data science solutions to create and manage machine learning (ML) models.

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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. What is MLOps?

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AWS Machine Learning Blog

NOVEMBER 16, 2023

This is a joint blog with AWS and Philips. Amazon SageMaker provides purpose-built tools for machine learning operations (MLOps) to help automate and standardize processes across the ML lifecycle. In this post, we describe how Philips partnered with AWS to develop AI ToolSuite—a scalable, secure, and compliant ML platform on SageMaker.

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AWS Machine Learning Blog

MAY 23, 2023

This is a guest blog post co-written with Vik Pant and Kyle Bassett from PwC. With organizations increasingly investing in machine learning (ML), ML adoption has become an integral part of business transformation strategies. Many organizations start their journey into the world of ML with a model-centric viewpoint.

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The MLOps Blog

MARCH 20, 2023

Long-term ML project involves developing and sustaining applications or systems that leverage machine learning models, algorithms, and techniques. An example of a long-term ML project will be a bank fraud detection system powered by ML models and algorithms for pattern recognition. 2 Ensuring and maintaining high-quality data.

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Flipboard

JUNE 11, 2023

SAIF draws inspiration from security best practices in software development and incorporates an understanding of security risks specific to AI systems. SAIF addresses risks such as model theft, data poisoning, malicious input injection, and confidential information extraction from training data.

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AWS Machine Learning Blog

APRIL 13, 2023

With real-time code recommendations from CodeWhisperer, you can stay focused in the IDE and finish your coding tasks faster. In this post, we illustrate how Accenture uses CodeWhisperer in practice to improve developer productivity. The Velocity team was looking for ways to improve developer productivity.

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IBM Journey to AI blog

APRIL 18, 2024

While AGI remains theoretical, organizations can take proactive steps to prepare for its arrival by building a robust data infrastructure and fostering a collaborative environment where humans and AI work together seamlessly. While the progress is exciting, the leap from weak AI to true AGI is a significant challenge.

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ML @ CMU

MARCH 31, 2023

This blog post discusses the effectiveness of black-box model explanations in aiding end users to make decisions. Our work further motivates novel directions for developing and evaluating tools to support human-ML interactions. How do you rigorously evaluate explanation methods?

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Heartbeat

JANUARY 3, 2024

Photo by Guy Bowden on Unsplash Weather forecasting is our trusty crystal ball, keeping us safe from storms, floods, and heat waves. The 21st century has become a pivotal moment for humanity that demands innovation, collaboration, and transformative action. But can ML also be the game-changer in our fight against climate change?

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AWS Machine Learning Blog

SEPTEMBER 1, 2023

This applies to customers that use them out of the box, create foundation models from scratch, or fine-tune them. To achieve this, a combination of teams and personas need to collaborate, as illustrated in the following figure. These data owners are focused on providing access to their data to multiple business units or teams.

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AWS Machine Learning Blog

FEBRUARY 22, 2023

In this post, we discuss how Boomi used the bring-your-own-container (BYOC) approach to develop a new AI/ML enabled solution for their customers to tackle the “blank canvas” problem. Boomi’s ML and data engineering teams needed the solution to be deployed quickly, in a repeatable and consistent way, at scale.

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Towards AI

JUNE 5, 2023

Last Updated on June 14, 2023 by Editorial Team Author(s): Anirudh Mehta Originally published on Towards AI. In May 2021, Khalid Salama, Jarek Kazmierczak, and Donna Schut from Google published a white paper titled “Practitioners Guide to MLOps”. There are hundreds of blogs written on the same topic. Source: Image by the author.

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Heartbeat

JUNE 12, 2023

Feedback Monitoring gathers feedback from users and stakeholders to ensure the model meets their needs and expectations. Many tools and techniques are available for ML model monitoring in production, such as automated monitoring systems, dashboarding and visualization, and alerts and notifications. The MLOps difference?

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Heartbeat

OCTOBER 30, 2023

Ensuring Long-Term Performance and Adaptability of Deployed Models Source: [link] Introduction When working on any machine learning problem, data scientists and machine learning engineers usually spend a lot of time on data gathering , efficient data preprocessing , and modeling to build the best model for the use case.

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AWS Machine Learning Blog

NOVEMBER 22, 2023

For decades, Amazon has pioneered and innovated machine learning (ML), bringing delightful experiences to its customers. From the earliest days, Amazon has used ML for various use cases such as book recommendations, search, and fraud detection.

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AWS Machine Learning Blog

FEBRUARY 24, 2023

AWS recently released Amazon SageMaker geospatial capabilities to provide you with satellite imagery and geospatial state-of-the-art machine learning (ML) models, reducing barriers for these types of use cases. For more information, refer to Preview: Use Amazon SageMaker to Build, Train, and Deploy ML Models Using Geospatial Data.

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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. Disclaimer: This article focuses on the setup of mostly production ML teams at Brainly.

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AWS Machine Learning Blog

DECEMBER 5, 2023

This post is written in collaboration with Balaji Chandrasekaran, Jennifer Cwagenberg and Andrew Sansom and Eiman Ebrahimi from Protopia AI. The transform that is created from the SDK can be deployed locally, in a hybrid setup, or completely on the cloud.

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Heartbeat

FEBRUARY 29, 2024

Enterprise Talk In 1972, introducing the C programming language marked a watershed moment for the software industry, elevating us from the depths of assembly language and paving the way for more expressive and powerful languages to emerge. Cross-functional teams often include product managers, UX designers, and multiple software engineers.

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Pickl AI

JANUARY 23, 2024

Job roles span from Data Analyst to Chief Data Officer, each contributing significantly to organisational success. This makes it one of the best Data Analytics courses available. With the Business Analytics market poised to reach new heights, from USD 43.9 This clearly reflects in the rising MBA in Data Analytics salary trends.

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Google Research AI blog

NOVEMBER 17, 2022

However, knowledge about datasets, including use and implementations, is often distributed across teams, individuals, and even time. However, knowledge about datasets, including use and implementations, is often distributed across teams, individuals, and even time.

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PyImageSearch

DECEMBER 11, 2023

The recount of past sprints was a great opportunity for participants to showcase their work and projects and get feedback from other attendees. The recount of past sprints was a great opportunity for participants to showcase their work and projects and get feedback from other attendees.

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ML @ CMU

MARCH 30, 2023

This blog post discusses the effectiveness of black-box model explanations in aiding end users to make decisions. Our work further motivates novel directions for developing and evaluating tools to support human-ML interactions. How do you rigorously evaluate explanation methods?

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AWS Machine Learning Blog

JANUARY 17, 2023

Amazon SageMaker Studio is a fully integrated development environment (IDE) for machine learning (ML) partly based on JupyterLab 3. Studio provides a web-based interface to interactively perform ML development tasks required to prepare data and build, train, and deploy ML models.

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Google Research AI blog

JUNE 14, 2023

To help with this, Google Maps launched Immersive View , which uses advances in machine learning (ML) and computer vision to fuse billions of Street View and aerial images to create a rich, digital model of the world. To obtain the best possible reconstruction quality, every surface should be observed from multiple different directions.

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Pickl AI

JULY 25, 2023

The following blog is a complete guide on Algorithmic Bias- What is it and How to Avoid it?, helping you learn about bias in ML. 4. Implicit Assumptions: Biases can also stem from implicit assumptions made during the design and implementation of algorithms, which may not be immediately apparent. What is Algorithmic Bias?

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Defined.ai blog

AUGUST 30, 2023

Through the relentless evolution of Natural Language Processing (NLP) in machine learning, the barriers between human and machine communication are not just blurring—they’re being dismantled, ushering in a new era of collaboration and understanding. Here’s how: Pattern Recognition : ML algorithms excel at recognizing patterns.

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Pickl AI

APRIL 10, 2023

So, if you are eyeing your career in the data domain, this blog will take you through some of the best colleges for Data Science in India. The amount increases with experience and varies from industry to industry. The course is offered in collaboration with IBM, thus making it one of the best-rated courses for Data Science.

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AWS Machine Learning Blog

AUGUST 16, 2023

This is a guest blog post co-written with Ben Veasey, Jeremy Anderson, Jordan Knight, and June Li from Travelers. Training machine learning (ML) models to interpret this data, however, is bottlenecked by costly and time-consuming human annotation efforts. We build on the code provided in the DINO repository. during training.

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AWS Machine Learning Blog

APRIL 6, 2023

& AWS Machine Learning Solutions Lab (MLSL) Machine learning (ML) is being used across a wide range of industries to extract actionable insights from data to streamline processes and improve revenue generation. Furthermore, the NXP team is also interested in predicting the product lifecycle of newly introduced products.

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The MLOps Blog

MARCH 15, 2023

It’s clear that the need for efficient and effective MLOps and CI/CD practices is becoming increasingly vital. We’ll delve into the MLOps practices and strategies we tried and implemented across some of our projects. Costs: Oftentimes, cost is the most important aspect of any ML model deployment.

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AWS Machine Learning Blog

NOVEMBER 9, 2023

Building out a machine learning operations (MLOps) platform in the rapidly evolving landscape of artificial intelligence (AI) and machine learning (ML) for organizations is essential for seamlessly bridging the gap between data science experimentation and deployment while meeting the requirements around model performance, security, and compliance.

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AWS Machine Learning Blog

MAY 16, 2023

JumpStart is the machine learning (ML) hub of Amazon SageMaker that provides access to foundation models in addition to built-in algorithms and end-to-end solution templates to help you quickly get started with ML. SageMaker provides a curated list of models that you can choose from on the SageMaker console.

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The MLOps Blog

MARCH 15, 2023

Automating myriad steps associated with pipeline data processing, helps you convert the data from its raw shape and format to a meaningful set of information that is used to drive business decisions. In this post, you will learn about the 10 best data pipeline tools, their pros, cons, and pricing.

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