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Forecasting Scores for Sustainable Development Goals (SDG) by 2030: A Methodology Using Machine Learning, ARIMAX, and Linear Regression Techniques

AI Paper Summary, Editors Pick, Staff, Tech News, UncategorizedJuly 25, 202432Views0Likes0Comments
The United Nations' Sustainable Development Goals (SDGs) aim to eradicate poverty, protect the environment, combat climate change, and bolster global peace and prosperity by the year 2030. Despite extensive research, additional work is required to accurately forecast SDG scores, which measure progress towards these objectives. By employing ARIMAX and Linear Regression machine learning models which…

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In order to improve an AI assistant, initiate by imitating the unpredictable actions of humans.

Algorithms, Artificial Intelligence, Computer modeling, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Electrical Engineering & Computer Science (eecs), Human-computer interaction, Machine learning, MIT Schwarzman College of Computing, National Science Foundation (NSF), Research, School of Engineering, UncategorizedJuly 25, 202428Views0Likes0Comments
Researchers from MIT and the University of Washington have developed a method to model the behaviour of an agent, including its computational limitations, predicting future behaviours by examining prior actions. The method applies to both humans and AI, and has a wide range of potential applications, including predicting navigation goals from past routes and forecasting…

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This miniature microchip can protect user information while facilitating effective computing on a mobile phone.

Artificial Intelligence, Computer science and technology, Cybersecurity, Data, Electrical Engineering & Computer Science (eecs), Electronics, Machine learning, MIT Schwarzman College of Computing, MIT-IBM Watson AI Lab, National Science Foundation (NSF), Privacy, Research, School of Engineering, UncategorizedJuly 25, 202431Views0Likes0Comments
Health-monitoring apps that assist people in managing chronic diseases or tracking fitness goals work with the help of large machine-learning models, which are often shuttled between a user's smartphone and a central memory server. This process can slow down the app's performance and drain the energy of the device. While machine-learning accelerators can help to…

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Enhancing the performance of Salesforce Einstein’s code generation model using Amazon SageMaker

Amazon Machine Learning, Amazon SageMaker, Amazon SageMaker JumpStart, Customer Solutions, Experience-Based Acceleration, Generative AI, UncategorizedJuly 25, 202434Views0Likes0Comments
This is a joint collaboration post between Salesforce and AWS, in which they discuss how the Salesforce Einstein AI Platform team has utilized Amazon SageMaker to enhance the efficiency and performance of their code generation LLM (Large Language Models) features, known as CodeGen. Salesforce, a cloud-based software company, offers customer relationship management (CRM) software applications focused…

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Experimenting with Large-scale Machine Learning using Amazon SageMaker Pipelines and MLflow

Advanced (300), Amazon SageMaker, Amazon SageMaker Studio, Generative AI, Technical How-to, Thought Leadership, UncategorizedJuly 25, 202434Views0Likes0Comments
This post explains how large language models (LLMs) can be fine-tuned to better adapt to specific domains or tasks, using Amazon SageMaker and MLflow. When working with LLMs, customers may have varied requirements such as choosing a suitable pre-trained foundation model (FM) or customizing an existing model for a specific task. Using Amazon SageMaker with…

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Transforming the Established Norms: Trade Association Advertising Techniques for the Digital Age

actionable insights, blog, industry association marketing, industry associations, marketing strategies, member advocacy, membership, UncategorizedJuly 24, 202431Views0Likes0Comments
The traditional methods of member newsletters and website updates are becoming obsolete in business-to-business (B2B) industry association marketing as more advanced tactics take their place. The updated strategies focus on data utilization, fostering authentic member engagement, and positioning the association as a leader in its field. The key to success for industry associations lies in…

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Researchers at Apple suggest LazyLLM: a unique AI strategy for productive LLM inference, specifically in situations with extended context.

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Language Model, Large Language Model, Staff, Tech News, Technology, UncategorizedJuly 24, 202434Views0Likes0Comments
Large Language Models (LLMs) have improved significantly, but challenges persist, particularly in the prefilling stage. This is because the cost of computing attention increases with the number of tokens in the prompts, leading to a slow time-to-first-token (TTFT). As such, optimizing TTFT is crucial for efficient LLM inference. Various methods have been proposed to improve…

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