Federated Learning

Anthropic AI Releases Claude 3.5: A New AI Model that Surpasses GPT-4o on Multiple Benchmarks While Being 2x Faster than Claude 3 Opus

AI Shorts
Anthropic AI has launched Claude 3.5 Sonnet, marking the first release in its new Claude 3.5 model family. This latest iteration of Claude brings significant advancements in AI capabilities, setting a new benchmark in the industry...

StreamSpeech: A Direct Simul-S2ST Speech-to-Speech Translation Model that Jointly Learns Translation and Simultaneous Policy in a Unified Framework of Multi-Task Learning

AI Paper Summary
Large Language Models (LLMs) have gained significant attention in the field of simultaneous speech-to-speech translation (SimulS2ST). This technology has become crucial for low-latency communication in various scenarios, such as international conferences, live broadcasts, and online subtitles....

University of Michigan Researchers Open-Source ‘FedScale’: a Federated Learning (FL) Benchmarking Suite with Realistic Datasets and a Scalable Runtime to Enable Reproducible FL Research...

AI Paper Summary
Federated learning (FL) is a new machine learning (ML) environment in which a logically centralized coordinator orchestrates numerous dispersed clients (e.g., cellphones or laptops)...

Google AI and Tel Aviv Researchers Introduce FriendlyCore: A Machine Learning Framework For Computing Differentially Private Aggregations

AI Paper Summary
Data analysis revolves around the central goal of aggregating metrics. The aggregation should be conducted in secret when the data points match personally identifiable...

In A New AI Research, Federated Learning Enables Big Data For Rare Cancer Boundary Detection

AI Paper Summary
The number of primary observations produced by healthcare systems has dramatically increased due to recent technological developments and a shift in patient culture from...

IOM Releases Its Second Synthetic Dataset From Trafficking Victim Case Records Generated With Differential Privacy And AI From Microsoft

AI Shorts
Researchers at Microsoft are committed to researching ways technology may help the world's most marginalized peoples improve their human rights situations. Their expertise spans...

Researchers Developed SmoothNets For Optimizing Convolutional Neural Network (CNN) Architecture Design For Differentially Private Deep Learning

AI Paper Summary
Differential privacy (DP) is used in machine learning to preserve the confidentiality of the information that forms the dataset. The most used algorithm to...

Researchers Analyze the Current Findings on Confidential Computing-Assisted Machine Learning ML Security and Privacy Techniques Along with the Limitations in Existing Trusted Execution Environment...

AI Paper Summary
The evolution of machine learning (ML) offers broader possibilities of use. However, wide applications also increase the risks of large attack surface on ML's...

3 Machine Learning Business Challenges Rooted in Data Sensitivity 

AI Governance
Machine Learning (ML) and, in particular, Deep Learning is drastically changing the way we conduct business as now data can be utilized to guide...

Researchers created a Novel Framework called ‘FedD3’ for Federated Learning in Resource-Constrained Edge Environments via Decentralized Dataset Distillation

AI Paper Summary
For collaborative learning in large-scale distributed systems with a sizable number of networked clients, such as smartphones, connected cars, or edge devices, federated learning...

Researchers At Amazon Propose ‘AdaMix’, An Adaptive Differentially Private Algorithm For Training Deep Neural Network Classifiers Using Both Private And Public Image Data

AI Paper Summary
It is crucial to preserve privacy by restricting the amount of data that may be gathered about each training sample when training a deep...

Stanford AI Researchers Propose ‘FOCUS’: A Foundation Model Which Aims to Achieve Perfect Secrecy For Personal Tasks

AI Paper Summary
Machine learning holds the possibility of assisting people with personal activities. Personal jobs range from well-known activities like subject categorization over personal correspondence and...

Researchers From China Introduce ‘FedPerGNN’: A New Federated Graph Neural Network (GNN) Framework For Both Effective And Privacy-Preserving Personalization

AI Ethics
This Article is written as a summay by Marktechpost Staff based on the paper 'A federated graph neural network framework for privacy-preserving personalization'. All...

Borealis AI Research Introduces fAux:  A New Approach To Test Individual Fairness via Gradient Alignment

AI Shorts
Machine learning models are trained on massive datasets with hundreds of thousands, if not billions, of parameters. However, how these models translate the input...
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Galileo Introduces Luna: An Evaluation Foundation Model to Catch Language Model Hallucinations with High...

Asif Razzaq - 0
The Galileo Luna represents a significant advancement in language model evaluation. It is specifically designed to address the prevalent issue of hallucinations in large...

Yandex Introduces YaFSDP: An Open-Source AI Tool that Promises to Revolutionize LLM Training by...

Asif Razzaq - 0
Developing large language models requires substantial investments in time and GPU resources, translating directly into high costs. The larger the model, the more pronounced...

Gretel AI Releases a New Multilingual Synthetic Financial Dataset on HuggingFace 🤗 for AI...

Asif Razzaq - 0
Detecting personally identifiable information PII in documents involves navigating various regulations, such as the EU’s General Data Protection Regulation (GDPR) and various U.S. financial...

Snowflake AI Research Team Unveils Arctic: An Open-Source Enterprise-Grade Large Language Model (LLM) with...

Asif Razzaq - 0
Snowflake AI Research has launched the Arctic, a cutting-edge open-source large language model (LLM) specifically designed for enterprise AI applications, setting a new standard...

Google DeepMind Releases RecurrentGemma: One of the Strongest 2B-Parameter Open Language Models Designed for...

Adnan Hassan - 0
Language models are the backbone of modern artificial intelligence systems, enabling machines to understand and generate human-like text. These models, which process and predict...

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