#machine-learning

#machine-learning

Tripadvisor's personalization engine uses machine learning models and ScyllaDB on AWS to process over 2 billion requests daily, providing real-time recommendations to users.

Researchers discovered over 86,000 hidden earthquakes at Yellowstone between 2008 and 2022, marking a significant increase compared to previous detections, prompting concerns of impending eruption.

At Deep Film Inc., you'll transform multimodal diffusion and transformer models into production-ready systems, mastering quantization and pruning to make them leaner and faster.

Despite impressive capabilities, large language models have yet to produce a genuine breakthrough. They lack fundamental aspects of human thought, remaining static and unable to learn from experience.

CodeRabbit's foundational capability is its continuous, context-aware pull request (PR) analysis. Once a PR is opened, CodeRabbit launches a full AI-powered review, surfacing actionable feedback without human involvement. The experience blends static review conventions with natural language explanations and inline suggestions.

Kriti Goyal leveraged her master's degree to advance her AI career in the US, pitching projects during her internship that secured a full-time offer.

The attention mechanism used in the AMIL and AdMIL models leads to attention scores that may not accurately represent tumors or their contributions to predictions.

AI-based vision systems can swiftly identify maintenance issues, such as battery leaks, damaged metal components, and patchy paintwork.

Our Loanbridge system is bringing that same methodology to our operations team on the origination side that we're using on the servicing side, and then we've been working incredibly hard, principally with our retail sales force, both our NFS team and our call center team, to take their workflows and standardize them.

The proposed llms.txt standard would guide large language models, helping e-commerce sites share product info directly with AI and shoppers.

The results demonstrate how targeted campaigns, effective publisher selection, and real-time optimization can drive scalable growth for crypto brands.

The system combines a graphene-derived material with machine learning to detect salty, bitter, sweet, and sour flavors, potentially restoring taste for those with neurological conditions.

The model's quality improved greatly from v2 to v4. Although when doing long text TTS, errors are unavoidable, it is good enough for my use case.

AI Runners enable serving of custom models through the Clarifai's publicly accessible API, allowing integration into any application.

The research proposes that the creativity of diffusion models stems from a deterministic process linked to how they employ the denoising mechanism to create images.

Developers are starting to look beyond AI-generated code and are asking a bigger question: can these tools help make sense of what's already written?

The copies used to train specific LLMs were justified as fair use. Every factor but the nature of the copyrighted work favors this result. The technology at issue was among the most transformative many of us will see in our lifetimes.

"The need for secure data collaboration is more critical than ever, with the need to protect sensitive information, yet share data with partners and other collaborators to improve machine learning models with collective data."

MS MARCO Web Search is the first web dataset that effectively meets the criteria of being large, real, and rich in terms of data quality. It is composed of large-scale web pages and query-document labels sourced from a commercial search engine, retaining rich information about the web pages that is widely employed in industry.

Context Engineering is described as the art of providing all the context for the task to be plausibly solvable by the LLM. It plays a crucial role in agent success.

The N-BaIoT dataset includes benign and attack traffic from various IoT devices, providing critical insights into device behavior under normal and compromised conditions.

Apple researchers investigated the abilities of Large Reasoning Models (LRMs) on puzzles, revealing a critical collapse threshold that limits their reasoning scalability.

To bridge the gap in public time series datasets for pre-training models, we collate multiple task-specific datasets into the Time Series Pile, encompassing diverse domains.

This interactive quiz helps reinforce your understanding of audio fundamentals and the essential use of TorchAudio for processing audio data in deep learning.