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Researchers from Fudan University and Shanghai AI Lab Introduces DOLPHIN: A Closed-Loop Framework for Automating Scientific Research with Iterative Feedback

Marktechpost

Fudan University and the Shanghai Artificial Intelligence Laboratory have developed DOLPHIN, a closed-loop auto-research framework covering the entire scientific research process. In image classification, DOLPHIN improved baseline models like WideResNet by up to 0.8%, achieving a top-1 accuracy of 82.0%.

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How Lumi streamlines loan approvals with Amazon SageMaker AI

AWS Machine Learning Blog

This post explores how Lumi uses Amazon SageMaker AI to meet this goal, enhance their transaction processing and classification capabilities, and ultimately grow their business by providing faster processing of loan applications, more accurate credit decisions, and improved customer experience.

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Yanfeng Auto adopts IBM Data, AI and Intelligent Automation Software to accelerate digital and intelligent transformation

IBM Journey to AI blog

According to the recent statistics released by a local auto industry association, the sales of China’s fuel vehicle market have declined for three consecutive years. The auto parts manufacturers caught in it are facing the problem of how to survive and grow against the increasingly fierce competition.

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LightAutoML: AutoML Solution for a Large Financial Services Ecosystem

Unite.AI

Second, the White-Box Preset implements simple interpretable algorithms such as Logistic Regression instead of WoE or Weight of Evidence encoding and discretized features to solve binary classification tasks on tabular data. In the situation where there is a single task with a small dataset, the user can manually specify each feature type.

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Announcing our $50M Series C to build superhuman Speech AI models

AssemblyAI

There also now exist incredibly capable LLMs that can be used to ingest accurately recognized speech and generate summaries, insights, takeaways, and classifications that are enabling entirely new products and workflows to be created with voice data for the first time ever.

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Sensor-Invariant Tactile Representation for Zero-Shot Transfer Across Vision-Based Tactile Sensors

Marktechpost

Auto-encoding representation approaches are also explored, with some researchers utilizing Masked Auto-Encoder (MAE) to learn tactile representations. In object classification tests using the researchers’ real-world dataset, SITR outperforms all baseline models when transferred across different sensors.

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Taming Long Audio Sequences: Audio Mamba Achieves Transformer-Level Performance Without Self-Attention

Marktechpost

Audio classification has evolved significantly with the adoption of deep learning models. The primary challenge in audio classification is the computational complexity associated with transformers, particularly due to their self-attention mechanism, which scales quadratically with the sequence length.