Modelos de IA

Os modelos de IA fazem previsões com base em seus dados de treinamento. Eles podem funcionar em qualquer domínio, como números, texto ou multimídia.

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Mestrados em Direito

Benchmark de Modelos Tabulares: Desempenho em 19 Conjuntos de Dados

Modelos de IAMai 22

We benchmarked 7 widely used tabular learning models across 19 real-world datasets, covering ~260,000 samples and over 250 total features, with dataset sizes ranging from 435 to nearly 49,000 rows. Our goal was to understand top-performing model families for datasets of different sizes and structure (e.g. numeric vs.

Modelos de Fundação do Mundo: 10 Casos de Uso

Training robots and autonomous vehicles (AVs) in the physical world can be costly, time-consuming and risky. World Foundation Models offer a scalable alternative by enabling realistic simulations of real-world environments. These models accelerate development and deployment in robotics, AVs, and other domains by reducing reliance on physical testing.

Modelos de IAMai 7

Comparação de modelos de visão de grande porte: GPT-4o vs YOLOv8n

Modelos de visão de grande escala (LVMs) podem automatizar e aprimorar tarefas visuais como detecção de defeitos, diagnóstico médico e monitoramento ambiental. Avaliamos o desempenho de três modelos de detecção de objetos: YOLOv8n, DETR e Vision, utilizando 1.000 imagens cada, medindo métricas como mAP@0.5, velocidade de inferência, FLOPs e número de parâmetros.

Modelos de IAAbr 24

Modelos de Linguagem Visual Comparados ao Reconhecimento de Imagem

Can advanced Vision Language Models (VLMs) replace traditional image recognition models? To find out, we benchmarked 16 leading models across three paradigms: traditional CNNs (ResNet, EfficientNet), VLMs ( such as GPT-4.1, Gemini 2.5), and Cloud APIs (AWS, Google, Azure).

Modelos de IAAbr 15

Compare Modelos de Fundação Relacionais

We benchmarked SAP-RPT-1-OSS against gradient boosting (LightGBM, CatBoost) on 17 tabular datasets spanning the semantic-numeral spectrum, small/high-semantic tables, mixed business datasets, and large low-semantic numerical datasets. Our goal is to measure where a relational LLM’s pretrained semantic priors may provide advantages over traditional tree models and where they face challenges under scale or low-semantic structure.

Modelos de IAFev 10

Modelos Fundamentais de Séries Temporais: Casos de Uso & Benefícios

Time series foundation models (TSFMs) build on advances in foundation models from natural language processing and vision. Using transformer-based architectures and large-scale training data, they achieve zero-shot performance and adapt across sectors such as finance, retail, energy, and healthcare.