A Coding Guide Implementing ScrapeGraph and Gemini AI for an Automated, Scalable, Insight-Driven Competitive Intelligence and Market Analysis Workflow

A Coding Guide Implementing ScrapeGraph and Gemini AI for an Automated, Scalable, Insight-Driven Competitive Intelligence and Market Analysis Workflow

In this tutorial, we demonstrate how to leverage ScrapeGraph’s powerful scraping tools in combination with Gemini AI to automate the collection, parsing, and analysis of competitor information. By using ScrapeGraph’s SmartScraperTool and MarkdownifyTool, users can extract detailed insights from product offerings, pricing strategies, technology stacks, and market presence directly from competitor websites. The tutorial then…

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LightOn AI Released GTE-ModernColBERT-v1: A Scalable Token-Level Semantic Search Model for Long-Document Retrieval and Benchmark-Leading Performance

LightOn AI Released GTE-ModernColBERT-v1: A Scalable Token-Level Semantic Search Model for Long-Document Retrieval and Benchmark-Leading Performance

Semantic retrieval focuses on understanding the meaning behind text rather than matching keywords, allowing systems to provide results that align with user intent. This ability is essential across domains that depend on large-scale information retrieval, such as scientific research, legal analysis, and digital assistants. Traditional keyword-based methods fail to capture the nuance of human language,…

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DeepSeek-GRM: Revolutionizing Scalable, Cost-Efficient AI for Businesses

DeepSeek-GRM: Revolutionizing Scalable, Cost-Efficient AI for Businesses

Many businesses struggle to adopt Artificial Intelligence (AI) due to high costs and technical complexity, making advanced models inaccessible to smaller organizations. DeepSeek-GRM addresses this challenge to improve AI efficiency and accessibility, helping bridge this gap by refining how AI models process and generate responses. The model employs Generative Reward Modeling (GRM) to guide AI…

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Mem0: A Scalable Memory Architecture Enabling Persistent, Structured Recall for Long-Term AI Conversations Across Sessions

Mem0: A Scalable Memory Architecture Enabling Persistent, Structured Recall for Long-Term AI Conversations Across Sessions

Large language models can generate fluent responses, emulate tone, and even follow complex instructions; however, they struggle to retain information across multiple sessions. This limitation becomes more pressing as LLMs are integrated into applications that require long-term engagement, such as personal assistance, health management, and tutoring. In real-life conversations, people recall preferences, infer behaviors, and…

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DeepSeek unveils new technique for smarter, scalable AI reward models

DeepSeek unveils new technique for smarter, scalable AI reward models

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More DeepSeek AI, a Chinese research lab gaining recognition for its powerful open-source language models such as DeepSeek-R1, has introduced a significant advancement in reward modeling for large language models (LLMs).  Their new technique, Self-Principled Critique Tuning…

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Salesforce AI Released APIGen-MT and xLAM-2-fc-r Model Series: Advancing Multi-Turn Agent Training with Verified Data Pipelines and Scalable LLM Architectures

Salesforce AI Released APIGen-MT and xLAM-2-fc-r Model Series: Advancing Multi-Turn Agent Training with Verified Data Pipelines and Scalable LLM Architectures

AI agents quickly become core components in handling complex human interactions, particularly in business environments where conversations span multiple turns and involve task execution, information extraction, and adherence to specific procedural rules. Unlike traditional chatbots that handle single-turn questions, these agents must hold context over several dialogue exchanges while integrating external data and tool usage….

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ZEISS Demonstrates the Power of Scalable Workflows with Ampere Altra and SpinKube — SitePoint

ZEISS Demonstrates the Power of Scalable Workflows with Ampere Altra and SpinKube — SitePoint

Snapshot Challenge The cost of maintaining a system capable of processing tens of thousands of near-simultaneous requests, but which spends greater than 90 percent of its time in an idle state, cannot be justified. Containerization promised the ability to scale workloads on demand, which includes scaling down when demand is low. Maintaining many pods among…

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Process Reinforcement through Implicit Rewards (PRIME): A Scalable Machine Learning Framework for Enhancing Reasoning Capabilities

Process Reinforcement through Implicit Rewards (PRIME): A Scalable Machine Learning Framework for Enhancing Reasoning Capabilities

Reinforcement learning (RL) for large language models (LLMs) has traditionally relied on outcome-based rewards, which provide feedback only on the final output. This sparsity of reward makes it challenging to train models that need multi-step reasoning, like those employed in mathematical problem-solving and programming. Additionally, credit assignment becomes ambiguous, as the model does not get…

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