Eugene Yan

SEPTEMBER 7, 2024

Comparing five implementations built with FastAPI, FastHTML, Next.

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Unite.AI

SEPTEMBER 7, 2024

A recent study from the University of California, Merced, has shed light on a concerning trend: our tendency to place excessive trust in AI systems, even in life-or-death situations. As AI continues to permeate various aspects of our society, from smartphone assistants to complex decision-support systems, we find ourselves increasingly relying on these technologies to guide our choices.

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Robotics AI AI Responsible AI 217

Marktechpost

SEPTEMBER 7, 2024

Hallucination is a phenomenon where large language models (LLMs) produce responses that are not grounded in reality or do not align with the provided context, generating incorrect, misleading, or nonsensical information. These errors can have serious consequences, particularly in applications that require high precision, like medical diagnosis, legal advice, or other high-stakes scenarios.

LLM 138

LLM Large Language Models ML AI 138

Marktechpost

SEPTEMBER 7, 2024

The primary challenge in scaling large-scale AI systems is achieving efficient decision-making while maintaining performance. Distributed AI, particularly multi-agent reinforcement learning (MARL), offers potential by decomposing complex tasks and distributing them across collaborative nodes. However, real-world applications face limitations due to high communication and data requirements.

ML 135

ML AI AI Artificial Intelligence 135

Speaker: David Warren and Kevin O'Neill Stoll

Transitioning to a usage-based business model offers powerful growth opportunities but comes with unique challenges. How do you validate strategies, reduce risks, and ensure alignment with customer value? Join us for a deep dive into designing effective pilots that test the waters and drive success in usage-based revenue. Discover how to develop a pilot that captures real customer feedback, aligns internal teams with usage metrics, and rethinks sales incentives to prioritize lasting customer eng

Marktechpost

SEPTEMBER 7, 2024

DeepSeek-AI has released DeepSeek-V2.5 , a powerful Mixture of Experts (MOE) model with 238 billion parameters, featuring 160 experts and 16 billion active parameters for optimized performance. The model excels in chat and coding tasks, with cutting-edge capabilities such as function calls, JSON output generation, and Fill-in-the-Middle (FIM) completion.

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AI AI Deep Learning Conversational AI 128

Marktechpost

SEPTEMBER 7, 2024

Large language models (LLMs) have become fundamental tools for tasks such as question-answering (QA) and text summarization. These models excel at processing long and complex texts, with capacities reaching over 100,000 tokens. As LLMs are popular for handling large-context tasks, ensuring their reliability and accuracy becomes more pressing. Users rely on LLMs to sift through vast information and provide concise, correct answers.

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LLM Large Language Models AI Researcher AI Research 105

Marktechpost

SEPTEMBER 7, 2024

Large language models (LLMs) have significantly progressed in various domains, including natural language understanding and code generation. These models can generate coherent text and solve complex tasks. However, LLMs face challenges when applied to more specialized areas such as competitive programming and code generation. This field focuses on improving the models’ ability to generate diverse, accurate solutions to coding problems, using computational power more effectively during inference.

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Large Language Models LLM AI AI 105

Marktechpost

SEPTEMBER 7, 2024

Social network generation finds numerous applications in various fields, such as epidemic modeling, social media simulations, and understanding social phenomena like polarization. Creating realistic social networks is crucial when real networks cannot be directly observed due to privacy concerns or other constraints. These generated networks are vital for accurately modeling interactions and predicting outcomes in these contexts.

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LLM Deep Learning Large Language Models OpenAI 64

Marktechpost

SEPTEMBER 7, 2024

Graph neural networks (GNNs) have emerged as powerful tools for capturing complex interactions in real-world entities and finding applications across various business domains. These networks excel at generating effective graph entity embeddings by encoding both node features and structural insights, making them invaluable for numerous downstream tasks.

Algorithm 59

Algorithm Neural Network Computer Vision Data Analysis 59

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Marktechpost

SEPTEMBER 7, 2024

Artificial intelligence (AI) and database management systems have increasingly converged, with significant potential to improve how users interact with large datasets. Recent advancements aim to allow users to pose natural language questions directly to databases and retrieve detailed, complex answers. However, current tools are limited in addressing real-world demands.

Business Intelligence 59

Business Intelligence Artificial Intelligence Artificial Intelligence Data Analysis 59

Marktechpost

SEPTEMBER 7, 2024

The paper “MemLong: Memory-Augmented Retrieval for Long Text Modeling” addresses a critical limitation regarding the ability to process long contexts in the field of Large Language Models (LLMs). While LLMs have shown remarkable success in various applications, they struggle with long-sequence tasks due to traditional attention mechanisms’ quadratic time and space complexity.

Large Language Models 59

Large Language Models ML Artificial Intelligence Artificial Intelligence 59

Marktechpost

SEPTEMBER 7, 2024

Graph Neural Networks (GNNs) have emerged as the leading approach for graph learning tasks across various domains, including recommender systems, social networks, and bioinformatics. However, GNNs have shown vulnerability to adversarial attacks, particularly structural attacks that modify graph edges. These attacks pose significant challenges in scenarios where attackers have limited access to entity relationships.

Neural Network 59

Neural Network ML Artificial Intelligence Artificial Intelligence 59

Marktechpost

SEPTEMBER 7, 2024

Mixture-of-experts (MoE) architectures are becoming significant in the rapidly developing field of Artificial Intelligence (AI), allowing for the creation of systems that are more effective, scalable, and adaptable. MoE optimizes computing power and resource utilization by employing a system of specialized sub-models, or experts, that are selectively activated based on the input data.

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Artificial Intelligence Artificial Intelligence Natural Language Processing Neural Network 59

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Large enterprises face unique challenges in optimizing their Business Intelligence (BI) output due to the sheer scale and complexity of their operations. Unlike smaller organizations, where basic BI features and simple dashboards might suffice, enterprises must manage vast amounts of data from diverse sources. What are the top modern BI use cases for enterprise businesses to help you get a leg up on the competition?

Business Intelligence