Unite.AI

SEPTEMBER 22, 2024

Recent years have witnessed significant strides in the field of microscale robotics , pushing the boundaries of what's possible at the miniature level. These advancements have paved the way for potential breakthroughs in areas ranging from medical applications to environmental monitoring. In this landscape of innovation, researchers at Cornell University have made a noteworthy contribution, developing microscale robots that can transform their shape on command.

Robotics 145

Robotics 145

Marktechpost

SEPTEMBER 22, 2024

Chain-of-thought (CoT) prompting has emerged as a popular technique to enhance large language models’ (LLMs) problem-solving abilities by generating intermediate steps. Despite its better performance in mathematical reasoning, CoT’s effectiveness in other domains remains questionable. Current research is focused more on mathematical problems, possibly overlooking how CoT could be applied more broadly.

Natural Language Processing 137

Natural Language Processing Large Language Models ML AI 137

Machine Learning Mastery

SEPTEMBER 22, 2024

This post dives into the application of tree-based models, particularly focusing on decision trees, bagging, and random forests within the Ames Housing dataset. It begins by emphasizing the critical role of preprocessing, a fundamental step that ensures our data is optimally configured for the requirements of these models. The path from a single decision tree […] The post From Single Trees to Forests: Enhancing Real Estate Predictions with Ensembles appeared first on MachineLearningMastery

Data Science 85

Data Science 85

Marktechpost

SEPTEMBER 22, 2024

Artificial intelligence (AI) has given rise to powerful models capable of performing diverse tasks. Two of the most impactful advancements in this space are Retrieval-Augmented Generation (RAG) and Agents, which play distinct roles in improving AI-driven applications. However, the emerging concept of Agentic RAG presents a hybrid model that utilizes the strengths of both systems.

Chatbots 137

Chatbots AI AI Neural Network 137

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

Artificial Lawyer

SEPTEMBER 22, 2024

Can an AI system help a litigant to win their case in court?

AI 125

AI AI 125

Bugra Akyildiz

SEPTEMBER 22, 2024

Articles State Space Sequence Models is proposed to be a net iteration on the modeling front to the transformers for some time and Chetan Nichkawde wrote a blog post on some of its properties for State Space Sequence Models. It starts with some good properties for transformers, and then, afterwards, the blog post talks about the state space sequence models and its properties and other advantages to the existing modeling approaches like Transformers.

Neural Network 59

Neural Network LLM Large Language Models Data Ingestion 59

Marktechpost

SEPTEMBER 22, 2024

Artificial Intelligence (AI) safety has become an increasingly crucial area of research, particularly as large language models (LLMs) are employed in various applications. These models, designed to perform complex tasks such as solving symbolic mathematics problems, must be safeguarded against generating harmful or unethical content. With AI systems growing more sophisticated, it is essential to identify and address the vulnerabilities that arise when malicious actors try to manipulate these mod

AI 124

AI AI Large Language Models Artificial Intelligence 124

Pickl AI

SEPTEMBER 22, 2024

Summary: Linear algebra underpins many analytical techniques in Data Science. Understanding vectors, matrices, and their applications, like PCA, improves data manipulation skills and enhances algorithm performance in real-world problems. Introduction Linear algebra for Data Science forms the backbone of many analytical and Machine Learning techniques.

Data Science 52

Data Science Machine Learning Algorithm Data Scientist 52

Marktechpost

SEPTEMBER 22, 2024

Federated learning (FL) is a powerful ML paradigm that enables multiple data owners to train models without centralizing their data collaboratively. This approach is particularly valuable in domains where data privacy is critical, such as healthcare, finance, and the energy sector. The core of federated learning lies in training models on decentralized data stored on each client’s device.

Machine Learning 114

Machine Learning AI AI ML 114

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Many software teams have migrated their testing and production workloads to the cloud, yet development environments often remain tied to outdated local setups, limiting efficiency and growth. This is where Coder comes in. In our 101 Coder webinar, you’ll explore how cloud-based development environments can unlock new levels of productivity. Discover how to transition from local setups to a secure, cloud-powered ecosystem with ease.

TheSequence

SEPTEMBER 22, 2024

Created Using Ideogram Next Week in The Sequence: Edge 433: Our series about SSM continues with the introduction of the SAMBA model and the concept and SSMs for long-context windows. We review the original SAMBA paper and Microsoft’s Task Weaver agent for analytic workloads. Edge 434: We dive into DeepMind’s amazing GameNGen model that can simulate an entire game of Doom in real time.

AI 52

AI AI ML Large Language Models 52

Marktechpost

SEPTEMBER 22, 2024

Governments and humanitarian organizations need reliable data on building and infrastructure changes over time to manage urbanization, allocate resources, and respond to crises. However, many regions across the Global South need more access to timely and accurate data on buildings, making it difficult to track urban growth and infrastructure development.

Machine Learning 110

Machine Learning AI AI ML 110

Marktechpost

SEPTEMBER 22, 2024

Multi-agent reinforcement learning (MARL) is a field focused on developing systems where multiple agents cooperate to solve tasks that exceed the capabilities of individual agents. This area has garnered significant attention due to its relevance in autonomous vehicles, robotics, and complex gaming environments. The aim is to enable agents to work together efficiently, adapt to dynamic environments, and solve complex tasks that require coordination and collaboration.

Robotics 105

Robotics Artificial Intelligence Artificial Intelligence Algorithm 105

Marktechpost

SEPTEMBER 22, 2024

Input space mode connectivity in deep neural networks builds upon research on excessive input invariance, blind spots, and connectivity between inputs yielding similar outputs. The phenomenon exists generally, even in untrained networks, as evidenced by empirical and theoretical findings. This research expands the scope of input space connectivity beyond out-of-distribution samples, considering all possible inputs.

Neural Network 64

Neural Network Explainability Algorithm ML 64

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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

Marktechpost

SEPTEMBER 22, 2024

Federated Learning (FL) is a technique that allows Machine Learning models to be trained on decentralized data sources while preserving privacy. This method is especially helpful in industries like healthcare and finance, where privacy issues prevent data from being centralized. However, there are big problems when trying to include Homomorphic Encryption (HE) to protect the privacy of the data while it’s being trained.

Machine Learning 64

Machine Learning ML AI AI 64

Marktechpost

SEPTEMBER 22, 2024

Computational reproducibility poses a significant challenge in scientific research across various fields, including psychology, economics, medicine, and computer science. Despite the fundamental importance of reproducing results using provided data and code, recent studies have exposed severe shortcomings in this area. Researchers face numerous obstacles when replicating studies, even when code and data are available.

Python 59

Python Neural Network Automation Machine Learning 59