Aiiot Talk

MAY 18, 2024

Customer relationship management (CRM) software is a crucial tool for small businesses in any industry. These platforms help you track your sales, churn rate and other customer interactions across their entire life cycle. This insight is a huge advantage in marketing and sales, and Internet of Things (IoT) connectivity can take it even further. Integrating the IoT into your CRM strategy could allow you to use extensive data for more in-depth customer insights.

Robotics 130

Robotics Artificial Intelligence Artificial Intelligence Automation 130

Marktechpost

MAY 18, 2024

The recent Yi-1.5-34B model introduced by 01.AI has brought about yet another advancement in the field of Artificial Intelligence. Positioned as a major improvement over its predecessors, this unique model bridges the gap between Llama 3 8B and 70B. It promises better performance in a number of areas, such as multimodal capability, code production, and logical reasoning.

Artificial Intelligence 131

Artificial Intelligence Artificial Intelligence Machine Learning AI 131

Salmon Run

MAY 18, 2024

Last month, I decided to sign-up for the Google AI Hackathon, where Google provided access to their Gemini Large Language Model (LLM) and tasked participants with building a creative application on top of it. I have worked with Anthropic's Claude and OpenAI's GPT-3 at work previously, and I was curious to see how Gemini stacked up against them.

Large Language Models 59

Large Language Models OpenAI LLM AI 59

Marktechpost

MAY 18, 2024

The artificial intelligence and machine learning world has witnessed rapid advancements, with OpenAI at the forefront of these innovations. One of the latest developments is the release of GPT-4o, an optimized version of the highly acclaimed GPT-4. Let’s delve into the key updates in GPT-4o, compare it with its predecessor, and present a comparative table highlighting the differences.

Artificial Intelligence 131

Artificial Intelligence Artificial Intelligence Natural Language Processing OpenAI 131

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

MAY 18, 2024

Although recent multimodal foundation models are extensively utilized, they tend to segregate various modalities, typically employing specific encoders or decoders for each. This approach constrains their capacity to fuse information across modalities effectively and produce multimodal documents comprising diverse sequences of images and text. Consequently, there’s a limitation in their ability to seamlessly integrate different types of content within a single document.

Machine Learning 130

Machine Learning AI AI ML 130

Marktechpost

MAY 18, 2024

Graph Neural Networks GNNs are advanced tools for graph classification, leveraging neighborhood aggregation to update node representations iteratively. This process captures local and global graph structure, facilitating node classification and link prediction tasks. Effective graph pooling is essential for downsizing and learning representations, categorized into global and hierarchical pooling.

Neural Network 111

Neural Network Categorization Deep Learning Data Analysis 111

Marktechpost

MAY 18, 2024

Accurate propagation modeling is paramount for effective radio deployments, coverage analysis, and interference mitigation in wireless communications. Path loss modeling, a widely adopted approach, enables generic predictions of signal power attenuation along wireless links, equipping network planners with essential insights into physical layer attributes.

Machine Learning 111

Machine Learning Neural Network ML Artificial Intelligence 111

Marktechpost

MAY 18, 2024

State-space models (SSMs) are crucial in deep learning for sequence modeling. They represent systems where the output depends on both current and past inputs. SSMs are widely applied in signal processing, control systems, and natural language processing. The main challenge is the inefficiency of existing SSMs, particularly regarding memory and computational costs.

Deep Learning 111

Deep Learning Natural Language Processing AI AI 111

Marktechpost

MAY 18, 2024

Machine learning models, which can contain billions of parameters, require sophisticated methods to fine-tune their performance efficiently. Researchers aim to enhance the accuracy of these models while minimizing the computational resources needed. This improvement is crucial for practical applications in various domains, such as natural language processing & artificial intelligence, where efficient resource utilization can significantly impact overall performance and feasibility.

Large Language Models 111

Large Language Models Natural Language Processing Artificial Intelligence Artificial Intelligence 111

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Marktechpost

MAY 18, 2024

As Artificial Intelligence (AI) systems advance, a fascinating trend has emerged: their representations of data across different architectures, training objectives, and even modalities seem to be converging. Researchers have put forth, as shown in Figure 1, a thought-provoking hypothesis to explain this phenomenon called the “Platonic Representation Hypothesis.” At its core, this hypothesis posits that various AI models strive to capture a unified representation of the underlying rea

Neural Network 105

Neural Network Large Language Models Artificial Intelligence Artificial Intelligence 105

Marktechpost

MAY 18, 2024

Data mapping is a critical process in data management, enabling the integration and transformation of data from various sources into a unified format. The concept of data mapping as a search problem provides a unique perspective on efficiently and effectively discovering mappings between data sources. Let’s explore the foundational concepts, challenges, methodologies, and future directions in the realm of data mapping viewed through the lens of search.

Machine Learning 105

Machine Learning Data Integration Algorithm Automation 105