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Robotic Marketer’s Lead Generation for IT Managed Service Providers

AI in IT, blog, IT managed services, IT solutions, Lead Generation, SaaS, UncategorizedJune 4, 2024184Views0Likes0Comments
Lead generation is crucial for IT managed services firms to expand their customer base and increase income. There is keen competition within the sector necessitating a well-considered strategy to cater to and capture high-quality leads. Increasingly, firms are incorporating tools such as Robotic Marketer to enhance their lead generation efforts. Lead generation entails luring prospects and…

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IEIT SYSTEMS introduces the updated version, Yuan 2.0-M32. This upgraded edition is a Bilingual Mixture of Expert MoE Language Model, which is fundamentally grounded on the Yuan 2.0. It also features an Attention Router.

AI Shorts, Applications, Artificial Intelligence, Editors Pick, Language Model, Large Language Model, Machine learning, Staff, Tech News, Technology, UncategorizedJune 4, 2024155Views0Likes0Comments
A research team from IEIT Systems has recently developed a new model, Yuan 2.0-M32, which uses the Mixture of Experts (MoE) architecture. This complex model is built on the same foundation as the Yuan-2.0 2B, but with utilization of 32 experts, only two of whom are active at any given time, resulting in its unique…

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AI-RAG Solutions: Hallucination-Free or Not? Stanford University Researchers Evaluate the Dependability of AI in Legal Research and Face Challenges with Illusions and Precision

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Language Model, Large Language Model, Machine learning, Staff, Tech News, Technology, UncategorizedJune 4, 2024143Views0Likes0Comments
Artificial Intelligence (AI) is increasingly being used in legal research and document drafting, aimed at improving efficiency and accuracy. However, concerns regarding the reliability of these tools persist, especially given the potential for the creation of false or misleading information, referred to as "hallucinations". This issue is of particular concern given the high-stakes nature of…

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Navigational Guidance and Prejudices in LLMs: Maneuvering through the Complexities of Persona Representation

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Language Model, Large Language Model, Staff, Tech News, Technology, UncategorizedJune 4, 2024179Views0Likes0Comments
Language and Large Model (LLM) research has shifted focus to steerability and persona congruity with complexities, challenging previous research simply based on one-dimensional personas or multiple-choice formats. A persona's intricacy and its potential to multiply biases in LLM simulations when there's lack of alignment with typical demographic views is now recognized. A recent research by…

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Knock Knock: An Innovative Python Library Allows You to Receive Alerts Once Your Training is Finished With Only Two Extra Lines of Code

AI Shorts, Applications, Artificial Intelligence, Editors Pick, Staff, Tech News, Technology, UncategorizedJune 4, 2024162Views0Likes0Comments
Deep learning (DL) model training often presents challenges due to its unpredictable and time-consuming nature. Determining when a model will finish training or foreseeing if it may crash unexpectedly can be difficult, leading to inefficiencies, especially during manual monitoring of the training process. While some techniques, such as early stopping and logging systems, do exist…

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Empowering individuals with challenges to utilize Artificial Intelligence.

Algorithms, Alumni/ae, Artificial Intelligence, Data, Innovation and Entrepreneurship (I&E), Machine learning, Media Lab, School of Architecture and Planning, Startups, UncategorizedJune 4, 2024188Views0Likes0Comments
In 2010, MIT Media Lab students Karthik Dinakar and Birago Jones embarked on a project to develop a tool to aid content moderation for companies like Twitter and YouTube. The original concept had difficulty identifying posts using teenage slang and other non-obvious language nuances, but after realizing those most familiar with the data should be…

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A new artificial intelligence model has the potential to simplify processes in an automated warehouse.

Algorithms, Artificial Intelligence, Civil and environmental engineering, Computer science and technology, IDSS, Laboratory for Information and Decision Systems (LIDS), Machine learning, MIT Schwarzman College of Computing, Research, Robots, School of Engineering, UncategorizedJune 4, 2024240Views0Likes0Comments
Navigating hundreds of robots in a warehouse without causing accidents is a growing challenge for many industries, from e-commerce to automotive production. To address this issue, a team of researchers at the Massachusetts Institute of Technology (MIT) has developed an AI-based approach that increases efficiency and reduces congestion. The team devised a deep learning model that…

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