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Scientists at Carnegie Mellon University unveil TriForce: A layered guess-based AI system capable of expanding to long sequence creation.

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Language Model, Large Language Model, Staff, Tech News, Technology, UncategorizedApril 21, 202432Views0Likes0Comments
Due to the need for long-sequence support in large language models (LLMs), a solution to the problematic key-value (KV) cache bottleneck needs addressing. LLMs like GPT-4, Gemini, and LWM are becoming increasingly prominent in apps such as chatbots and financial analysis, but the substantial memory footprint of the KV cache and their auto-regressive nature make…

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The AI Safety Working Group from MLCommons has introduced version 0.5 of an innovative AI Safety Benchmark in their latest AI publication.

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Language Model, Large Language Model, Staff, Tech News, Technology, UncategorizedApril 21, 202438Views0Likes0Comments
MLCommons, a joint venture of industry and academia, has built a collaborative platform to improve AI safety, efficiency, and accountability. The MLCommons AI Safety Working Group established in late 2023 focuses on creating benchmarks for evaluating AI safety, tracking its progress, and encouraging safety enhancements. Its members, with diverse expertise in technical AI, policy, and…

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Comprehending Causal AI: Building a Link between Correlation and Causation

AI Shorts, Applications, Artificial Intelligence, Editors Pick, Staff, Tech News, Technology, UncategorizedApril 21, 202439Views0Likes0Comments
Artificial Intelligence (AI) has conventionally been spearheaded by statistical learning methods that are excellent at uncovering patterns from sizeable datasets. However, these tend to uncover correlations rather than causations, a differentiator that is of immense importance given correlation does not infer causation. Causal AI is an emerging, transformative approach that strives to comprehend the 'why'…

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Formal Interaction Model (FIM): A mathematically driven machine learning model which articulates the mutual influence between AI systems and their users.

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Machine learning, Staff, Tech News, Technology, UncategorizedApril 21, 202439Views0Likes0Comments
Machine learning is the driving force behind data-driven, adaptive, and increasingly intelligent products and platforms. Algorithms of artificial intelligence (AI) systems, such as Content Recommender Systems (CRS), intertwine with users and content creators, in turn shaping viewer preferences and the available content on these platforms. However, the current design and evaluation methodologies of these AI systems…

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Scientists at Stanford University are investigating Direct Preference Optimization (DPO), opening up fresh prospects in the field of machine learning and human feedback.

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Machine learning, Staff, Tech News, Technology, UncategorizedApril 21, 202434Views0Likes0Comments
Exploring the interactions between reinforcement learning (RL) and large language models (LLMs) sheds light on an exciting area of computational linguistics. These models, largely enhanced by human feedback, show remarkable prowess in understanding and generating text that mirrors human conversation. Yet, they are always evolving to capture more subtle human preferences. The main challenge lies…

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“UT Austin’s ‘Inheritune’ Aids in Streamlined Language Model Training: Utilizing Inheritance and Minimized Data for Equivalent Performance”

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Language Model, Large Language Model, Staff, Tech News, Technology, UncategorizedApril 21, 202436Views0Likes0Comments
Researchers at UT Austin have developed an effective and efficient method for training smaller language models (LM). Called "Inheritune," the method borrows transformer blocks from larger language models and trains the smaller model on a minuscule fraction of the original training data, resulting in a language model with 1.5 billion parameters using just 1 billion…

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‘Inheritune’ from UT Austin Aids in Streamlining Language Model Training: Utilizing Inheritance and Minimal Data for Similar Performance Outcomes.

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Language Model, Large Language Model, Staff, Tech News, Technology, UncategorizedApril 21, 202429Views0Likes0Comments
Scaling up language learning models (LLMs) involves substantial computational power and the need for high-density datasets. Language models typically make use of billions of parameters and are trained using datasets that contain trillions of tokens, making the process resource-intensive. A group of researchers from the University of Texas at Austin have found a solution. They’ve…

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Six Complimentary Google Courses on Artificial Intelligence (AI)

AI Shorts, Applications, Artificial Intelligence, Editors Pick, Staff, Tech News, Technology, UncategorizedApril 21, 202435Views0Likes0Comments
Six free artificial intelligence (AI) courses offered by Google provide a beginner's guide to exploring the realm of AI. These courses are designed to deliver fundamental concepts and practical applications in a comprehensive and manageable format, each estimated to take approximately 45 minutes for completion. On successful completion of each course, learners are rewarded with…

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Six Complimentary AI Courses Provided by Google

AI Shorts, Applications, Artificial Intelligence, Editors Pick, Staff, Tech News, Technology, UncategorizedApril 21, 202441Views0Likes0Comments
These six free artificial intelligence (AI) courses from Google provide a comprehensive pathway for beginners starting their journey into the AI world. They introduce key concepts and practical tools in a format that is easy to digest and understand. The first course, Introduction to Generative AI, gives an introductory overview of Generative AI. The course highlights…

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Introducing Briefer: A startup powered by AI, providing a platform similar to Jupyter Notebook. It assists data scientists in crafting analyses, visualizations, and data applications.

AI Startups, Editors Pick, Staff, Tech News, UncategorizedApril 21, 202444Views0Likes0Comments
The rapid progression of technology is revolutionizing the data analysis industry. Artificial Intelligence (AI) is poised to alter workflows swiftly, presenting prospects to automate functions and derive richer insights. Amid this shifting paradigm, Briefer, a cutting edge AI startup, has emerged. Heavily influenced by Notion's user-friendly interface, Briefer simplifies SQL and Python code execution, promotes collaborative…

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Google AI presents SOAR, an enhanced search algorithm for vectors that offers an efficient and minimal supplementary redundancy to ScaNN.

AI Shorts, Applications, Artificial Intelligence, Editors Pick, Machine learning, Staff, Tech News, Technology, UncategorizedApril 21, 202437Views0Likes0Comments
Google's AI research team has unveiled the ScaNN (Scalable Nearest Neighbors) vector search library, intended to address the growing need for efficient vector similarity search, a fundamental component of many machine learning algorithms. Current methods for calculating vector similarity are adequate for small datasets but as these datasets grow and new applications emerge, the requirement…

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Is it Possible for Language Models to Tackle Olympiad Programming? A New USACO Benchmark is Unveiled by Princeton University Scientists for Meticulously Assessing Code Language Models.

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Language Model, Large Language Model, Staff, Tech News, Technology, UncategorizedApril 21, 202438Views0Likes0Comments
Code generation is a critical domain for assessing and employing Large Language Models (LLMs). However, numerous existing coding benchmarks, such as HumanEval and MBPP, have reached solution rates over 90%, indicating the requirement for more challenging benchmarks. These would underline the limitations of current models and suggest ways to improve their algorithmic reasoning capabilities. Competitive programming…

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