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Progress in Protein Sequence Design: Utilizing Reinforcement Learning and Language Models

AI Paper Summary, AI Shorts, Artificial Intelligence, Editors Pick, Machine learning, Staff, Tech News, Technology, UncategorizedJuly 9, 202429Views0Likes0Comments
Protein sequence design is a significant part of protein engineering for drug discovery, involving the exploration of vast amino acid sequence combinations. To overcome the limitations of traditional methods like evolutionary strategies, researchers have proposed utilizing reinforcement learning (RL) techniques to facilitate the creation of new protein sequences. This progress comes as advancements in protein…

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Salesforce Research has launched INDICT, an innovative framework designed to boost the security and usefulness of AI-produced coding across a wide range of programming languages.

AI Shorts, Applications, Artificial Intelligence, Editors Pick, Language Model, Large Language Model, Staff, Technology, UncategorizedJuly 9, 202434Views0Likes0Comments
The use of Large Language Models (LLMs) for automating and assisting in coding holds promise for improving the efficiency of software development. However, the challenge is ensuring these models produce code that is not only helpful but also secure, as the code generated could potentially be used maliciously. This concern is not theoretical, as real-world…

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This AI Article from Cohere for AI provides an exhaustive analysis about optimizing preferences in multiple languages.

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Language Model, Large Language Model, Staff, Tech News, Technology, UncategorizedJuly 9, 202431Views0Likes0Comments
The study of multilingual natural language processing (NLP) is rapidly progressing, seeking to create language models capable of interpreting and generating text in various languages. The central goal of this research is to improve global communication and access to information, making artificial intelligence technologies accessible across diverse linguistic backgrounds. However, creating such models brings significant challenges,…

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Scientists from the University of Manchester have put forward ESBMC-Python, a pioneering Python-code checker relying on BMC, for official verification of Python software.

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Staff, Tech News, Technology, UncategorizedJuly 9, 202434Views0Likes0Comments
Software engineering frequently employs formal verification to guarantee program correctness, a process frequently facilitated by bounded model checking (BMC). Traditional verification tools use explicit type information, making Python, a dynamic programming language, difficult to verify. The lack of clear type information in Python programs makes ensuring their safety a challenging process, especially in systems with…

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Key Artificial Intelligence (AI) Search Engines to be Aware of in 2024

AI Shorts, Applications, Artificial Intelligence, Editors Pick, Staff, Tech News, Technology, UncategorizedJuly 8, 202435Views0Likes0Comments
Artificial Intelligence (AI) search engines are revolutionizing users' online search experience by delivering more precise results tailored to user preferences, using advanced algorithms, machine learning, natural language processing, and deep learning. They provide individualized results, understand the context behind the queries, and can even understand poorly structured questions. Some notable AI search engines that are…

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T-FREE: An Efficient and Scalable Method for Text Encoding in Large Language Models that Doesn’t Require a Tokenizer

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Language Model, Large Language Model, Staff, Tech News, Technology, UncategorizedJuly 8, 202431Views0Likes0Comments
Natural language processing (NLP) is a field in computer science that seeks to enable computers to interpret and generate human language. This has various applications such as machine translation and sentiment analysis. However, there are limitations and inefficiencies with conventional tokenizers employed in large language models (LLMs). These tokenizers break down text into subwords, demanding…

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Tsinghua University Unveils Open-Sourced CodeGeeX4-ALL-9B: An Innovative Multilingual Code Generation Model Surpassing Key Rivals and Enhancing Code Assistance.

AI Shorts, Applications, Artificial Intelligence, Editors Pick, Language Model, Large Language Model, New Releases, Staff, Tech News, Technology, UncategorizedJuly 8, 202440Views0Likes0Comments
The Knowledge Engineering Group (KEG) and Data Mining team at Tsinghua University have revealed their latest breakthrough in code generation technology, named CodeGeeX4-ALL-9B. This advanced model, a new addition in the acclaimed CodeGeeX series, is a ground-breaking achievement in multilingual code generation, raising the bar for automated code generation efficiency and performance. A product of extensive…

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Scientists from the IT University in Copenhagen suggest using self-regulating neural networks to improve adaptability.

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Deep Learning, Editors Pick, Machine learning, Staff, Tech News, Technology, UncategorizedJuly 8, 202426Views0Likes0Comments
Artificial Neural Networks (ANNs) have long been used in artificial intelligence but are often criticized for their static structure which struggles to adapt to changing circumstances. This has restricted their use in areas such as real-time adaptive systems or robotics. In response to this, researchers from the IT University of Copenhagen have designed an innovative…

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Copenhagen’s IT University scientists suggest using self-adjusting neural networks for improved adaptability.

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Deep Learning, Editors Pick, Machine learning, Staff, Tech News, Technology, UncategorizedJuly 8, 202422Views0Likes0Comments
Artificial Neural Networks (ANNs), while transformative, have traditional shortcomings in terms of adaptability and plasticity. This lack of flexibility poses a significant challenge for their applicability in dynamic and unpredictable environments. It also inhibits their effectiveness in real-time applications like robotics and adaptive systems, making real-time learning and adaptation a crucial achievement for artificial intelligence…

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Google researchers have put forth a novel machine learning algorithm, formally boosting an algorithm that applies to any loss function whose set of discontinuities bears no Lebesgue measure.

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Machine learning, Staff, Tech News, Technology, UncategorizedJuly 8, 202431Views0Likes0Comments
Google's research team is working on developing an optimized machine learning (ML) method known as "boosting." Boosting involves creating high performing models using a "weak learner oracle" which gives classifiers a performance slightly better than random guessing. Over the years, boosting has evolved into a first-order optimization setting. However, some in the industry erroneously define…

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Google scientists suggest a precise enhancing system for machine learning algorithms that can work with any loss function, provided its set of discontinuities possesses no Lebesgue measurement.

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Machine learning, Staff, Tech News, Technology, UncategorizedJuly 8, 202433Views0Likes0Comments
Boosting, a highly effective machine learning (ML) optimization setting, has evolved from a model that did not require first-order loss information into a method that necessitates this knowledge. Despite this transformation, few investigations have been made into boosting, even as machine learning witnesses a surge in zeroth-order optimization - methods that bypass the use of…

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