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Artificial Intelligence

Is it Possible for LLMs to Speed Up the Identification of Data-Driven Scientific Theories? Introducing DiscoveryBench: An Extensive LLM Standard that Structurally Defines the Multi-Stage Procedure of Data-Dependent Discovery.

Scientific discovery has vastly benefited from advancements in technology and artificial intelligence, and now Large Language Models (LLMs) offer the potential to revolutionize this process. Researchers from the Allen Institute for AI, OpenLocus, and the University of Massachusetts Amherst have probed this potential with their DISCOVERYBENCH tool. Traditionally, scientific discovery has relied on manual processes…

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A novel computational method could simplify the process of designing beneficial proteins.

MIT researchers have developed a computational approach to help predict mutations that can create optimized versions of certain proteins, working with a relatively small amount of data. The team believes the system could lead to potential medical applications and neuroscience research tools. Usually, protein engineering begins with a natural protein that already has a desirable function,…

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Anole: A Public, Native Broad Multimodal Model Utilizing Autoregressive Techniques for Combined Image-Text Generation

Open-source large multimodal models (LMMs), such as LLaVA, CogVLM, and DreamLLM, which primarily handle multimodal understanding without generation capabilities, currently face significant limitations. They often lack the native integration required to align visual representations with pre-trained language models, leading to complexity and inefficiency in both training and inference time. Moreover, many are either restricted to…

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Cornell’s AI research paper presents UCB-E and UCB-E-LRF: Innovative multi-armed bandit algorithms designed for productive and economically viable LLM assessment.

Natural Language Processing (NLP) allows for the interaction between humans and computers via natural language, which includes tasks like translation, sentiment analysis and answering questions. Achieving high performance and accuracy in NLP tasks relies on large language models (LLMs). These models have vast applications, ranging from auto-generated customer support to content creation, and have shown…

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Google DeepMind Introduces PaliGemma: A Multifaceted 3B Vision-Language Model VLM with Grand Scale Objectives.

DeepMind researchers have unveiled a new model, PaliGemma, pushing forward the evolution of vision-language models. The new model successfully integrates the strengths of both the PaLI vision-language model series and the Gemma family of language models. PaliGemma is an example of a sub-3B vision-language model that uses a 400M SigLIP vision model along with a…

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Google DeepMind Introduces PaliGemma: A Multifaceted 3B Vision-Language Model with Extensive-Scale Goals

DeepMind researchers have developed an open vision-language model called PaliGemma, blending the strengths of the PaLI vision-language model series with Gemma family of language models. This model merges a 400 million SigLIP vision model with a 2 billion Gemma language model, creating a compact vision-language model that can compete with larger predecessors such as PaLI-X,…

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Surpassing AI’s Future Insight and Decision-Making Boundaries: More than Just Predicting the Next Token

A new study attempts to address the limitations associated with next-token prediction methods in artificial intelligence (AI), which currently hinder the technology's ability to mimic human intelligence, specifically in the area of advance planning and reasoning. Featuring in a multitude of language models today, these methods are increasingly shown to be deficient when it comes…

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Beyond Predicting the Next Token: Surpassing the Predictive and Decision-Making Constraints of AI

Artificial intelligence research often examines whether next-token prediction—the convention for AI language models—can replicate some aspects of human intelligence such as planning and reasoning. However, despite its extensive use, this method may have native limitations when it comes to tasks necessitating foresight and decision-making. This is important because overcoming this could allow the development of…

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The launch of FlashAttention-3 is confirmed: it delivers extraordinary accuracy and velocity, leveraging state-of-the-art hardware usage and reduced-precision computation.

FlashAttention-3, the newest addition to the FlashAttention series, was created to address the fundamental issues related to Transformer architectures' attention layer. This is particularly important to the performance of large language models (LLMs) and applications that need long-context processing. Historically, the FlashAttention series, which includes FlashAttention and FlashAttention-2, has reshaped how attention mechanisms function on GPUs…

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A novel computational algorithm could simplify the process of creating beneficial proteins.

MIT researchers have developed a computational approach that predicts protein mutations, based on limited data, that would enhance their performance. The researchers used their model to create optimized versions of proteins derived from two naturally occurring structures. One of these was the green fluorescent protein (GFP), a molecule used to track cellular processes within the…

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Celebrating a significant event: A dedication ceremony applauds the inauguration of the new Schwarzman College of Computing building at MIT.

The MIT Stephen A. Schwarzman College of Computing recently celebrated the completion of its new Vassar Street building. The dedication ceremony was attended by members of the MIT community, distinguished guests, and supporters, reflecting on the transformative gift from Stephen A. Schwarzman that initiated the biggest change to MIT’s institutional structure in over 70 years.…

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FunAudioLLM: An Integrated Platform for Naturally Fluid, Multilingual and Emotionally Responsive Voice Communications

Artificial Intelligence (AI) advancements have significantly evolved voice interaction technology with the primary goal to make the interaction between humans and machines more intuitive and human-like. Recent developments have led to the attainment of high-precision speech recognition, emotion detection, and natural speech generation. Despite these advancements, voice interaction needs to improve latency, multilingual support, and…

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