​[[{“value”:” Neural networks have been widely used to solve partial differential equations (PDEs) in different fields, such as biology, physics, and materials science. Although current research focuses on PDEs with a singular solution, nonlinear PDEs with multiple solutions create a major problem. Different neural network… Read More »Newton Informed Neural Operator: A Novel Machine Learning Approach for Computing Multiple Solutions of Nonlinear Partials Differential Equations Sajjad Ansari Artificial Intelligence Category – MarkTechPost

​[[{“value”:” What are AI Agents? Artificial intelligence (AI) agents are intelligent beings with the capacity to sense their surroundings, analyze information, and act independently to accomplish predetermined objectives. These agents use AI approaches to perform their functions and can be either software-based or physical beings.… Read More »What are AI Agents? How do you make one? Understand the Basics Tanya Malhotra Artificial Intelligence Category – MarkTechPost

​[[{“value”:” The Mistral AI Team has announced the release of its groundbreaking code generation model, Codestral-22B. This contributes toward a new direction and benchmark of AI for software development. Codestral empowers developers by enhancing their coding capabilities and streamlining the development process. Codestral is an… Read More »Mistral AI Releases Codestral: An Open-Weight Generative AI Model for Code Generation Tasks and Trained on 80+ Programming Languages, Including Python Asif Razzaq Artificial Intelligence Category – MarkTechPost

​[[{“value”:” With significant advancements through its Gemini, PaLM, and Bard models, Google has been at the forefront of AI development. Each model has distinct capabilities and applications, reflecting Google’s research in the LLM world to push the boundaries of AI technology. Gemini: Google’s Multimodal Marvel… Read More »Google’s Advanced AI Models: Gemini, PaLM, and Bard Sana Hassan Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Protein design is a rapidly advancing field leveraging computational models to create proteins with novel structures and functions. This technology has significant applications in therapeutics and industrial processes, revolutionizing how proteins are engineered for specific tasks. Researchers in this field aim to develop methods… Read More »Genie 2: Transforming Protein Design with Advanced Multi-Motif Scaffolding and Enhanced Structural Diversity Aswin Ak Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Multimodal Large Language Models (MLLMs) represent an advanced field in artificial intelligence where models integrate visual and textual information to understand and generate responses. These models have evolved from large language models (LLMs) that excelled in text comprehension and generation to now also processing… Read More »Beyond High-Level Features: Dense Connector Boosts Multimodal Large Language Models MLLMs with Multi-Layer Visual Integration Nikhil Artificial Intelligence Category – MarkTechPost

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The ability of LLMs to execute commands through plain language (e.g. English) has enabled agentic systems that can complete a user query by orchestrating the right set of tools (e.g. ToolFormer, Gorilla). This, along with the recent multi-modal efforts such as the GPT-4o or Gemini-1.5 model, has expanded the realm of possibilities with AI agents. While this is quite exciting, the large model size and computational requirements of these models often requires their inference to be performed on the cloud. This can create several challenges for their widespread adoption. First and foremost, uploading data such as video, audio, or text documents to a third party vendor on the cloud, can result in privacy issues. Second, this requires cloud/Wi-Fi connectivity which is not always possible. For instance, a robot deployed in the real world may not always have a stable connection. Besides that, latency could also be an issue as uploading large amounts of data to the cloud and waiting for the response could slow down response time, resulting in unacceptable time-to-solution. These challenges could be solved if we deploy the LLM models locally at the edge.

Read More »TinyAgent: Function Calling at the Edge The Berkeley Artificial Intelligence Research Blog

​[[{“value”:” The rapid advancements in sequencing technologies have unlocked unprecedented potential in genomic research and precision medicine. However, the challenge of accurately identifying genetic variants from billions of short, error-prone sequence reads remains significant. A promising solution to this challenge has emerged in DeepVariant, a… Read More »AI-Powered Genomic Analysis: Transforming Precision Medicine through Advanced Data Interpretation Sana Hassan Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Community Question Answering (CQA) platforms, exemplified by Quora, Yahoo! Answers, and StackOverflow, serve as interactive hubs for information exchange. Despite their popularity, the varying quality of responses poses a challenge for users who must navigate through numerous answers to find relevant information efficiently. Answer… Read More »Question-Answer Cross Attention Networks (QAN): Advancing Answer Selection in Community Question Answering Mohammad Asjad Artificial Intelligence Category – MarkTechPost