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How do you make a robot smarter? Program it to know what it doesn’t know
Engineers have developed a method to teach robots to recognize uncertainty by quantifying the vagueness of human instructions, prompting them to request clarification when necessary, such as when multiple objects are present but only one is needed.
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Amazon Launches Amazon Q a Workplace-Focused AI Chatbot
Amazon introduced Amazon Q, an AI chatbot for workplace assistance from AWS, focusing on streamlining office tasks while prioritizing data security. Competing with Microsoft and Google, it’s priced at $20/user/month. Amazon also plans to enhance AI infrastructure in partnership with Nvidia.
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Norway’s tech leaders to feature at the Nordic AI Summit
The Nordic AI Summit in Oslo will showcase how Norwegian business leaders utilize AI for company transformation. The event includes expert talks, such as by Simplifai’s Erik Leung, and discussions on practical AI applications, aiming to bridge the understanding between engineers and decision-makers. Networking opportunities with key AI figures are also highlighted.
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5 Code Optimization Techniques To Speed Up Your Programs
Improve code efficiency with these five language-agnostic methods: extract loop-invariants to reduce CPU cycles; use enums instead of strings for state representation to avoid errors and enhance performance; replace conditional statements with algebraic or boolean operations when possible; utilize memoization to store function outputs for repeated calls; and select the optimal data structure for your…
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Scientists use AI to find an equation to predict rogue waves
Scientists from universities in Victoria and Copenhagen applied AI to the Free Ocean Wave Dataset, successfully predicting rogue waves using a neural network. Employing symbolic regression, they derived an equation revealing the causal factors of these waves, aiding forecasts and enhancing maritime safety.
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This AI Research from China Introduces GS-SLAM: A Novel Approach for Enhanced 3D Mapping and Localization
Researchers from various universities in China and Hong Kong developed GS-SLAM, a 3D Gaussian-based SLAM system, to balance accuracy with efficiency. It uses innovative rendering and adaptive strategies to enhance pose tracking, demonstrating competitive performance on standard datasets. GS-SLAM offers improvements in dense visual SLAM, but faces challenges with memory usage and dependency on high-quality…
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Revolutionizing Digital Art: Researchers at Seoul National University Introduce a Novel Approach to Collage Creation Using Reinforcement Learning
Seoul National University researchers have advanced AI in art by training an AI agent to create authentic collages via reinforcement learning. Their model eschews pixel-based methods for a process that mirrors human techniques, showing promise in crafting AI-generated art with depth and creativity as confirmed by user studies and CLIP-based assessments.
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This AI Research Introduces GAIA: A Benchmark Defining the Next Milestone in General AI Proficiency
GAIA, a benchmark by FAIR Meta and partners, tests AI assistants on real-world tasks that demand reasoning and multi-modal skills. It evaluates LLMs with practical, non-gameable questions reflecting actual use cases, aiming to bridge the gap between AI and human performance. GAIA benchmarks show humans outperforming GPT-4, guiding future AI advancements.
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Amazon Unveils Q: A Generative AI Chatbot that can be Tailored Specifically to a Business
Amazon Q, an AI-powered assistant by AWS, offers customized support tailored to specific business needs and workflows, with high security and privacy standards. It assists developers with AWS insights, automates feature development, integrates with company systems, and offers administrative control, enhancing workplace productivity and innovation.
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Researchers from Meta AI Introduce Style Tailoring: A Text-to-Sticker Recipe to Finetune Latent Diffusion Models (LDMs) in a Distinct Domain with High Visual Quality
Researchers from Meta AI introduced “Style Tailoring,” improving Latent Diffusion Models (LDMs) for sticker generation with better visual quality, alignment, and diversity. It employs multi-stage fine-tuning, human-in-the-loop adjustments, and achieves 14-16.2% enhancements over the base Emu model, with room for broader research applications.