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Researchers from Stanford Introduce RT-Sketch: Elevating Visual Imitation Learning Through Hand-Drawn Sketches as Goal Specifications
Researchers at Stanford University have introduced RT-Sketch, a goal-conditioned manipulation policy that uses hand-drawn sketches as a more precise and abstract alternative to natural language and goal images in visual imitation learning. RT-Sketch demonstrates robust performance in various manipulation tasks, outperforming language-based agents in scenarios with ambiguous goals or visual distractions. The study highlights the…
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7 Tips for Efficient Data Labeling
This text provides smart tips for efficient data labeling using the Clarifai Platform.
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31 Countries endorse US guardrails for military use of AI
During the AI Safety Summit in the UK, US VP Kamala Harris announced that 30 countries have joined the US in endorsing its proposed guidelines for the military use of AI. The “Political Declaration on Responsible Military Use of Artificial Intelligence and Autonomy” was posted on the US Department of State website, with additional details…
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Meet the Clarifai Winners of the AI DevWorld Hackathon
The winners of the AI DevWorld Hackathon for building the most interesting Clarifai projects have been announced.
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This AI Paper from China Introduces a Novel Time-Varying NeRF Approach for Dynamic SLAM Environments: Elevating Tracking and Mapping Accuracy
Researchers from China have introduced a new framework called TiV-NeRF for simultaneous localization and mapping (SLAM) in dynamic environments. By leveraging neural implicit representations and incorporating an overlap-based keyframe selection strategy, this approach improves the reconstruction of moving objects, addressing the limitations of traditional SLAM methods. While promising, further evaluation on real-world sequences is necessary…
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UCSD Researchers Evaluate GPT-4’s Performance in a Turing Test: Unveiling the Dynamics of Human-like Deception and Communication Strategies
The researchers from UCSD conducted a Turing Test using GPT-4. The best performing prompt from GPT-4 was successful in 41% of the games, outperforming ELIZA, GPT-3.5, and random chance. The test revealed that participants judged primarily on language style and social-emotional qualities. The Turing Test remains useful for studying spontaneous communication and deceit. However, the…
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AI Transforming Computer Use and Software Industry, Says Bill Gates
Bill Gates believes that artificial intelligence (AI) will revolutionize computing and reshape the software industry. He envisions AI-driven agents that understand and respond to natural language and can perform tasks across multiple applications. These agents will learn from users’ preferences and behavior patterns, acting as personal assistants for tasks ranging from travel planning to healthcare…
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Reconciling the Generative AI Paradox: Divergent Paths of Human and Machine Intelligence in Generation and Understanding
The latest wave of generative AI, from ChatGPT to GPT4 to DALL-E 2/3 to Midjourney, has attracted global attention. These models exhibit superhuman capabilities but also make fundamental comprehension mistakes. Researchers propose the Generative AI Paradox hypothesis, suggesting that generative models can be more creative than humans because they are trained to produce expert-like outputs…
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[SOLVED] Authorization Error Accessing Plugins in ChatGPT
The post discusses a common error that some users encounter when using ChatGPT plugins, which is the “Authorization error accessing plugins.” It provides a step-by-step guide on how to solve this error, including clearing the browser cache and data, uninstalling and reinstalling the plugins, using a VPN, switching browsers, and contacting the plugin developer for…
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Google AI Introduces a Novel Clustering Algorithm that Effectively Combines the Scalability Benefits of Embedding Models with the Quality of Cross-Attention Models
The KwikBucks algorithm combines embedding models with cross-attention models for efficient and high-quality clustering. It uses the embedding model to guide queries to the cross-attention model, conserving resources. The algorithm identifies centers and creates clusters based on them, merging clusters with strong connections. The algorithm outperformed baseline algorithms in tests on different datasets. (50 words)