Amazon SageMaker Canvas is a no-code environment that allows users to easily utilize machine learning (ML) models for various data types. It integrates with Amazon Comprehend for natural language processing tasks like sentiment analysis and entity recognition. It also integrates with Amazon Rekognition for image analysis, and Amazon Textract for document analysis. The ready-to-use solutions…

The text discusses the challenges of evaluating language models and proposes using language models to evaluate other language models. It introduces several metrics and evaluators that rely on language models, including G-Eval, FactScore, and RAGAS. These metrics aim to assess factors such as coherence, factual precision, faithfulness, answer relevance, and context relevance. While there are…

The Vision Transformer (ViT) model is a groundbreaking approach to image recognition that transforms images into sequences of patches and applies Transformer encoders to extract insights. It surpasses traditional CNN models by leveraging self-attention mechanisms and sequence-based processing, offering superior performance and computational efficiency. ViT presents new possibilities for complex visual tasks, making it a…

A recent study evaluated the performance of GPT-4V, a multimodal language model, in handling complex queries that require both text and visual inputs. While GPT-4V has potential in enhancing natural language processing and computer vision applications, it is not suitable for practical medical diagnostics due to unreliable and suboptimal responses. The study highlights the need…

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…

This text provides smart tips for efficient data labeling using the Clarifai Platform.

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…

The winners of the AI DevWorld Hackathon for building the most interesting Clarifai projects have been announced.

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…

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…