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…
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…
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…
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…
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)
Researchers from NVIDIA and UT Austin have developed MimicGen, an autonomous data generation system for robotics. With just 200 human demonstrations, MimicGen generated a large multi-task dataset of over 50,000 demonstrations. This system can help train robots without the need for extensive human work, making it a valuable tool in robotics research and development.
Nvidia’s Eos AI supercomputer, equipped with 10,752 NVIDIA H100 Tensor Core GPUs, achieved new MLPerf AI training benchmark records. It successfully trained a GPT-3 model with 175 billion parameters on one billion tokens in just 3.9 minutes, compared to nearly 11 minutes previously. The improved processing power and efficiency indicate significant advancements in AI technology.
kscorer is a package that helps with clustering and data analysis through advanced scoring and parallelization. It offers techniques such as dimensionality reduction, cosine similarity, multi-metric assessment, and data sampling to determine the optimal number of clusters. The package also provides evaluation metrics like Silhouette Coefficient, Calinski-Harabasz Index, Davies-Bouldin Index, Dunn Index, and Bayesian Information…
The introduction of Large Language Models (LLMs) has been a significant advancement in Artificial Intelligence. These models face unique challenges in the finance industry but have seen progress in financial text summarization, stock price predictions, financial report production, news sentiment analysis, and financial event extraction. However, in the Chinese financial market, LLMs lack an in-depth…
This week’s AI news roundup includes various interesting developments. Pepsico has used AI to silence the crunch of Doritos for gamers. Steak-umm gaslit vegans with fake videos. AI-generated fake nudes caused issues in a New Jersey school. Meta now requires labeling of AI-generated ads due to the ease with which humans are tricked. There is…
New research by CAS, Microsoft, William & Mary, Beijing Normal University, and HKUST explores the relationship between Emotional Intelligence (EQ) and large language models (LLMs). The study investigates whether LLMs can interpret emotional cues and how emotional stimuli can improve their performance. The researchers developed EmotionPrompt, a method for investigating LLMs’ emotional intelligence, and found…
Large Language Models (LLMs) have gained popularity for their text generation and language understanding capabilities. However, their adoption is challenging due to the large memory requirements. Intel researchers propose using quantization methods to reduce computational power on CPUs. Their approach includes INT-4 weight-only quantization and a specialized LLM runtime for efficient inference. Experimental results show…
“Intelligent Model Architecture Design (MAD)” explores the idea of using generative AI to guide researchers in designing more effective and efficient deep learning model architectures. By leveraging techniques like Neural Architecture Search (NAS) and graph-based approaches, MAD aims to accelerate the discovery of new breakthroughs in model architecture design. The potential implications of self-improvement in…
LLM-based applications, powered by Large Language Models (LLMs), are becoming increasingly popular. However, as these applications transition from prototypes to mature versions, it’s important to have a robust evaluation framework in place. This framework will ensure optimal performance and consistent results. Evaluating LLM-based applications involves collecting data, building a test set, and measuring performance using…