Purdue University researchers have introduced a novel approach using topological data analysis (TDA) to interpret complex prediction models, including machine learning and neural networks. They leveraged TDA to construct Reeb networks, providing a topological view that aids interpretation. The method was successfully applied to various domains and showcased its scalability across large datasets, with applications…
Microsoft Research and Tsinghua University researchers have introduced a new approach called Skeleton-of-Thought (SoT) to address the sluggish processing speed of Large Language Models (LLMs) like GPT-4 and LLaMA. SoT refrains from making extensive changes to the LLMs themselves and focuses on optimizing the organization of their output content. By prompting LLMs to construct a…
A new AI software can accurately analyze complex cuneiform texts using 3D models of the tablets, leading to more reliable results compared to previous methods. This enables researchers to compare and search through multiple tablets and opens up new avenues for research.
Nvidia researchers have developed Tied-LoRA, a technique that enhances the parameter efficiency of the Low-rank Adaptation (LoRA) method. By using weight tying and selective training, Tied-LoRA achieves an optimal balance between performance and trainable parameters. Experimental results show trade-offs between efficiency and performance, with a specific Tied-LoRA configuration achieving comparable performance with only 13% of…
Researchers have developed a new method called Drivable 3D Gaussian Avatars (D3GA) for rendering realistic human bodies. Using Gaussian splats instead of radiance fields, the method accurately represents human appearance and deformations. It eliminates the need for extensive pre-processing and achieves high-quality results without requiring ground truth geometry. The research outperforms current methods and reduces…
The Federal Trade Commission (FTC) has expanded its powers to investigate the AI industry. This includes the use of civil investigative demands (CIDs) to gather information relevant to the investigation. Non-compliance with CIDs can lead to legal consequences. The FTC is also focusing on algorithmic fairness and transparency in AI systems. FTC chair Lina Khan…
“The Book of Why” Chapters 3&4 are part of the Read with Me series and can be found on Towards Data Science.
Scientists at the McGovern Institute for Brain Research at MIT, the Broad Institute of MIT and Harvard, and the National Center for Biotechnology Information have developed a new search algorithm called FLSHclust that allows for more efficient searching of microbial sequence databases. The algorithm identified 188 new rare CRISPR systems in bacterial genomes, revealing a…
Meta has proposed a new approach called System 2 Attention (S2A) to address the issue of bias and irrelevant context in large language models (LLMs). S2A uses natural language processing to refine the original prompt, stripping out bias and irrelevant information before generating a response. The results show impressive improvements in accuracy, particularly in factual…
The value of data lies in its ability to bring about tangible positive change. Leveraging data can help solve complex business decisions and improve everyday routines. Here are some recent favorite articles that demonstrate the practical role of data in different areas, such as survival analysis, decision trees, personal habit tracking, customer lifetime value modeling,…
Lincoln Laboratory is focused on reducing energy consumption in AI models through improved transparency and more efficient training methods.
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OpenAI-Altman saga continues with the firing of Sam Altman. Sources suggest that the reason behind his dismissal is an AI model known as Q*, which is believed to be powerful enough to threaten humanity. Q* combines elements of Q-learning and A* search algorithms and is optimized through Reinforcement Learning from Human Feedback. However, the claims…
Elon Musk has announced the upcoming release of Grok, xAI’s new chatbot, for X Premium+ subscribers. This integration with X signifies Musk’s larger vision for the platform, aiming to transform it into a versatile application. Grok stands out with its ability to stay updated on current events and trends, as well as its user-friendly and…
Real AI has been chosen to build Europe’s first-ever Human-Centered LLM on the LEONARDO AI Computer Cluster. LEONARDO is the fourth largest AI cluster in the world and Real AI aims to provide responsible AI development by collaborating with UNINA and LEONARDO. The project, called HOMINIS, aims to revolutionize AI by creating ethical, bias-free systems…
A Finnish AI startup called Poro has developed an open-source language model designed to cover all 24 official languages of the European Union. Poro uses cross-lingual training and has 34.2 billion parameters. It outperforms existing models for Finnish and aims to match or surpass English performance. The startup believes that Poro is important for digital…
Mirasol3B is a multimodal autoregressive model developed by Google that addresses the challenges of machine learning across different modalities. It uses a unique architecture to handle time-aligned and non-aligned modalities, such as video, audio, and text. The model achieves impressive performance by employing cross-attention mechanisms and intelligent partitioning of video inputs. Mirasol3B outperforms other models…
This article discusses the importance of effective management of big data in cloud-based storage solutions. It introduces the rclone command-line utility as a tool for cloud-based storage management and compares its performance to other tools. The article also highlights the capability of rclone for transferring data between different object storage systems, providing a convenient and…
Decision trees are often replaced with random forests, but this prioritizes a “black box” algorithm. Decision trees provide intuitive results and allow for trade-off comparisons and process improvement. To improve decision tree performance, principal component analysis (PCA) can be applied to optimize feature data and reduce the feature space. This improves performance and generalizability.
The research paper discusses the latent space of diffusion models in Artificial Intelligence and Machine Learning, particularly in the context of image modification. The authors propose integrating local geometry into the latent space using the pullback metric from Riemannian geometry. This enables image editing at specific timesteps without additional training. The study explores the evolution…