Large language model
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…
The article discusses the importance of understanding computer vision and building a Convolutional Neural Network (CNN) from scratch using Python library Numpy. It covers the main components of a CNN, such as convolutional layers and pooling layers, and provides Python implementations for these layers. The article also includes code examples and references for further learning.
Psychologists are studying the use of EEG to explore how games provide insights into our capacity for teamwork.
Microsoft Research has introduced Florence-2, a vision foundation model that aims to achieve a unified prompt-based representation for various computer vision and vision-language tasks. It addresses challenges related to spatial hierarchy and semantic granularity by integrating spatial, temporal, and multi-modal features. The model achieves state-of-the-art performance in tasks such as referencing expression comprehension, visual grounding,…
This text discusses a method for segmenting product features into Core, Power, and Casual categories based on retention rates. The author emphasizes the importance of considering both the qualitative (value) and quantitative (popularity) metrics when analyzing feature retention. By applying percentile thresholds, the author identifies nine clusters of product features and provides insights on each…
Nvidia reported a historic high third-quarter revenue of $18.12 billion, surpassing predictions and driving its market cap to $1.22 trillion. The company experienced significant growth in gaming revenue and data center revenue, as well as gains in its Professional Visualization and Automotive business units. Despite US export restrictions, Nvidia remains confident in its ability to…
The GPT-Vision model, which has generated excitement for its ability to understand and generate content related to text and images, lacks a clear understanding of its strengths and limitations. To address this, researchers from the University of Pennsylvania have proposed a new evaluation method inspired by social science and human-computer interaction. This method involves five…
MIT researchers have developed PockEngine, a technique that allows deep-learning models to be fine-tuned directly on edge devices. This eliminates the need for sending user data to cloud servers and improves privacy, customization options, and cost-effectiveness. PockEngine has shown impressive speed improvements and memory savings, making on-device fine-tuning more accessible.
Alibaba researchers have developed Qwen-Audio, a series of large-scale audio-language models that address the challenge of limited pre-trained audio models. Qwen-Audio achieves impressive performance across diverse benchmark tasks without task-specific fine-tuning. Qwen-Audio-Chat extends these capabilities to support multi-turn dialogues and diverse audio scenarios. The models demonstrate robust audio understanding and alignment with human intent. Further…
Claude.ai, developed by Anthropic, has released an upgraded version called Claude 2.1. The major improvement is the doubling of its context window, now at 200,000 tokens, making it the largest in the industry. While it performs well, accuracy in recalling information decreases as the context grows longer. Other features of Claude 2.1 include increased accuracy,…
A study by UC Berkeley and Shanghai Jiao Tong University highlights the challenges in evaluating language models due to contaminated datasets. Conventional decontamination techniques are flawed, prompting the researchers to propose a new approach using rephrased samples and embedding similarity search. The study emphasizes the need for more thorough decontamination procedures and suggests new tests…
Researchers from the University of Pennsylvania, the University of Washington, and Tencent AI Lab have developed a sub-sentence encoder, an embedding model that generates distinct embeddings for atomic propositions within a text sequence. The model focuses on fine-grained semantic representation and is effective in tasks like retrieving supporting facts and recognizing conditional semantic similarity. It…
Scientists have discovered that by imposing physical constraints on artificial intelligence systems, similar to how the human brain functions within physical and biological limits, these systems can develop characteristics found in the brains of complex organisms, helping them to solve tasks effectively.
US Ambassador to India, Eric Garcetti, emphasized the importance of deeper conversations between India and the US on artificial intelligence (AI). He called for a comprehensive regulatory framework to prevent catastrophic consequences and stressed the urgency of staying ahead in the AI field. Garcetti highlighted the need for bilateral efforts and collaboration on defense, technology,…
The decision to fire Sam Altam from OpenAI may have been influenced by the effective altruistic ideals of the board members. Interim CEO Emmett Shear shares concerns about AI. Some board members align with the concept of Effective Altruism (EA) and its fears regarding AI development. Shear supports the views of the EA community, including…
In a surprising turn of events, Sam Altman is set to be reinstated as the CEO of OpenAI. The drama started when Altman was removed for a lack of candor in his communications. This led to Altman and co-founder Greg Brockman planning to join Microsoft, while OpenAI employees threatened to leave. OpenAI has now formed…