Artificial Intelligence
Large Language Models (LLMs) are pivotal in AI development, but traditional training methods faced limitations. Researchers at FAIR introduced the innovative Branch-Train-Mix (BTX) strategy, combining parallel training and Mixture-of-Experts model to enhance LLM capabilities efficiently and maintain adaptability. It demonstrated superior domain-specific performance without significant increase in computational demand. This marks a significant advancement in…
Spotify has added audiobooks to its platform, requiring new recommendation methods. The 2T-HGNN model uses a Two Tower (2T) architecture and Heterogeneous Graph Neural Networks (HGNN) to analyze user interests and enhance recommendations. This has led to a 23% increase in streaming rates and a 46% rise in starting new audiobooks, addressing data distribution imbalances…
Devin, created by Cognition AI, is the world’s first autonomous AI software engineer, setting a new benchmark in software engineering. With advanced capabilities, it operates autonomously, collaborates on tasks, and tackles complex coding challenges, showing potential to reshape the industry. Its groundbreaking performance on the SWE-Bench benchmark signifies a monumental shift in software development.
Large language models (LLMs) like GPT have revolutionized scientific research, particularly in materials science. Researchers from Imperial College London have shown how LLMs automate tasks and streamline workflows, making intricate analyses more accessible. LLMs’ potential in interpreting research papers, automating lab tasks, and creating datasets for computer vision is profound, though challenges like inaccuracies and…
AI technologies are revolutionizing programming, as AI-generated code becomes more accurate. This article discusses AI tools like OpenAI Codex, Tabnine, CodeT5, Polycoder, and others that are transforming how programmers create code. These tools support various languages and environments, empowering developers to write better code more efficiently.
A groundbreaking approach targeting black-box language models has been introduced, allowing for the recovery of a transformer language model’s complete embedding projection layer. Despite the efficacy of the attack and its application to production models, further improvements and extensions are anticipated. Emphasis is placed on addressing vulnerabilities and enhancing the resilience of machine learning systems.
Advanced language models have transformed NLP, enhancing machine understanding and language generation. Researchers have played a significant role in this transformation, spurring various AI applications. Methodological innovations and efficient training have significantly improved language model efficiency. These algorithmic advancements have outpaced hardware improvements, emphasizing the crucial role of algorithmic innovations in shaping the future of…
Google DeepMind researchers have developed Multistep Consistency Models, merging them with TRACT and Consistency Models to narrow the performance gap between standard diffusion and few-step sampling. The method offers a trade-off between sample quality and speed, achieving superior performance in just eight steps, improving efficiency in generative modeling tasks.
ELLA, a new method discussed in a Tencent AI paper, enhances text-to-image diffusion models by integrating powerful Large Language Models (LLMs) without requiring retraining. It improves comprehension of intricate prompts by introducing the Timestep-Aware Semantic Connector (TSC) and effectively addressing dense prompts. ELLA promises significant advancement in text-to-image generation without extensive retraining. For more details,…
Research in 3D generative AI has led to a fusion of 3D generation and reconstruction, notably through innovative methods like DreamFusion and the TripoSR model. TripoSR, developed by Stability AI and Tripo AI, uses a transformer architecture to rapidly generate 3D models from single images, offering significant advancements in AI, computer vision, and computer graphics.
A groundbreaking approach called Strongly Supervised pre-training with ScreenShots (S4) is introduced to enhance Vision-Language Models (VLMs) by leveraging web screenshots. S4 significantly boosts model performance across various tasks, demonstrating up to 76.1% improvement in Table Detection. Its innovative pre-training framework captures diverse supervisions embedded within web pages, advancing the state-of-the-art in VLMs.
Recent studies have highlighted the advancements in Vision-Language Models (VLMs), exemplified by OpenAI’s GPT4-V. These models excel in vision-language tasks like captioning, object localization, and visual question answering. Apple researchers assessed VLM limitations in complex visual reasoning using Raven’s Progressive Matrices, revealing discrepancies and challenges in tasks involving visual deduction. The evaluation approach, inference-time techniques,…
Advancements in large language models (LLMs) have impacted various fields, yet the legal domain lags behind. Equall.ai’s researchers introduce SaulLM-7B, a public legal LLM specialized for legal text, leveraging extensive pretraining on dedicated legal corpora. It outperforms non-legal models on legal-specific tasks, presenting opportunities for further enhancement in conclusion tasks. Full paper available here.
AI’s pervasive role has raised concerns about the amplification of biases. A recent study reveals covert racism in language models, particularly in their negative associations with African American English (AAE) speakers. The research emphasizes the pressing need for novel strategies to address linguistic prejudice and ensure equitable AI technology. Read the full post on MarkTechPost.
Peking University and Alibaba Group developed FastV to tackle inefficiencies in Large Vision-Language Models’ attention computation. FastV dynamically prunes less relevant visual tokens, significantly reducing computational costs without compromising performance. This improves the computational efficiency and practical deployment of LVLMs, offering a promising solution to resource constraints in real-world applications.
Researchers have encountered significant challenges in developing drugs for Idiopathic Pulmonary Fibrosis and renal fibrosis due to their complex pathogenesis and lack of effective treatments. However, utilizing AI, they identified TNIK as a promising anti-fibrotic target and developed the inhibitor INS018_055, showing favorable properties and efficacy in preclinical and clinical studies. This innovative approach offers…
The demand for advanced, scalable, and versatile tools in software development continues to grow. Meeting these demands requires overcoming significant challenges such as handling vast amounts of data and providing flexible, user-friendly interfaces. C4AI Command-R, a groundbreaking 35-billion parameter generative model developed by Cohere and Cohere For AI, effectively addresses these challenges with its unique…
In data science and AI, embedding entities into vector spaces enables numerical representation, but a study by Netflix Inc. and Cornell University challenges the reliability of cosine similarity, revealing its potential for arbitrary and misleading results. Regularization impacts similarity outcomes, highlighting the need to critically evaluate such metrics and consider alternative approaches.
The Large Language Models (LLMs) have remarkable capabilities in various domains like content generation, question-answering, and mathematical problem-solving, challenging the need for extensive pre-training. A recent study demonstrates that the LLaMA-27B model displays outstanding mathematical abilities and proposes a supervised fine-tuning method to enhance accuracy, offering insights into scaling behaviors. The study’s findings suggest that…
We’ve teamed up with Le Monde and Prisa Media to provide French and Spanish news content for ChatGPT.