Artificial Intelligence
As an oncologic surgeon and AI researcher, I observe a growing gap between clinical practice and AI research. Despite the disruptive potential of AI in healthcare, the lack of clinician involvement and top-down market strategies hinder its effectiveness. To truly innovate in healthcare, we need an interdisciplinary approach and a new generation of doctors skilled…
A series of experiments published in Nature Communications showed evidence of systematic influence on human judgments by adversarial perturbations.
In 2023, advancements in NLP saw the emergence of ChatGPT and other Large Language Models, making fine-tuning LLMs easier. The demand for personalized RAGs surged across industries, with a need for tailored solutions. Techniques to enhance RAG efficiency include enhancing data quality, optimizing index structure, adding metadata, aligning query with documents, mixed retrieval, ReRank, prompt…
The text discusses the growing significance of software in the landscape of Large Language Models (LLMs) and outlines emerging libraries and frameworks enhancing LLM performance. It emphasizes the critical challenge of reconciling software and hardware optimizations for LLMs and highlights specific software tools and libraries catering to LLM deployment. Emerging hardware and memory technologies are…
Nobel laureate Sir Christopher Pissarides cautions against rushing into STEM education due to AI’s impact on job markets. He emphasizes AI’s potential to replace STEM jobs and suggests a shift towards roles requiring empathy and creativity. Pissarides is part of The Institute for the Future of Work, aiming to navigate the changes AI brings to…
TinyGPT-V is a novel multimodal large language model aiming to balance high performance with reduced computational needs. It integrates a 24G GPU for training and an 8G GPU/CPU for inference, leveraging Phi-2 language backbone and pre-trained vision modules for efficiency. The unique architecture delivers impressive results, showcasing promise for real-world applications.
Recent advances in AI and NLP have led to the development of KwaiAgents, an information-seeking agent system based on Large Language Models (LLMs). It comprises KAgentSys, KAgentLMs, and KAgentBench, demonstrating improved performance compared to existing open-source systems. Additionally, the Meta-Agent Tuning framework ensures effective performance with less sophisticated LLMs.
Matthew Candy, IBM’s global managing partner for generative AI, predicts that a computer science degree may soon be unnecessary in the tech industry, with AI enabling non-coders to innovate. He highlights a shift towards creativity and innovation over technical expertise but acknowledges concerns about job redundancy due to AI advancements. This signals a significant change…
Researchers at the University of Science and Technology of China have introduced “City-on-Web,” a method to render large scenes in real-time by partitioning scenes into blocks and employing varying levels-of-detail (LOD). This approach enables efficient resource management, reducing bandwidth and memory requirements, and achieves high-fidelity rendering at 32 FPS with minimal GPU usage.
Vector databases, originating from 1960s information retrieval concepts, have evolved to manage diverse data types, aiding Large Language Models (LLMs). They offer foundational data management, real-time performance, application productivity, semantic understanding integration, high-dimensional indexing, and similarity search. In FMOps/LLMOps, they support semantic search, long-term memory, architecture, and personalization, forming a crucial aspect of efficient data…
Stable Diffusion in Java (SD4J) leverages deep learning to transform text into vibrant images, with the ability to handle negative inputs. Its Graphical User Interface simplifies image generation, and integration with ONNXRuntime-Extensions enhances functionality. Users can fine-tune guidance scales and seed for granular control, while leveraging pre-built models from Hugging Face. The tool simplifies text-to-image…
The LASER approach, introduced by researchers from MIT and Microsoft, revolutionizes the optimization of large language models (LLMs) by selectively targeting higher-order components of weight matrices for reduction. This innovative technique improves model efficiency and accuracy without additional training, expanding LLMs’ capabilities in processing nuanced data. LASER signifies a significant advancement in AI and language…
Machine Learning and Artificial Intelligence have revolutionized autonomous agent technology. However, a significant challenge is agents’ tendency to operate in isolation, limiting their efficiency and learning process. Researchers from Chinese universities introduced ‘Experiential Co-Learning,’ revolutionizing autonomous software-developing agents’ capabilities by integrating past experiences into their operational fabric. The framework significantly improves agent autonomy, collaborative efficiency,…
A Python library called Pyfiber, developed by researchers from the University of Bordeaux and UCL Sainsbury Wellcome Centre, seamlessly integrates fiber photometry with complex behavioral paradigms in behavioral neuroscience research. It offers versatility, ease of use, and robust analytical capabilities, providing a transformative tool for exploring the brain-behavior relationship. [Summary: 50 words]
Meta has developed HawkEye, a powerful toolkit addressing the complexities of debugging and monitoring in machine learning. It streamlines the identification and resolution of production issues, enhancing the quality of user experiences and monetization strategies. HawkEye’s decision tree-based approach significantly reduces debugging time, empowering a broader range of users to efficiently address complex issues.
The rise of AI assistants, such as ChatGPT, raises questions about the teaching of coding skills. While AI can help with writing code, it may hinder students’ deep engagement and understanding of concepts. Educators should embrace AI assistants, but also focus on teaching critical thinking, problem framing, and quality evaluation. Integrating AI into the curriculum…
The text discusses methods to boost the performance of fine-tuned models, particularly Large Language Models (LLMs) using Reinforcement Learning from Human Feedback (RLHF) and Direct Preference Optimization (DPO). It details the formatting of preference datasets, training the model with DPO, and evaluating the performance of the model. The process results in the creation of a…
The text discusses the challenges of using one-hot encoding for handling large categorical data and introduces a solution through the use of embeddings, addressing memory requirements and computational complexity. It details methods for reducing memory footprint, including dimension reduction, hashing, and the quotient-remainder trick, as well as their implementation in TensorFlow. The author also shares…
Margrethe Vestager defended the proposed AI Act in a Financial Times interview, emphasizing its provision of legal certainty for technology startups. The Act has faced criticism from French President Macron, who warned of over-regulation risks. Vestager argued that the Act would promote innovation and research in the EU. The legislation awaits ratification by EU member…
Researchers at the University of Bonn, led by Prof. Dr. Jürgen Bajorath, have discovered that ‘black box’ AIs in pharmaceutical research rely on recalling existing data rather than learning new chemical interactions, challenging previous assumptions. The study focuses on Graph Neural Networks (GNNs) and suggests improved training techniques could enhance their performance. Prof. Bajorath advocates…