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“Prompt Engineering, AI Agents, and LLMs: Kick-Start a New Year of Learning” sets the tone for the new year, introducing thought-provoking articles. Sheila Teo’s GPT-4 Competition win and Oren Matar’s ChatGPT review offer insights. Mariya Mansurova discusses LLM-Powered Analysts, while Heston Vaughan and others delve into AI agents and music AI breakthroughs. The newsletter also […] ➡️➡️➡️

The researchers propose DL3DV-10K as a solution to the limitations in Neural View Synthesis (NVS) techniques. The benchmark, DL3DV-140, evaluates SOTA methods across diverse real-world scenarios. The potential of DL3DV-10K in training generalizable Neural Radiance Fields (NeRFs) is explored, highlighting its significance in advancing 3D representation learning. The work influences the future trajectory of NVS […] ➡️➡️➡️

Microsoft recently added a new AI key to their keyboards for Windows 11 PCs. The key enables the use of Copilot, an AI tool for tasks like searching, email writing, and image creation. This move reflects Microsoft’s growing integration of AI in their products and partnerships with OpenAI. Yusuf Mehdi foresees AI transforming computer usage […] ➡️➡️➡️

The development of Large Language Models (LLMs) like GPT and BERT presents challenges in training due to computational intensity and potential failures. Addressing the need for efficient management and recovery, Alibaba and Nanjing University researchers introduce Unicron, which enhances LLM training resilience through innovative features, including error detection, cost-efficient planning, and efficient transition strategies, achieving […] ➡️➡️➡️

The text discusses the importance of spotting new trends and the various methods to identify them early. It covers tools such as Exploding Topics, utilizing YouTube, discovering mega trends through data, public domain opportunities, and sports industry trends. It emphasizes the need for a game plan to capitalize on trends and invites readers to join […] ➡️➡️➡️

A new study proposes a three-step system to evaluate artificial intelligence’s ability to reason like a human, acknowledging the limitations of the Turing test due to AI’s capacity to imitate human responses. ➡️➡️➡️

In 2023, predictions about the future of AI, Big Tech, and AI’s impact on industries were partly accurate. Looking forward to 2024, specific trends include the rise of customized chatbots for non-tech users, advancements in generative video models, the spread of AI-generated election disinformation, and the development of robots with multitasking abilities. ➡️➡️➡️

A group of researchers led by Prof. Qu Kun has developed SPACEL, a deep-learning toolkit consisting of Spoint, Splane, and Scube modules, to overcome limitations in spatial transcriptomics analysis. By accurately predicting cell types, identifying spatial domains, and constructing 3D tissue architecture, SPACEL outperforms existing techniques, offering a powerful solution for comprehensive spatial transcriptomic analysis. ➡️➡️➡️

Large Language Models (LLMs) have revolutionized processing multimodal information, leading to breakthroughs in multiple fields. Prompt engineering, introduced by researchers at MBZUAI, focuses on optimizing prompts for LLMs. Their study outlines 26 principles for crafting effective prompts, emphasizing conciseness, context relevance, task alignment, and advanced programming-like logic to improve LLMs’ responses. ➡️➡️➡️

The article explores the intersection of philosophy and data science, focusing on causality. It delves into different philosophical theories of causality, such as deterministic vs probabilistic causality, regularity theory, process theory, and counterfactual causation. The author emphasizes the importance of understanding causality in data science to provide valuable recommendations. ➡️➡️➡️

Large Language Models (LLMs) are crucial in enabling machines to understand and generate human-like text. The open-source frameworks for LLM application development include LangChain, Chainlit, Helicone, LLMStack, Hugging Face Gradio, FlowiseAI, LlamaIndex, Weaviate, Semantic Kernel, Superagent, and LeMUR. These frameworks offer diverse tools to simplify LLM application development, enhancing flexibility, transparency, and usability. ➡️➡️➡️

Nvidia researchers developed TSPP, a benchmarking tool for time series forecasting in finance, weather, and demand prediction. It standardizes machine learning evaluation, integrates all lifecycle phases, and demonstrates the effectiveness of deep learning models. TSPP offers efficiency and flexibility, marking a significant advance in accurate forecasting for real-world applications. [50 words] ➡️➡️➡️

The text can be summarized as follows: The article discusses the use of LoRA (Low-Rank Adaptation) for fine-tuning language models. The summary highlights the practical strategies for achieving good performance and parameter efficiency using LoRA. It also addresses the impact of hyperparameters and design decisions on performance, GPU memory utilization, and training speed. The article […] ➡️➡️➡️

Researchers from the University of Georgia and Mayo Clinic tested the proficiency of Large Language Models (LLMs), particularly OpenAI’s GPT-4, in understanding biology-related questions. GPT-4 outperformed other AI models in reasoning about biology, scoring an average of 90 on 108 test questions. The study highlights the potential applications of advanced AI models in biology and […] ➡️➡️➡️

The article “On the Statistical Analysis of Rounded or Binned Data” discusses the impact of rounding or binning on statistical analyses. It explores Sheppard’s corrections and the total variation bounds on the rounding error in estimating the mean. It also introduces bounds based on Fisher information. The article highlights the importance of addressing errors when […] ➡️➡️➡️

CMU’s research addresses the challenge of noisy evaluations in Federated Learning’s hyperparameter tuning. It introduces the one-shot proxy RS method, leveraging proxy data to enhance tuning effectiveness in the face of data heterogeneity and privacy constraints. The innovative approach reshapes hyperparameter dynamics and holds promise in overcoming complex FL challenges. ➡️➡️➡️

The article emphasizes the importance of text embeddings in NLP tasks, particularly referencing the use of embeddings for information retrieval and Retrieval Augmented Generation. It highlights recent research by Microsoft Corporation, presenting a method for producing high-quality text embeddings using synthetic data. The approach is credited with achieving remarkable results and eliminating the need for […] ➡️➡️➡️

Researchers from UCLA and Snap Inc. have developed “Dual-Pivot Tuning,” a personalized image restoration method. This approach uses high-quality images of an individual to enhance restoration, aiming to maintain identity fidelity and natural appearance. It outperforms existing methods, achieving high fidelity and natural quality in restored images. For more information, refer to the researchers’ paper […] ➡️➡️➡️

The text discusses the misuse of AI leading to a reproducibility crisis in scientific research and technological applications. It explores the fundamental issues contributing to this detrimental effect and highlights the challenges specific to AI-based science, such as data quality, modeling transparency, and risks of data leakage. The article also suggests standards and solutions to […] ➡️➡️➡️