​ Large language models (LLMs) are excelling at pretty much all NLP tasks. However, traditional fine-tuning methods are costly for LLMs, leading to the development of continuous prompt-tuning techniques that use trainable prompt embeddings without modifying LLM parameters. However, these methods still require access to… Read More »This AI Research by Microsoft and Tsinghua University Introduces EvoPrompt: A Novel AI Framework for Automatic Discrete Prompt Optimization Connecting LLMs and Evolutionary Algorithms Janhavi Lande Artificial Intelligence Category – MarkTechPost

​ By dramatically improving state-of-the-art performance across a wide range of tasks and revealing new emergent skills, large language models (LLMs) have profoundly impacted NLP research and applications. To encode input texts into representation vectors, the encoder-only models have been investigated; to create texts, the… Read More »Researchers from the University of Oregon and Adobe Introduce CulturaX: A Multilingual Dataset with 6.3T Tokens in 167 Languages Tailored for Large Language Model (LLM) Development Dhanshree Shripad Shenwai Artificial Intelligence Category – MarkTechPost

​ A common machine learning architecture today is the transformer architecture. One of the main parts of the transformer, attention, has a softmax that generates a probability distribution across tokens. Parallelization is difficult with Softmax since it is expensive owing to an exponent calculation and… Read More »ReLU vs. Softmax in Vision Transformers: Does Sequence Length Matter? Insights from a Google DeepMind Research Paper Aneesh Tickoo Artificial Intelligence Category – MarkTechPost

​ Reinforcement Learning from Human Feedback (RLHF) is recognized as the industry standard technique for ensuring large language models (LLMs) produce content that is truthful, harmless, and helpful. The technique operates by training a “reward model” based on human feedback and uses this model as… Read More »Improving your LLMs with RLHF on Amazon SageMaker Weifeng Chen AWS Machine Learning Blog

​ In Python, the min() function is used to get the smallest item from iterable objects or a sequence. The built-in min() function can take any number of arguments and return the smallest item among all the arguments. It can be used on lists, tuples,… Read More »Python min() Function Malli Spark By {Examples}

​ How to get the first element of a tuple in Python? In Python, tuples are ordered collections of elements, and you can access individual elements of a tuple using index notation. To get the first element of a tuple, you can use indexing. In… Read More »Get the First Element of a Tuple in Python Malli Spark By {Examples}

​ In recent years, the rapid progress in Artificial Intelligence (AI) has led to its widespread application in various domains such as computer vision, audio recognition, and more. This surge in usage has revolutionized industries, with neural networks at the forefront, demonstrating remarkable success and… Read More »Researchers at the University of Tokyo Introduce a New Technique to Protect Sensitive Artificial Intelligence AI-Based Applications from Attackers Niharika Singh Artificial Intelligence Category – MarkTechPost

​ Deep learning has developed into a potent and ground-breaking technique in artificial intelligence, with applications ranging from speech recognition to autonomous systems to computer vision and natural language processing. However, the deep learning model needs significant data for training. To train the model, a… Read More »Do Machine Learning Models Produce Reliable Results with Limited Training Data? This New AI Research from Cambridge and Cornell University Finds it.. Rachit Ranjan Artificial Intelligence Category – MarkTechPost

​ How to convert a list of tuples to a dictionary in Python? In Python, a list of tuples can be converted into a dictionary by using various methods. Converting a list of tuples into a dictionary can be useful in situations where you have… Read More »Python List of Tuples into Dictionary Malli Spark By {Examples}

​ Modern large language models (LLMs) rely heavily on mathematical reasoning, which is the primary focus of this work. There is a clear divide between closed-source and open-source LLMs, even with the recent progress in this area; closed-source models like GPT-4, PaLM-2, and Claude 2… Read More »Meet MAmmoTH: A Series of Open-Source Large Language Models (LLMs) Specifically Tailored for General Math Problem-Solving Dhanshree Shripad Shenwai Artificial Intelligence Category – MarkTechPost