​Posted by AJ Piergiovanni and Anelia Angelova, Research Scientists, Google Research Vision-language foundational models are built on the premise of a single pre-training followed by subsequent adaptation to multiple downstream tasks. Two main and disjoint training scenarios are popular: a CLIP-style contrastive learning and next-token… Read More »MaMMUT: A simple vision-encoder text-decoder architecture for multimodal tasks Google AI Google AI Blog

​ Reinforcement learning (RL) is a popular approach to training autonomous agents that can learn to perform complex tasks by interacting with their environment. RL enables them to learn the best action in different conditions and adapt to their environment using a reward system. A… Read More »Dream First, Learn Later: DECKARD is an AI Approach That Uses LLMs for Training Reinforcement learning (RL) Agents Ekrem Çetinkaya Artificial Intelligence Category – MarkTechPost

​ Time series forecasting refers to the process of predicting future values of time series data (data that is collected at regular intervals over time). Simple methods for time series forecasting use historical values of the same variable whose future values need to be predicted,… Read More »Automate the deployment of an Amazon Forecast time-series forecasting model Aaron Fagan AWS Machine Learning Blog

​ Generative AI is gaining a lot of public attention at present, with talk around products such as GPT4, ChatGPT, DALL-E2, Bard, and many other AI technologies. Many customers have been asking for more information on AWS’s generative AI solutions. The aim of this post… Read More »Get started with generative AI on AWS using Amazon SageMaker JumpStart Paul Colmer AWS Machine Learning Blog

​ Researchers have long explored the emergent features of complex systems, from physics to biology to mathematics. Nobel Prize-winning physicist P.W. Anderson’s commentary “More Is Different” is one notable example. It makes the case that as a system’s complexity rises, new properties may manifest that… Read More »A New AI Research From Stanford Presents an Alternative Explanation for Seemingly Sharp and Unpredictable Emergent Abilities of Large Language Models Aneesh Tickoo Artificial Intelligence Category – MarkTechPost

​ CoT prompting uses a step-by-step explanation to guide a big language model to develop a response. CoT prompting has been demonstrated to increase productivity in activities that require extensive reasoning significantly. The self-consistency (SC) technique further enhances accuracy by sampling multiple chains of thought… Read More »A New AI Research Introduces A Method To Answer Questions By Meta-Reasoning over Multiple Chains of Thought Tanushree Shenwai Artificial Intelligence Category – MarkTechPost

​ Machine learning models have been proven to be a powerful tool for solving complex tasks, but training these models has often been manual and time-consuming. However, with the emergence of large language models like GPT-3.5, training machine-learning models can now be automated. This has… Read More »Automating Machine Learning Tasks: How MLCopilot Utilizes LLMs to Assist Developers in Streamlining ML Processes Niharika Singh Artificial Intelligence Category – MarkTechPost

​ As the large language models took the Artificial intelligence domain by storm, all the science fiction movies a whole generation grew up watching, people speculating about an era ruled by robots, all the heated debates about the ethics perspective. All of these points are… Read More »Meet MetaGPT: A GPT-4-powered Application That Can Create Websites, Apps, And More Based Only On Natural Language Prompts Anant shahi Artificial Intelligence Category – MarkTechPost

​ MongoDB and MySQL are both powerful database management systems hence, it is important to know the difference between MongoDB vs MySQL. Here, I will explain the differences by exploring the CRUD operation on MongoDB and MySQL. CRUD is to create, read, update, and delete. Related: MongoDB Beginners… Read More »MongoDB Vs MySQL Differences Naveen (NNK) Spark By {Examples}