In this blog, we will give you a brief introduction of what are multimodal models and what can multimodal generative models accomplish. OpenAI just released their latest text-to-video multimodal generative model "SORA" in Feb, 2024 which becomes extremely popular. SORA can generate short videos of up to 1 minute's length. Before SORA, there are also many generative multi-modal models released by various companies, such as BLIP, BLIP2, FLAMINGO, FlaVA, etc. We will summarize a complete list of these time tested multi-modal generative models, introduce the model architures (text and image encoder), the training process, tasks, latex equation of loss functions, the Vision Language capabilities (such as text-to-image, text-to-video, text-to-audio, visual question answering), etc. Tag: Multimodal, AIGC, Large Language Model

AI agent research have attracted a lot of attention with the rapid development of Large Language Model (LLM) and Reasoning (RL or CoT Chain of Thought) technology. Generative AI Agents use LLM to plan, act and reflect on the memories from the environment as well as the interactions from other agents, just like the environment in Stanford's Generative Agents paper "Generative Agents: Interactive Simulacra of Human Behavior". The simulation environment usually consists of a environment (Such as A Small Town) and multiple AI Agents taking actions to make plans and achieve goals. Before making plans and taking actions, agents will retrieve related information from memories, which is a list of descriptions of the timestamp and exact events, such as "2023-02-03 Someone is watching a movie...". During multi-agents simulation, each agent will have its own timeline and their actions are usually asynchronous. In this blog, we will give a review of the tools of AI Agents Visualization, especially in the situation where there are multiple agents with asynchronous actions during the simulation.

This blog summarizes the latest research development of dialogue and large language models (LLM) papers published in ACL2023 conferences. This year there are total 79 papers related to dialogue in ACL2023. Most of the authors' affiliations are top research institutes (Google Research, DeepMind, Meta FAIR) and universities (Stanford, Berkeley, MIT, CMU and others).

We are witnessing great success in recent development of generative Artificial Intelligence in many fields, such as AI assistant, Chatbot, AI Writer. Among all the AI native products, AI Search Engine such as Perplexity, Gemini and SearchGPT are most attrative to website owners, bloggers and web content publishers. AI Search Engine is a new tool to provide answers directly to users' questions (queries). In this blog, we will give some brief introduction to basic concepts of AI Search Engine, including Large Language Models (LLM), Retrieval-Augmented Generation(RAG), Citations and Sources. Then we will highlight some majors differences between traditional Search Engine Optimization (SEO) and Generative Engine Optimization(GEO). And then we will cover some latest research and strategies to help website owners or content publishers to better optimize their content in Generative AI Search Engines.

In this blog, we are introducing how you can use financial chatbot and AI-assistant writer to help you facilitate daily financial work, such as getting realtime stock price quote from global markets (US: NYSE,NASDAQ; China: HKEX, Shanghai,Shenzhen, etc.), consulting investment advice, consensus ratings and target price of stocks from analysts of multiple organizations (Schwab.com, MarketBeats, Zacks.com) and compare them, finding the meaning of complicated financial terms such as CPI, Put Option, Sharpe Ratio. You can also use ChatGPT to act as personally financial assistant, track your portfolio's stock names and show realtime changes. For content generation, you can use the AI-Writer assistant to facilitate writing reports, which integrates many APIs and other ChatGPT style Large Language Model to automatically generate text contents such as market research, financial reports of listed companies, etc.

In this blog, we will show you 3 easy steps to create your personal financial chatbot assistant powered by ChatGPT. ChatGPT is Large Language Model (LLM) based Artificial Intelligent service created by OpenAI company, who just released their latest Assistant API for chatbot creation. These AI assistants are very useful in financial industries. Common use cases include: Generating realtime stock price quotes, Analyzing financial data, Providing investment advices, generating summary of financial reports, etc. Keywords: Financial Chatbot, Financial ChatGPT, Chatbot Stock Price, Chatbot NYSE, Chatbot.