In this week's real-time analytics news: Several companies announced generative AI offerings or enhancements to their product lines. Keeping pace with news and developments in the real-time analytics market can be a daunting task. We want to help by providing a summary of some of the important real-time analytics news items our staff came across this week. Salesforce launched Einstein GPT, a generative AI CRM technology, which delivers AI-created content across every sales, service, marketing, commerce, and IT interaction. Einstein GPT will infuse Salesforce's proprietary AI models with generative AI technology from an ecosystem of partners and real-time data from the Salesforce Data Cloud.

CyberGuy explains how ChatGPT's functions can help you in your day to day life. ChatGPT has kept growing more and more in popularity since OpenAI released it back in November. Now, the chatbot has Chrome extensions that you can add to your browser to make accessing the feature that much easier. CLICK TO GET KURT'S CYBERGUY NEWSLETTER WITH QUICK TIPS, TECH REVIEWS, SECURITY ALERTS AND EASY HOW-TO'S TO MAKE YOU SMARTER By now, you may have heard of ChatGPT. It is a computer program developed by the artificial intelligence laboratory OpenAI that simulates human conversation and provides helpful and informative responses.

BigTech companies already dominate in GenAI infrastructure with their cloud services and hardware chips. Microsoft and Google are well-positioned in the US cloud market, while Baidu and Alibaba are well-positioned in China. Their massive supercomputer cloud infrastructure is engineered to run GenAI's complex, expensive, large text, visual, and audio Foundational Models. There are already many developers using their cloud AI API services and tools to build apps, and this trend is expected to accelerate as entrepreneurs rush to address virtually limitless GenAI use cases. Amazon has been quiet on Foundational Models, so a big question is how will they respond. GenAI uses massive amounts of computational power to generate creative outputs.

AI Web Designer is a web building tool powered by OpenAI's GPT API. It allows you to create and design static web pages with ease. The tool is programmed using ReactJS and is designed to help individuals and teams build web pages faster. Due to the limitations of OpenAI's API, AI Web Designer cannot handle large documents with too much content. The API has a maximum token limit of 4,000 per request, which means that the AI cannot generate large sections of code, or respond to the user when the document is too big.

Collaboration is an essential function of multiplayer game such as a MOBA, and Soccer game. In the case of Reinforcement Learning, the transition probabilities should be stationary in order to be trained well. Due to this point, famous early study of the OpenAI tried to apply a additional method to deal with the fluctuating transition probabilities. However, recent research of the DeepMind for MARL say that multiple agent game also can be converged to the Nash Equilibrium despite of unstable transition probability. In theory such multi-agent systems may continue to explore forever.

ChatGPT 4 is the latest iteration of the ChatGPT series of AI language models, developed by OpenAI. With its advanced capabilities and impressive performance, ChatGPT 4 is poised to be a game-changer in the field of natural language processing (NLP). Trained on a massive dataset of over 45 terabytes of text, ChatGPT 4 has an unparalleled ability to understand and generate human-like responses to queries and prompts. Its enhanced multilingual capabilities, improved sentiment analysis, and creative writing capabilities make it an ideal tool for a wide range of applications, from customer service chatbots to content creation. One of the standout features of ChatGPT 4 is its ability to generate more coherent and engaging conversations.

AI is the digital distillation of a technological revolution that is facilitating the long-overdue evolution of the human mind. AI, as fear-inducing as anything disruptive and new is, can galvanise, turbo-charge, and trigger new avenues of intelligence in human minds. These new avenues can enable us to understand and attack society's greatest challenges today. What a layman does not know is that AI can traditionally be divided into AGI and ANI. Theorists and AI experts call this Artificial General Intelligence (AGI) and Artificial Narrow Intelligence (ANI). AGI is designed to be capable of performing a wide variety of intellectual tasks, while ANI is designed to perform a single or a narrow set of related tasks.

Niki Parmar and Ashish Vaswani co-authored a seminal paper that set the groundwork for ChatGPT and other generative AI models. ChatGPT has taken the world by storm, but seeds of the groundbreaking technology were sown at the USC Viterbi School of Engineering. The seminal paper "Attention Is All You Need," which laid the foundation for ChatGPT and other generative AI systems, was co-authored by Ashish Vaswani, a PhD computer science graduate ('14) and Niki Parmar, a master's in computer science graduate ('15). The landmark paper was presented at the 2017 Conference on Neural Information Processing Systems (NeurIPS), one of the top conferences in AI and machine learning. In the paper, the researchers introduced the transformer architecture, a powerful type of neural network that has become widely used for natural language processing tasks, from text classification to language modeling.

Salesforce is making a big deal this week of building OpenAI's GPT3 technology -- which powers ChatGPT -- into a broad swathe of its products, describing its Einstein GPT offering as "the world's first generative AI CRM technology." But as I explored in an interview published yesterday with Emergence Capital's Jake Saper, there are big risks in using these Large Language Models (LLMs) in a business context. I spent the day investigating whether Salesforce is cognizant of those risks, and what steps it is taking to ensure its customers don't fall foul of them when implementing solutions based on Einstein GPT. On the face of it, generative AI looks like it can bring a massive boost to business productivity, by making it easier to summarize information from unstructured data stored in documents, knowledgebases and message streams, preparing ready-made drafts for messages, emails and web content used in sales, service and marketing, or generating chunks of code and test routines for developers. But in more than twenty-five years of writing about and reporting on technology, I've seen enough to know that it's always sensible to look behind the hype and the enthusiastic demos to figure out what are the hidden downsides -- where could it all go wrong?

MOUNTAIN VIEW, Calif., Feb 22 (Reuters) - As Alphabet Inc (GOOGL.O) looks past a chatbot flub that helped erase $100 billion from its market value, another challenge is emerging from its efforts to add generative artificial intelligence to its popular Google Search: the cost. Executives across the technology sector are talking about how to operate AI like ChatGPT while accounting for the high expense. The wildly popular chatbot from OpenAI, which can draft prose and answer search queries, has "eye-watering" computing costs of a couple or more cents per conversation, the startup's Chief Executive Sam Altman has said on Twitter. In an interview, Alphabet's Chairman John Hennessy told Reuters that having an exchange with AI known as a large language model likely cost 10 times more than a standard keyword search, though fine-tuning will help reduce the expense quickly. Even with revenue from potential chat-based search ads, the technology could chip into the bottom line of Mountain View, Calif.-based Alphabet with several billion dollars of extra costs, analysts said.