Artificial Intelligence (AI) is a broad term. Machine Learning and Deep Learning are considered to make up the majority of the term "AI" that many are talking about today, and Deep Learning can be classified under Machine Learning. The main application of Machine Learning is to make predictions of the future from past data. In other words, the machine is capable of finding out the patterns within data, and patterns in the data that lead to a certain outcome, thus, predicting the future.

As tech world goes gaga for latest chatbot, remember Watson's AI fame and subsequent fallout before getting too excited about the possibilities for the latest machine-learning wunderkind ChatGPT is the latest product of artificial intelligence to take away Silicon Valley's breath (and venture-capital investments), but it is also yet another AI advancement that has not proved its ability to live up to a large valuation. ChatGPT debuted about a month ago, offering a chatbot that appears leagues ahead of its predecessors. OpenAI, the company that created ChatGPT, said that it is in a research preview, and that it is collecting data to train its so-called large-language model. Projects like ChatGPT can be astounding, as they seek to test the limits of technology and push them farther. However, excitement for technological promise does not always lead to big financial returns.

The gigantic technological leap that machine learning models have shown in the last few months is getting everyone excited about the future of AI -- but also nervous about its uncomfortable consequences. After text-to-image tools from Stability AI and OpenAI became the talk of the town, ChatGPT's ability to hold intelligent conversations is the new obsession in sectors across the board. In China, where the tech community has always watched progress in the West closely, entrepreneurs, researchers, and investors are looking for ways to make their dent in the generative AI space. Tech firms are devising tools built on open source models to attract consumer and enterprise customers. Individuals are cashing in on AI-generated content.

The gigantic technological leap that machine learning models have shown in the last few months is getting everyone excited about the future of AI …

This is a demo app that shows how to use OpenAI Embeddings and Pinecone vector database to build a semantic search engine. You can run explore this freely using the free tier of Pinecone and OpenAI. I recommend to watch this youtube video from AssemblyAI to learn more about embeddings.

Artificial intelligence is all over the news. When ChatGPT, OpenAI's new chatbot, was released last month it seemed, finally, to match the hype that generative A.I. has been promising for years--an easy-to-use machine intelligence for the general public. Wild predictions soon followed: The death of search engines, the end of homework, the hollowing-out of creative professions. And, for the first time, such predictions didn't seem abstract. When an A.I. bot like ChatGPT can write a coherent story or essay in seconds, and visual applications like Midjourney, Stable Diffusion and DALL-E 2, produce similarly comprehensible images you have to wonder if human creativity--slow and often uncertain--might be superfluous.

The rise of artificial intelligence and machine learning is examined in Mike Hodgkinson's story.

In my previous NextGov column, I reviewed the new ChatGPT artificial intelligence, asking it to perform tasks as varied as programming in C to telling me a bedtime story. I even interviewed the AI about why some people are afraid of artificial intelligences and the importance of ethics as the science of AI moves forward. I found that the ChatGPT AI from OpenAI was extremely adept at fielding just about any kind of question I could throw at it. Even though it's not connected to the internet or any live data streams--so you can't ask it about current events after 2021--it generally provided much better and more detailed information than you would ever find in something like a Google search. The AI is currently free to use, so everyone should give it a try.

AI art can make you uneasy about where the future of creative industries is heading. Even knowing where AI is used is far from clear, since a lot of AI-generated art, music, writing, and videos pass deceptively like something a human created. To help you navigate the AI landscape, this article will explain how AI is being used in five different creative industries. As these AI tools become more available, you might find your own creative use for some of the mind-boggling AI software mentioned below. Creating art using AI systems seems impossible to believe until the results appear before your eyes like magic.

In 2022, the AI boutique movie became a blockbuster. It took exactly ten years for the modern AI story to transform from the new new thing for a bunch of geeks to popular entertainment for the masses. In 2022, AI conversationalist ChatGPT signed up more than one million users in 5 days and AI image generator Midjourney amassed 6 million members in less than 6 months. The 2012 deep learning breakthrough in image identification convinced many computer science PhD candidates to switch their dissertation work to the new superior method for finding patterns in data. Even more important, the entire "Silicon Valley" community fell for the hype created by this new phase of the six decades-long quest for replicating human intelligence in a computer.