Two new AI models out this week show the power of artificial intelligence to read text, write it -- and even convert it into computer code. Why it matters: Natural language processing (NLP) is one of the most exciting areas in AI research, with major implications for how we'll communicate and work in the years ahead. Driving the news: On Wednesday morning, the Israeli startup AI21 Labs is releasing a line of language-generating AI models called Jurassic. How it works: Like other large language models, including GPT-3, the AI21 models have been trained on massive amounts of text, which enables the system to learn the statistical relationships between words and use that to read text prompts from users and write text in response. Situational awareness: On Tuesday, OpenAI itself released Codex, an updated descendant of its GPT-3 model, for a private developer beta test.

All the sessions from Transform 2021 are available on-demand now. That motivational speech a coach or business executive gives you might one day soon be generated by an AI assistant alongside other bits of timely advice and insight. SportsBettingDime, in collaboration with research lab OpenAI, has been experimenting with AI in the form of a GPT-3 text editor to emulate a coach that provides both play-calling advice and motivational speeches based on the situation a team is currently facing. GPT-3 is an AI language model developed by OpenAI that employs a Transformer model to create content in any voice, style, or tone by leveraging assets freely available on the internet. The basic idea is to aggregate play calls made by other head coaches facing similar situations alongside all the best motivational speeches ever given by head coaches.

AI research company OpenAI is releasing a new machine learning tool that translates the English language into code. The software is called Codex and is designed to speed up the work of professional programmers, as well as help amateurs get started coding. In demos of Codex, OpenAI shows how the software can be used to build simple websites and rudimentary games using natural language, as well as translate between different programming languages and tackle data science queries. Users type English commands into the software, like "create a webpage with a menu on the side and title at the top," and Codex translates this into code. The software is far from infallible and takes some patience to operate, but could prove invaluable in making coding faster and more accessible. "We see this as a tool to multiply programmers," OpenAI's CTO and co-founder Greg Brockman told The Verge.

We are excited to have co-led the € 23 million Series A financing round of Heidelberg-based Aleph Alpha together with our friends at Lakestar, UVC and existing investors LEA Partners, 468 Capital and Cavalry Ventures. The exceptional team around AI-serial-entrepreneur Jonas Andrulis and co-founder Samuel Weinbach research, develop and operationalise a new generation of huge and powerful AI like GPT-3, DALL-E or MuZero to maintain European sovereignty for Artificial General Intelligence (AGI). Andrew Ng, one of the leading AI experts stated in 2017: "AI is the new electricity" -- but is it really? Today, narrow AI -- models that are trained to perform one very specific task like chess or solving equations on or above human level -- have automated the development of Covid-19 vaccines, autonomous driving, the creation of music, perfumes, and a lot more. Yes, AI has led to mind boggling results but to fully gauge its potential, I'd like to put things into context: If humanity would have existed an equivalent of 1 day (to represent 300k years) and electricity for 1 minute (to represent 200 years), then narrow AI would be around for about 5 seconds (representing less than two decades).

Imagine using this in schools -- playing around with Codex, kids will fall in love with code. And I can assure you, they won't transform themselves into those lazy folks from WALL-E, they will research and encounter. Codex enables people who don't code to dive in, try things out, and implement their ideas. Artists, teachers, many other people whose profession doesn't involve coding languages will create their approaches and fulfill their visions. It also will help coders with short try&break brainstorming experiments without investing hours into programming "just to try out".

All the sessions from Transform 2021 are available on-demand now. In January, OpenAI released Contrastive Language-Image Pre-training (CLIP), an AI model trained to recognize a range of visual concepts in images and associate them with their names. CLIP performs quite well on classification tasks -- for instance, it can caption an image of a dog "a photo of a dog." But according to an OpenAI audit conducted with Jack Clark, OpenAI's former policy director, CLIP is susceptible to biases that could have implications for people who use -- and interact -- with the model. Prejudices often make their way into the data used to train AI systems, amplifying stereotypes and leading to harmful consequences.

OpenAI has already made some big changes to Codex, the AI-powered coding assistant the company announced last month. The system now accepts commands in plain English and outputs live, working code, letting someone build a game or web app without so much as naming a variable. A few lucky coders (and, one assumes, non-coders) will be able to kick the tires on this new Codex API in a free private beta. Codex is best thought of as OpenAI's versatile language engine, GPT-3, but trained only on code instead of ordinary written material. That lets it do things like complete lines of code or entire sections, but when it was announced it wasn't really something a non-coder would be able to easily interact with.

AI Researcher, Cognitive Technologist Inventor - AI Thinking, Think Chain Innovator - AIOT, XAI, Autonomous Cars, IIOT Founder Fisheyebox Spatial Computing Savant, Transformative Leader, Industry X.0 Practitioner At what stage of development are #artificialintelligence and #machinelearning now? We're living exciting times in the Narrow AI of Statistic ML/DL to be replaced by the Causal AI/ML/DL. Are there any new breakthrough results? OpenAI shocked the world a year ago with GPT-3. Google presented LaMDA and MUM, two AIs that will revolutionize chat-bots and the search engine, respectively.

Generative A.I., from GANs to CLIP, with Python and Pytorch Learn to code the most creative and exciting A.I. architectures, generative networks, from basic to advanced and beyond Hot & New Rating: 4.5 out of 5 What you'll learn Description Generative A.I. is the present and future of A.I. and deep learning, and it will touch every part of our lives. It is the part of A.I that is closer to our unique human capability of creating, imagining and inventing. By doing this course, you gain advanced knowledge and practical experience in the most promising part of A.I., deep learning, data science and advanced technology. The course takes you on a fascinating journey in which you learn gradually, step by step, as we code together a range of generative architectures, from basic to advanced, until we reach multimodal A.I, where text and images are connected in incredible ways to produce amazing results. At the beginning of each section, I explain the key concepts in great depth and then we code together, you and me, line by line, understanding everything, conquering together the challenge of building the most promising A.I architectures of today and tomorrow.

At 135 billion parameters, the neural network is described as the largest "universal" artificial intelligence that the company has running in production. The largest neural network built to date, OpenAI LLC's GPT-3 natural language processing model, has 175 billion parameters.