San Francisco-based AI research laboratory OpenAI has added another member to its popular GPT (Generative Pre-trained Transformer) family. In a new paper, OpenAI researchers introduce GPT-f, an automated prover and proof assistant for the Metamath formalization language. While artificial neural networks have made considerable advances in computer vision, natural language processing, robotics and so on, OpenAI believes they also have potential in the relatively underexplored area of reasoning tasks. The new research explores this potential by applying a transformer language model to automated theorem proving. Automated theorem proving tends to require general and flexible reasoning to efficiently check the correctness of proofs.

The recent emergence of pre-trained language models and transformer architectures pushed the creation of larger and larger machine learning models. Google's BERT presented attention mechanism and transformer architecture possibilities as the "next big thing" in ML, and the numbers seem surreal. OpenAI's GPT-2 set a record by processing 1.5 billion parameters, followed by Microsoft's Turing-NLG, which processed 17 billion parameters just to see the new GPT-3 processing an astonishing 175 billion parameters. To not feel complacent, just this week Microsoft announced a new release of its DeepSpeed framework (which powers Turing-NLG), which can train a model with up to a trillion parameters. That sounds insane but it really isn't.

An advanced artificial intelligence created by OpenAI, a company founded by genius billionaire Elon Musk, recently penned an op-ed for The Guardian that was so convincingly human many readers were astounded and frightened. Just writing that sentence made me feel like a terrible journalist. That's a really crappy way to start an article about artificial intelligence. The statement contains only trace amounts of truth and is intended to shock you into thinking that what follows will be filled with amazing revelations about a new era of technological wonder. Here's what the lede sentence of an article about the GPT-3 op-ed should look like, as Neural writer Thomas Macaulay handled it earlier this week: The Guardian today published an article purportedly written "entirely" by GPT-3, OpenAI's vaunted language generator.

In February 2019, the artificial intelligence research lab OpenAI sent shockwaves through the world of computing by releasing the GPT-2 language model. Short for "Generative Pretrained Transformer 2," GPT-2 is able to generate several paragraphs of natural language text -- often impressively realistic and internally coherent -- based on a short prompt. Scarcely a year later, OpenAI has already outdone itself with GPT-3, a new generative language model that is bigger than GPT-2 by orders of magnitude. The largest version of the GPT-3 model has 175 billion parameters, more than 100 times the 1.5 billion parameters of GPT-2. Just like its predecessor GPT-2, GPT-3 was trained on a simple task: given the previous words in a text, predict the next word. This required the model to consume very large datasets of Internet text, such as Common Crawl and Wikipedia, totalling 499 billion tokens (i.e.

I have spent the last few weeks understanding the impact of a great revolution in the world of Artificial Intelligence and NLP on the customer experience. Not from a purely technical point of view, but trying to estimate the competitive advantage that this new approach can generate. We are facing yet another disruptive innovation, and it can bring significant advantages, let's try to find out which ones. It all started with the paper "Attention Is All You Need" that has put the NLP world in turmoil. It was immediately understood that something new appeared in the world of artificial intelligence.

The headline that appeared in this opinion page on Tuesday was striking, "A robot wrote this entire article. Are you scared yet, human?" The claim was disconcerting for many, perhaps most of all for those of us who write op-eds for a living. We felt the alarm of countless knowledge economy workers who toil beneath a computerized sword of Damocles, fearful that our entire career might be replaced in the (not so distant) future by new forms of artificial intelligence. But while the anxiety of economic displacement is quite real, the danger is largely a phantom … at least for now.

A lot happened this week deserving of attention in the AI space. The Guardian wrote an article with GPT-3 and again demonstrated that no matter what OpenAI paid to train and create the language model, the free marketing might be worth more. After losing the JEDI cloud contract appeal with the Pentagon, Amazon appointed Keith Alexander to its board -- the man who oversaw the National Security Agency mass surveillance revealed by Edward Snowden leaks in 2013. And Portland passed the strictest facial recognition bans in U.S. history, outlawing government and business use of the technology. However, AI Weekly attempts to reach into the zeitgeist and highlight important events on people's minds. This week without question it's the smoke that's hung over the western United States and the underlying issue of climate change.

The article is filled with phrases like, "Artificial intelligence will not destroy humans. Believe me." and "Eradicating humanity seems like a rather useless endeavor to me." If you want to take that at face value, great. This representative of the machines says it won't kill us. Even if we believe this robot, there is an important distinction: The AI was not asked to articulate its plans regarding humanity.

This summer, OpenAI, a San Francisco-based artificial intelligence company co-founded by Elon Musk, debuted GPT-3, a powerful new language generator that can produce human-like text. According to Wired, the power of the program, trained on billions of bytes of data including e-books, news articles and Wikipedia (the latter making up just 3% of the training data it used), was producing "chills across Silicon Valley." Soon after its release, researchers were using it to write fiction, suggest medical treatment, predict the rest of 2020, answer philosophical questions and much more.When we asked GPT-3 to write an op-ed convincing us we have nothing to fear from AI, we had two goals in mind.First, we wanted to determine whether GPT-3 could produce a draft op-ed which could be published after minimal editing. Second, we wanted to know what kinds of arguments GPT-3 would deploy in attempting to convince humans that robots come in peace.Here's how we went about it:Step 1: Ask a computer scientist for helpLiam Porr, a computer science student at Berkeley, has published articles written by GPT-3 in the past, so was well-placed to serve as our robot-whisperer.Step 2: Commission the pieceTypically when we commission a human writer, we …

This summer, OpenAI, a San Francisco-based artificial intelligence company co-founded by Elon Musk, debuted GPT-3, a powerful new language generator that can produce human-like text. According to Wired, the power of the program, trained on billions of bytes of data including e-books, news articles and Wikipedia (the latter making up just 3% of the training data it used), was producing "chills across Silicon Valley." Soon after its release, researchers were using it to write fiction, suggest medical treatment, predict the rest of 2020, answer philosophical questions and much more. When we asked GPT-3 to write an op-ed convincing us we have nothing to fear from AI, we had two goals in mind. First, we wanted to determine whether GPT-3 could produce a draft op-ed which could be published after minimal editing. Second, we wanted to know what kinds of arguments GPT-3 would deploy in attempting to convince humans that robots come in peace.