Recent public interest in tools like ChatGPT has raised an old question in the artificial intelligence community: is artificial general intelligence (in this case, AI that performs at human level) achievable? An online preprint this week has added to the hype, suggesting the latest advanced large language model, GPT-4, is at the early stages of artificial general intelligence (AGI) as it's exhibiting "sparks of intelligence". OpenAI, the company behind ChatGPT, has unabashedly declared its pursuit of AGI. Meanwhile, a large number of researchers and public intellectuals have called for an immediate halt to the development of these models, citing "profound risks to society and humanity". These calls to pause AI research are theatrical and unlikely to succeed – the allure of advanced intelligence is too provocative for humans to ignore, and too rewarding for companies to pause.

The open letter calling for an immediate six-month pause in the AI development arms race and signed by more than 1600 tech luminaries, researchers and responsible technology advocates under the umbrella of the Future of Life Institute is stunning on its face. Self-reflection and caution have never been defining qualities of technology sector leaders. Outside of nuclear technology, it's hard to identify another time when so many have publicly rallied to slow the pace of technology development down, much less call for government regulation and intervention. "Advanced AI could represent a profound change in the history of life on Earth and should be planned for and managed with commensurate care and resources," the letter states. "Unfortunately, this level of planning and management is not happening, even though recent months have seen AI labs locked in an out-of-control race to develop and deploy ever more powerful digital minds that no one – not even their creators – can understand, predict, or reliably control. "Therefore, we call on all AI labs to immediately pause for at least 6 months the training of AI systems more powerful than (Open AI's) GPT-4.

When you scan the headlines on your favourite news app each morning, do you ever stop to think who -- or what -- wrote the story? The assumption is there are human beings doing the work. But it's also possible an algorithm wrote it. Artificial intelligence is capable of producing text, images and audio with little to no human intervention. For instance, the neural network called Generative Pre-trained Transformer 3 (GPT-3) is capable of producing text -- a fictional story, a poem or even a programming code -- virtually indistinguishable from text written by a person.

You might have heard of ChatGPT, a chat bot that is very good at answering questions. The big "T" in GPT stands for "Transformer", and is why GPTs are so good at what they do. A transformer is a computer program that answers questions. It is especially good at what it does, because it has certain super-powers. Let's see what these are… When you here a question like, "What is the capital of India?", you probably pay more attention to "India", because it is important.

Artificial intelligence in some shape or form has been a part of everyday life for years, but the meteoric rise of ChatGPT and the resulting aggressive development pace of conversational and generative AI models is, for the first time ever, putting the underlying technology into the hands of the general public. Even though current large language models are primarily able to guess the best-fitting next word in a sentence based on the corpus of content they were fed, CEOs, researchers and AI experts are now urging the industry to pump the brakes on training and developing models more capable than OpenAI's GPT-4. The company's latest large language model is currently available in a limited capacity for ChatGPT Plus subscribers and will soon be integrated into Microsoft productivity and security products. According to an open letter signed by influential figures like Elon Musk and Stability AI CEO Emad Mostaque, « powerful AI systems should be developed only once we are confident that their effects will be positive and their risks will be manageable. The Musk Foundation is a primary donor to the organization.

Maybe LLMs aren't all that great at it yet, but why can't they be thinking? They're producing output that looks like it's the result of thinking. One thing is, that result you're talking about doesn't really correspond to what the LLM "thought" if it actually could be called that. Very simplified explanation from someone who is definitely not an expert. You feed it tokens and you get back a token like "the", right?

TikTok video from Just Minded (@justminded.com): "ChatGPT: The revolutionary AI language model #chatgpt #chatgpt4 #openai #artificialintelligence #languagemodel #ai". original sound - Just Minded.

Artificial intelligence (AI) has become the buzzword of the moment in the tech industry, especially after OpenAI launched its now infamous chatbot ChatGPT. Since then, a spotlight has been shone on how AI has been constantly transforming the way we live, work, and interact with the world around us. Its uses are endless thanks to the constant upgrade of AI tools; from content creation to image generation, the sky's the limit. With it no longer being viewed as something of the future but part of our present, it's important to explore the various services AI tools offer that can help take our productivity to the next level. While ChatGPT has made quite the splash, it's important to note that there are many other tools available that offer their own unique and exciting features, including automating data analysis and creating stunning visuals.

Kevin Bocek is vice president, security strategy and threat intelligence, at Venafi, a company that makes security software for authenticating machines. He used ChatGPT to create Excel macros and PowerShell scripts, which are two different ways to give a computer repeatable instructions. Hackers often use them to launch an attack.

OpenAI's GPT-4 is a Large Language Model (LLM) that can generate coherent constructed languages, or "conlangs," which we propose be called "genlangs" when generated by Artificial Intelligence (AI). The genlangs created by ChatGPT for this research (Voxphera, Vivenzia, and Lumivoxa) each have unique features, appear facially coherent, and plausibly "translate" into English. This study investigates whether genlangs created by ChatGPT follow Zipf's law. Zipf's law approximately holds across all natural and artificially constructed human languages. According to Zipf's law, the word frequencies in a text corpus are inversely proportional to their rank in the frequency table. This means that the most frequent word appears about twice as often as the second most frequent word, three times as often as the third most frequent word, and so on. We hypothesize that Zipf's law will hold for genlangs because (1) genlangs created by ChatGPT fundamentally operate in the same way as human language with respect to the semantic usefulness of certain tokens, and (2) ChatGPT has been trained on a corpora of text that includes many different languages, all of which exhibit Zipf's law to varying degrees. Through statistical linguistics, we aim to understand if LLM-based languages statistically look human. Our findings indicate that genlangs adhere closely to Zipf's law, supporting the hypothesis that genlangs created by ChatGPT exhibit similar statistical properties to natural and artificial human languages. We also conclude that with human assistance, AI is already capable of creating the world's first fully-functional genlang, and we call for its development.