DALL-E is a Generative Pre-trained Transformer (GPT) model developed by OpenAI that can generate images from textual descriptions.

ChatGPT, OpenAI's free chatbot based on GPT-3.5, was released on 30 November 2022 and racked up a million users in five days. It is capable of writing emails, essays, code and phishing emails, if the user knows how to ask. By comparison, it took Twitter two years to reach a million users. Facebook took ten months, Dropbox seven months, Spotify five months, Instagram six weeks. Pokemon Go took ten hours, so don't break out the champagne bottles, but still, five days is pretty impressive for a web-based tool that didn't have any built-in name recognition.

'Leaving aside the very real ramifications of robots displacing artists who are already underpaid, we believe that AI art devalues the act of artistic creation for both the artist and the public'

Using a pretrained AI model from Nvidia, startup Evozyne has created two proteins with significant potential in healthcare and clean energy. A joint paper released today describes the process and the biological building blocks it produced. One aims to cure a congenital disease, another is designed to consume carbon dioxide to reduce global warming. Initial results show a new way to accelerate drug discovery and more. "It's been really encouraging that even in this first round the AI model has produced synthetic proteins as good as naturally occurring ones," says Andrew Ferguson, Evozyne's co-founder and a co-author of the paper.

Microsoft is discussing a potential $10 billion investment in ChatGPT founder OpenAI that will boost its value to $29 billion. The AI tool has dazzled many people worldwide due to its uncanny ability to generate text while mimicking human speech. According to Reuters, OpenAI told investors last month it expects $200 million in revenue in 2023 and a billion dollars by 2024. Most people know Microsoft as the creator of MS Word, PowerPoint, Excel, and Outlook. Meanwhile, OpenAI is an artificial intelligence laboratory made popular by ChatGPT.

Russian cyber-criminals have been observed on dark web forums trying to bypass OpenAI's API restrictions to gain access to the ChatGPT chatbot for nefarious purposes. Various individuals have been observed, for instance, discussing how to use stolen payment cards to pay for upgraded users on OpenAI (thus circumventing the limitations of free accounts). Others have created blog posts on how to bypass the geo controls of OpenAI, and others still have created tutorials explaining how to use semi-legal online SMS services to register to ChatGPT. "Generally, there are a lot of tutorials in Russian semi-legal online SMS services on how to use it to register to ChatGPT, and we have examples that it is already being used," wrote Check Point Research (CPR), which shared the findings with Infosecurity ahead of publication. "It is not extremely difficult to bypass OpenAI's restricting measures for specific countries to access ChatGPT," said Sergey Shykevich, threat intelligence group manager at Check Point Software Technologies.

DALL-E 2 is artificial intelligence software that can turn anything you type into art, in any style. You want a portrait of a panda in the style of Renoir? Try this! Said one woman, "That is frightening and fascinating all at the same time!" I've even used it to illustrate "Sunday Morning" stories. DALL-E 2 and its rivals, like Midjourney and Stable Diffusion, are available to anyone; they're inexpensive, or even free, to use.

Paris – The hottest startup in Silicon Valley right now is OpenAI, the Microsoft-backed developer of ChatGPT, a much-hyped chatbot that can write a poem, college essay or even a line of software code. Tesla tycoon Elon Musk was an early investor in OpenAI and Microsoft is reported to be in talks to up an initial investment of between $1 billion and $10 billion in a goal to challenge Google's world-dominating search engine. If agreed, the cash injection by the Windows-maker would value OpenAI at a whopping $29 billion, making it a rare tech-world success at a time when major players such as Amazon, Meta and Twitter are cutting costs and laying off staff. This could be due to a conflict with your ad-blocking or security software. Please add japantimes.co.jp and piano.io to your list of allowed sites.

On Wednesday the Chartr office party was in full swing, but instead of heading for drinks -- as originally planned -- we found ourselves still in the office, writing increasingly funny prompts into ChatGPT, a chatbot from OpenAI. Built on the architecture of GPT-3, with some 175 billion parameters, the key innovation of ChatGPT relative to other AI breakthroughs is that it's super easy to interact with. "Tell me a joke", "write a recipe for pecan pie in the style of a pirate", "explain long division to a ten-year-old"... ChatGPT has a -- pretty convincing -- response for all. That functionality has gone viral, with OpenAI reporting that ChatGPT had hit 1 million users in just 5 days. Searches for ChatGPT rocketed, surpassing those for "lensa", another AI app making waves this week, but ChatGPT is undoubtedly the much, much bigger story.

This report describes our PromptShots submissions to a shared task on Evaluating the Rationales of Amateur Investors (ERAI). We participated in both pairwise comparison and unsupervised ranking tasks. For pairwise comparison, we employed instruction-based models based on T5-small and OpenAI InstructGPT language models. Surprisingly, we observed OpenAI InstructGPT language model few-shot trained on Chinese data works best in our submissions, ranking 3rd on the maximal loss (ML) pairwise accuracy. This model works better than training on the Google translated English data by a large margin, where the English few-shot trained InstructGPT model even performs worse than an instruction-based T5-small model finetuned on the English data. However, all instruction-based submissions do not perform well on the maximal potential profit (MPP) pairwise accuracy where there are more data and learning signals. The Chinese few-shot trained InstructGPT model still performs best in our setting. For unsupervised ranking, we utilized many language models, including many financial-specific ones, and Bayesian lexicons unsupervised-learned on both Chinese and English words using a method-of-moments estimator. All our submissions rank best in the MPP ranking, from 1st to 3rd. However, they all do not perform well for ML scoring. Therefore, both MPP and ML scores need different treatments since we treated MPP and ML using the same formula. Our only difference is the treatment of market sentiment lexicons.