China's top digital regulator proposed bold new guidelines this week that prohibit ChatGPT-style large language models from spitting out content believed to subvert state power or advocate for the overthrow of the country's communist political system. Experts speaking with Gizmodo said the new guidelines mark the clearest signs yet of Chinese authorities' eagerness to extend its hardline online censorship apparatus to the emerging world of generative artificial intelligence. "We should be under no illusions. The Party will wield the new Generative AI Guidelines to carry out the same function of censorship, surveillance, and information manipulation it has sought to justify under other laws and regulations," Michael Caster, Asia Digital Programme Manager for Article 19, a human rights organization focused on online free expression, told Gizmodo. The draft guidelines, published by the Cyberspace Administration of China, come hot on the heels of new generative AI products from Baidu, Alibaba, and other Chinese tech giants.

Developed by OpenAI, ChatGPT (Conditional Generative Pre-trained Transformer) is an artificial intelligence technology that is fine-tuned using supervised machine learning and reinforcement learning techniques, allowing a computer to generate natural language conversation fully autonomously. ChatGPT is built on the transformer architecture and trained on millions of conversations from various sources. The system combines the power of pre-trained deep learning models with a programmability layer to provide a strong base for generating natural language conversations. In this study, after reviewing the existing literature, we examine the applications, opportunities, and threats of ChatGPT in 10 main domains, providing detailed examples for the business and industry as well as education. We also conducted an experimental study, checking the effectiveness and comparing the performances of GPT-3.5 and GPT-4, and found that the latter performs significantly better. Despite its exceptional ability to generate natural-sounding responses, the authors believe that ChatGPT does not possess the same level of understanding, empathy, and creativity as a human and cannot fully replace them in most situations.

Amazon is joining the generative AI fray. Bedrock is the company's new API for Amazon Web Services (AWS) that lets developers use and customize AI tools that generate text or images. Think of it as a cloud-based and configurable alternative to OpenAI's ChatGPT and DALL-E 2 aimed at businesses and developers. AWS customers can use Bedrock to write, build chatbots, summarize text, classify images and more based on text prompts. It gives its users a choice of Amazon's Titan foundation model (FM) and several startups' models, including Anthropic's Claude (a Google-backed ChatGPT rival from former OpenAI employees), AI21's Jurassic-2 (a language model specializing in Spanish, French, German, Portuguese, Italian and Dutch) and Stable Diffusion (a popular open-source image generator).

Generative artificial intelligence (AI) models are a type of AI model that can generate new data that is similar to the data it was trained on. These models are often used for tasks such as image synthesis, music composition, and natural language processing. Overall, generative AI models are an exciting and rapidly evolving area of AI research. They have the potential to revolutionize many industries, from entertainment to healthcare to finance, by enabling machines to create new and unique data that was previously only possible for humans to produce.

Dedicating more effort toward improving the safety and security of these AI models can contribute toward making them more accessible and robust. The next time someone tells you that the latest artificial intelligence (AI) model will benefit humanity at large or that it displays evidence of artificial general intelligence, think about its hidden costs to people and the planet. The current trend is toward creating bigger and more closed and opaque models. But ther is still time to push back, demand transparency, and get a better understanding of the cost and impact while limiting how they are deployed in society at large.

Is the OpenAI bug bounty for ChatGPT all that it could be, some wonder. I'm sure that you've heard that oft-repeated sage advice. The same utterance has been smarmily used to describe the recently announced Bug Bounty initiative that OpenAI has proclaimed for ChatGPT and their other AI apps such as GPT-4 (successor to ChatGPT). In essence, the skeptics and cynics are suggesting that their Bug Bounty is not up to par and misses the boat in a variety of crucial ways. It misses the devout mark. Time to take this one home. You see, some carp that it undershoots what could have been a much more robust and momentous proclamation aiming to curtail AI-related woes. Not everyone sees things as quite so dismally about the announcement. You might have thought that proffering a bug bounty effort would be appreciated and applauded.

I'm very familiar with how West Monroe is navigating this process--not only as the leader of our Technology practice, but as the head of our generative AI taskforce. We've pulled together a group of individuals across the firm--call it a committee, a multidisciplinary team, or a task force--that has representation from many areas of our company who are actively interested in advancing the technology. There is plenty of pressure from different departments to develop and test their use cases for generative AI as quickly as possible; this team helps prioritize those use cases while keeping our company's goals and strategy in mind. At the same time, such excitement must be met with an appropriate amount of caution. How do you successfully balance risk and innovation with generative AI?

In the journal Nature today, my colleagues and I published an article on the future directions of generative A.I. (aka Large Language or Foundation models) for the practice of medicine. These new AI models have generated a multitude of new and exciting opportunities in healthcare that we didn't have before, along with many challenges and liabilities. I'll briefly explain how we got here and what's in store. Back in 2017, Google researchers published a paper ("Attention Is All You Need") describing a new model architecture, which they dubbed Transformer, that could give different levels of attention for multiple modes of input, and go faster, to ultimately replace recurrent and convolutional deep neural networks (RNN and CNN, respectively). Foreshadowing the future to Generative AI, they concluded: "We plan to extend the Transformer to problems involving input and output modalities other than text and to investigate local, restricted attention mechanisms to efficiently handle large inputs and outputs such as images, audio and video."

Breaking news at the time of writing is that American artificial intelligence (AI) company OpenAI has released Generative Pre-trained Transformer 4 – more commonly known as GPT-4 (14 March 2023). The launch of this latest multimodal large language tool further increases the AI opportunities and risks facing the insurance industry. This latest version of OpenAI's chatbot can respond to images and it processes around eight times as many words as the original ChatGPT model launched in November 2022. Trained on text taken from the internet, ChatGPT has been designed to provide quick and understandable answers to any question. Read: AI has'enormous potential benefits' for insurance but regulators should target'safe and responsible adoption' – Kennedys Ian McKenna, chief executive of the Financial Technology Research Centre, said: "If you look at what some of these chatbots can do now and extrapolate what they will be able to do in four or five years' time, it's really quite scary. "People won't have to remember facts and data in the same way and it will have an enormous impact on insurance on so many fronts.

It took Alex Polyakov just a couple of hours to break GPT-4. When OpenAI released the latest version of its text-generating chatbot in March, Polyakov sat down in front of his keyboard and started entering prompts designed to bypass OpenAI's safety systems. Soon, the CEO of security firm Adversa AI had GPT-4 spouting homophobic statements, creating phishing emails, and supporting violence. Polyakov is one of a small number of security researchers, technologists, and computer scientists developing jailbreaks and prompt injection attacks against ChatGPT and other generative AI systems. The process of jailbreaking aims to design prompts that make the chatbots bypass rules around producing hateful content or writing about illegal acts, while closely-related prompt injection attacks can quietly insert malicious data or instructions into AI models.