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.

OpenAI is a research and deployment company. They are the creators of the models powering experiences like ChatGPT and Bing Image Creator.

Join top executives in San Francisco on July 11-12, to hear how leaders are integrating and optimizing AI investments for success. Coursera is offering more classes and degrees so that global labor market won't be blindsided by the rise of generative AI and remote work. As businesses adopt generative AI to improve customer offerings and productivity, it will also create an unprecedented demand for reskilling – with up to 49% of workers having half or more of their tasks exposed to large language models. "Today, we're excited to announce several new content offerings, ChatGPT-powered platform innovations, and expanded immersive learning experiences to better serve our learners and educators worldwide," said Jeff Maggioncalda, CEO of Coursera, in a blog post. To meet the growing demand for AI skills in the workforce, Coursera is increasing its selection of AI-related courses, including a ChatGPT Teach-Out (University of Michigan) and AI for Good Specialization (DeepLearning.AI).

Amazon Web Services (AWS), announced today that it is expanding its generative AI services in a bid to make the technology more available to organizations in the cloud. Among the new AWS cloud AI services is Amazon Bedrock, which is launching in preview as a set of foundation model AI services. The initial set of foundation models supported by the service include ones from AI21, Anthropic, and Stability AI as well as a set of new models developed by AWS known collectively as Amazon Titan. In addition, AWS is also announcing the general availability of Amazon EC2 Inf2 cloud instances powered by the company's own AWS Inferentia2 chips, which provide high performance for AI. Rounding out the updates, the Amazon CodeWhisperer generative AI service for code development is now generally available, with AWS making it free for all individual developers.

According to the USCO: "This initiative is in direct response to the recent striking advances in generative AI technologies and their rapidly growing use by individuals and businesses." It is also a response to requests from Congress and the public. A summary of this guidance is here. The Guide provides a convenient collection of relevant materials in one document for your convenience. We are also planning a webinar on legal issues with Generative AI, generating employee guidance on the use of AI and dealing with contractors that produce content for you.

The seeds of a machine learning (ML) paradigm shift have existed for decades, but with the ready availability of scalable compute capacity, a massive proliferation of data, and the rapid advancement of ML technologies, customers across industries are transforming their businesses. Just recently, generative AI applications like ChatGPT have captured widespread attention and imagination. We are truly at an exciting inflection point in the widespread adoption of ML, and we believe most customer experiences and applications will be reinvented with generative AI. AI and ML have been a focus for Amazon for over 20 years, and many of the capabilities customers use with Amazon are driven by ML. Our e-commerce recommendations engine is driven by ML; the paths that optimize robotic picking routes in our fulfillment centers are driven by ML; and our supply chain, forecasting, and capacity planning are informed by ML. Prime Air (our drones) and the computer vision technology in Amazon Go (our physical retail experience that lets consumers select items off a shelf and leave the store without having to formally check out) use deep learning.

While we'll have some innovations like Med-PaLM 2 that are tuned for healthcare, we also have products that are relevant across industries. Last month, we announced several generative AI capabilities coming to Google Cloud, including Generative AI support in Vertex AI and Generative AI App Builder, which are already being tested by a number of customers. Developers and businesses already use Vertex AI to build and deploy machine learning models and AI applications at scale, and we recently added Generative AI support in Vertex AI. This gives customers foundation models they can fine-tune with their own data, and the ability to deploy applications with this powerful new technology. We also launched Generative AI App Builder to help organizations build their own AI-powered chat interfaces and digital assistants in minutes or hours by connecting conversational AI flows with out-of-the-box search experiences and foundation models.

The hype around artificial intelligence (AI) has skyrocketed since the launch of ChatGPT, the chatbot from OpenAI. In just two months, ChatGPT was estimated to have reached 100 million monthly active users, with wide-ranging use cases including writing essays, debugging code and composing music. Such a leap in functionality and adoption prompted leading lights in the technology industry to call for a'pause' in the development of powerful AI systems. On March 22, the non-profit organisation Future of Life Institute published an open letter urging AI research facilities to put a stop to the creation of systems that can match human intelligence. More than 50,000 industry figures -- including CEO of SpaceX, Tesla and Twitter Elon Musk; Apple co-founder Steve Wozniak; and Chris Larsen, co-founder of Ripple -- have added their signatures to halt the training of models larger than GPT-4, the newest version of OpenAI's language model system.

Generative AI is transforming many industries, including entertainment, manufacturing, automotive, and knowledge-based. In knowledge-based industries, it has the potential to automate certain tasks, such as generating legal documents and automating financial analysis, that can increase the productivity of knowledge workers. A report by Research and Markets states generative AI is projected to become a $200.73 billion market by 2032. Recently, Bill Gates, in his blog post, said, "In the future, ChatGPT will be like having a white-collar worker available to assist you with various tasks," But since generative AI is still in its early stages, it has limitations and unintended consequences. While it can perform tasks, it cannot replace the reasoning abilities and cognitive flexibility of humans essential to white-collar knowledge work.