Is ChatGPT a threat or an opportunity for journalism? Five AI experts weigh in

And there are these models that produce video, that produce 3D models. Generative AI is an umbrella term that refers to any of these models that produce novel outputs. Which essentially means all of the internet has been funneled into this large language model, and it has billions of weights. And weights are like little knobs that you turn this way and that way to impact how that large language model makes its predictions. The event consisted of an hour-long open discussion where attendees had the opportunity to ask questions. Other researchers have raised concerns around the tool’s water footprint, referring to the consumption of water used for cooling in data centres.

To understand what chat gpt is used for,  and application of ai in this way, you must know about the different areas where this ai chatbot can be applied. There is a free version of ChatGPT and also a paid version, available at $20/month. It’s part of a new generation of machine-learning systems that can converse, generate readable text on demand and produce novel images and video based on what they’ve learned from a vast database of digital books and online text.

Exploring generative AI: ChatGPT, Dall-E, and the copyright conundrum in the UK

No one really knows how data is used once it’s shared with public AI models, which is extremely concerning. If employees have unrestricted use of ChatGPT, it can lead to businesses no longer being in full control of their own and their customers’ (often sensitive) data. If employees are copying data and sending it to ChatGPT, or other public LLMs, you can no longer control what happens to it. Every ChatGPT answer comes with the caveat that “ChatGPT may produce inaccurate information about people, places, or facts”.

The focus of this article is on the legal issues related to content generating AI such as ChatGPT and Dall-E. This AI driven chatbot provides answers to user prompts ranging from requests for cooking recipes to marketing content requests and, as the introduction to this article shows, it is demonstrably competent in delivering results. Yet it does not pick the most probable next word – it adds randomness (or ‘temperature’, in AI speak) to make the answers more interesting.

Is ChatGPT trustworthy?

Finally, ChatGPT will generate little or no information on events from January 2022 onward, because it has only been provided with data covering events until 2021, and is not linked directly to the Internet. Any AI is only as useful as the data it has been trained on, alongside a few other factors. This could lead to instances of introducing bad code, basing research or content on outdated information and even internalising bias or misinformation. These hallucinations, inaccuracies, and bias can appear because generative AI is probabilistic. At its most basic level, an LLM learns to predict the next word or sequence of words depending on the input.

• For the contact centre, audio and visual models are less interesting at the moment.
• Take this short course to learn how ChatGPT and other generative AI tools work and how you can use them in business.
• Generative AI is being hailed as the next era-defining technological innovation, changing how we create new content online or even experience the internet, and in the process sparking a Silicon Valley frenzy.
• Any personal data processed by an AI system must be processed in accordance with the requirements of data protection laws including the UK GDPR and EU GDPR.

This is something that you’re likely accustomed to checking within your organisation. However, ChatGPT won’t necessarily have the context to provide documentation that meets regulatory approval. Instead, the user must provide the contextual nuance in order to improve the quality of any translation given. This could include asking ChatGPT to use medical terms, describing what sort of document it is, or describing the perspective of the person speaking.

Using generative Artificial Intelligence (AI) tools such as ChatGPT in academic work

This is precisely what is resulting in its vast potential in business and governments. Creating Large Language Models (LLMs) that can generate natural-sounding outputs like text by leveraging high-volume data sets, grammar, semantics, and context is a clear example of the power of generative AI. There is no limit to how Generative AI could transform existing industries or spark innovative new business models as the technology evolves. ChatGPT, created by OpenAI, is widely used as an artificial intelligence instructional help. OpenAI just released GPT-4 with the promise of enhanced performance, fine-tuned interactions, and a more human-like interface.

Because they draw on such big datasets, platforms like ChatGPT generate reasonably accurate, plausible-sounding responses to prompts on a wide range of topics. However, these responses tend to be vague and general, with little real detail and personalisation. They also may not be accurate – citations are likely to be irrelevant or even made-up. There’s a lot of buzz about AI at the moment, much of it prompted by the launch of ChatGPT at the end of last year. ChatGPT has brought AI into the public domain, making it possible for anyone to use AI to generate content. For the first time, it’s not just tech companies, business leaders and politicians talking about AI, it’s lawyers, teachers, writers and the mainstream media, too.

UAE moves one step closer to inclusion of Arabic in global AI development

My background is in law, communications, marketing and government relations. In 2018 I realised that AI was going to change our world dramatically so I completely changed my career by taking a year to study MSc AI and Data Science. I learned to code and was inspired by the technical opportunities AI offers, as well as the ethical challenges.

Explaining how a generative AI system operates to generate output becomes increasingly challenging as the level of sophistication of these systems increases. The challenge of explicability can be further complicated when the AI technology is supplied by another provider or a chain of providers who themselves lack the visibility of how such system operates or functions. Organisations will need to consider how they themselves receive the necessary information, as well as how to achieve the appropriate level of transparency for their use of AI. Some generative AI tools are freely available online – either as stand-alone tools or as products that can integrate into a chain of tools that are provided by multiple developers.

ChatGPT’s conversational capabilities and ability to summarize volumes of source data in coherent paragraphs is why it has become one of the fastest-growing apps of all time. ChatGPT is like an assistant that can get projects going and hand them off to you in a way no other widely available tool can. But I still default to a standard Google search, even after months of reviewing ChatGPT, Google Bard, and Bing Chat. Their shallow, overview-style chatbot answers mean I end up on Google anyway, where the information is richer and easier to fact-check.

Develop a framework for ongoing monitoring and evaluation of
generative AI technologies in the legal market, ensuring that the
barrister’s chambers stays informed and adaptive to emerging
trends and developments. This chapter will examine the various alternative dispute
resolution options for professional negligence claims, including
mediation, arbitration, and early neutral evaluation. It will
discuss the advantages and genrative ai disadvantages of each approach and
provide practical guidance on selecting the most appropriate method
for resolving disputes. This chapter will explore the crucial aspects of causation,
loss, and quantum in professional negligence claims. It will
discuss the ‘but for’ test and the principles governing the
assessment of damages, including the duty to mitigate loss and the
approach to valuing claims involving future loss.