Swedish Radio publishes policy for generative AI

We now look forward to even more discussions with committed colleagues about what is most important for us to explore and decide on going forward. In dialogue with the rest of the media industry and other social actors, we also want to contribute to the use of AI in a responsible and transparent way so that it benefits Swedish media consumers. For several years now, Swedish Radio has been actively exploring how, with the help of artificial intelligence, we can strengthen our offer to the audience and make our operations more efficient.

Decision-makers and stakeholders have a vital role to play in embracing the transformative potential of generative AI while implementing robust frameworks for accountability, fairness and user protection. As we navigate this new digital frontier, it is crucial to prioritise its genrative ai responsible use, foster collaboration, and shape a future where generative AI contributes positively to society while mitigating risks and pitfalls. Generative AI can compose original music, adapt compositions in real time, and create soundscapes that react to user input.

Model management

NVIDIA NeMo enables organizations to build custom large language models (LLMs) from scratch, customize pretrained models, and deploy them at scale. Included with NVIDIA AI Enterprise, NeMo includes training and inferencing frameworks, guardrailing toolkits, data curation tools, and pretrained models. For enterprises running their business on AI, NVIDIA AI Enterprise provides a production-grade, secure, end-to-end software platform for development and deployment. It includes over 100+ frameworks, pretrained models, and open-source development tools, such as NeMo, Triton™, TensorRT™ as well as generative AI reference applications and enterprise support to streamline adoption. Generative artificial intelligence (Generative AI) has been a topic of increasing interest, especially following the release of ChatGPT by OpenAI in November 2022.

Iain Brown PhD, Head of Data Science for SAS, Northern Europe, explores recent developments in AI and delves into the potential promises, pitfalls, and concerns around bias surrounding the future of generative AI. This raises serious genrative ai concerns about the potential misuse of deepfake technology, from political propaganda to personal vendettas. Deepfakes have already been used to create fake pornographic videos, causing harm to the individuals involved.

Understanding the role of generative AI in insurance industry transformation

Generative AI models have the ability to mimic language in response to human-entered prompts. In some contexts, it can use such prompts to create detailed written responses that reflect general knowledge on the subject matter. It is important to balance the opportunity it gives with deep responsibility and security. Google has committed to Responsible AI practices, which means that enterprise and user security and data management features are built in within their platform.

Some other terms, such as ‘frontier models’ and ‘AGI/strong AI’ are also being used in industry, policy and elsewhere, but are more contested. This is in part because of the lack of a specific interpretation, and in part because of their origins and the context in which they are used. Metaphysic is also capable of processing live video in real-time, which is at the cutting edge of AI technology.

A prolific businessman and investor, and the founder of several large companies in Israel, the USA and the UAE, Yakov’s corporation comprises over 2,000 employees all over the world. He graduated from the University of Oxford in the UK and Technion in Israel, before moving on to study complex systems science at NECSI in the USA. Yakov has a Masters in Software Development.

„Generative AI has many exciting – and potentially transformational – use cases. Responsible AI governance will be key to enabling businesses to innovate while maintaining customer trust.” Will data entered on the AI system be protected, and will the operation of the system be robust? To what degree will your personnel rely on the use of that AI, and are contingencies needed in the event it becomes unavailable (for a temporary period, or permanently)? Some sectors, such as the financial services sector, may also have overarching governance and genrative ai oversight frameworks under which cyber-security and operational resilience considerations may apply to certain uses of generative AI. Organisations using AI will have a range of legal obligations regarding equality, diversity and fair treatment, as well as ethical and reputational imperatives. The accuracy and completeness of an AI system’s output may also be important, with the degree of importance varying depending on the use for which the output will be used and the level of human review, expertise and judgement that will be applied.

And as technologies develop, today’s frontier models will no longer be described in those terms. This means that they predict the likelihood of a character, word or string, based on the preceding or surrounding context. For example, language models can predict the next most likely word in a sentence given the previous paragraph.[25] This is commonly used in applications such as SMS, Google Docs or Microsoft Word, which make suggestions as you are writing. Some forms of generative AI can be unimodal (receiving input and generating outputs based on just one content input type) or multimodal (that is, able to receiving input and generate content in multiple modes, for example, text, images and video).

Generative AI broadly refers to machine learning models that can create new content in response to a user prompt. These tools – which include the likes of ChatGPT and Midjourney – are typically trained on large volumes of data, and can be used to produce text, images, audio, video and code. Avanade believes that AI is the next wave of computing, a technology that will influence nearly every area of business. Generative AI will create new business models, and possibly new industries, altogether. Generative AI refers to a broad class of artificial intelligence systems that can generate new and seemingly original content such as images, music or text in response to user requests or prompts.

• Recruitment, talent pipeline management and staff training will be aspects to consider in planning for effective AI risk management.
• This allows CPG companies to create products that better cater to consumer needs and preferences.
• Being a pioneer in technology with deep expertise in AI, blockchain, Generative AI, and other cutting-edge technologies like IoT, LeewayHertz is dedicated to helping companies navigate their most complex tech challenges and facilitate business growth.
• As the field continues to develop, we can expect to see even more disruption and transformation in the years to come.

Large Language Models can generate engaging, personalized marketing content, such as email campaigns, social media posts, and advertisements. By tailoring content to individual customer preferences and interests, CPG companies can enhance customer engagement and drive sales. Generative AI can assist in the product development process by analyzing customer feedback and market trends to identify potential product ideas and improvements. This allows CPG companies to create products that better cater to consumer needs and preferences.

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Hernaldo Turrillo is a writer and author specialised in innovation, AI, DLT, SMEs, trading, investing and new trends in technology and business. He is the editor of openbusinesscouncil.org, tradersdna.com, hedgethink.com, and writes regularly for intelligenthq.com, socialmediacouncil.eu. Hernaldo was born in Spain and finally settled in London, United Kingdom, after a few years of personal growth.

It is a fascinating field that has the potential to revolutionise various industries, including insurance. Variational Autoencoders (VAEs) and Recurrent Neural Networks (RNNs) began to demonstrate their ability to generate novel content, marking a significant step forward in the field. The emergence of these technologies set the stage for Generative AI’s growth and the development of more advanced models. Current monetization efforts for AI platforms and services are still at an early stage, but AI business models should eventually prove to be valuable to end-customers. As we enter the exponential age, the wielders of new, permissioned technology will have access to bewilderingly more advanced capabilities than those without this privilege.