Generative AI: Why it matters for you and your business

Using advanced natural language processing algorithms and deep learning techniques, AI-powered content-generation tools are able to analyze existing content within a specific industry or niche. Using that information, AI tools can then generate relevant and engaging content for you. This form of machine learning allows artificial intelligence models to generate exciting content, including everything from music to virtual worlds. It also has serious benefits, such as creating product designs or business processes in the corporate world. The level of explicability – or “explainability” – required or expected depends on the type of activity, the relevant legal jurisdictions of deployment, the recipient of the explanation and the nature of the AI used. For example, the EU GDPR contains transparency requirements regarding use of personal data, and specific requirements regarding fully automated decisions with legal or similarly significant effects on a data subject.

This is a poignant reminder that, while generative AI is here to stay, it offers both risks and rewards to the cyber security community and is not a replacement for human knowledge. In the world of cyber security, AI is creating just as much of a buzz as it is everywhere else. genrative ai Indeed, the RSA Conference included several perspectives on the topic, including talks by government officials from the U.S. Cyber security and Infrastructure Security Agency (CISA), National Security Agency (NSA), and the National Aeronautics and Space Administration (NASA).

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A recent study of European startups found that 40% of the businesses surveyed claim to be ‘AI startups’ but actually had no AI at all. Being known as an AI washout can have harmful impacts on your business, so if your business is planning to publicise its use of AI, just make sure you’re comfortable backing up those claims. By striking this balance, we can harness the true potential of future generative AI while building a more equitable and responsible digital landscape for all. However, as the prevalence of generative AI and LLMs continues to rise, so does the risk of AI-generated fraud and concerns around bias.

Upskilling, retraining, and embracing new opportunities can help mitigate the negative effects and maximize the potential benefits of AI integration. Apprehensions included potential job losses from automation and the need to develop AI skills for future employment opportunities. Generative AI has not only captured the attention of tech enthusiasts and researchers but has also started to permeate the education sector, significantly impacting students and the future of employment. The rise of this transformative technology raises intriguing questions about the role it plays in shaping educational experiences and the implications it has on the evolving job market.

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On the other hand, some argued that the popularity of AI right now, particularly LLMs, is more a result of marketing than actual technology advancements. Next-generation models are poised to better understand human psychology and the creative process in more depth, enabling them to produce written content that is not only technically sound but also deeply engaging, inspiring, and emotionally resonant. Using Transformer architecture, generative AI models can be pre-trained on massive amounts of unlabeled data of all kinds—text, images, audio, etc. There is no manual data preparation, and because of the massive amount of pre-training (basically learning), the models can be used out-of-the-box for a wide variety of generalised tasks.

It can extract and classify data, improving accuracy and efficiency in tasks like accounts payable/receivable, compliance reporting, and fraud detection. Generative AI can also assist in risk modeling and forecasting, generating synthetic scenarios to assess potential market risks and optimize investment strategies. Large language models benefit from their immense size, as they can capture a wide range of linguistic patterns and nuances. However, it’s important to note that these models operate based on statistical patterns rather than true understanding or consciousness—they do not possess explicit knowledge or real-world experience, but rely on patterns learned from the training data. Generative AI is the use of artificial intelligence (AI) systems to generate original media such as text, images, video, or audio in response to prompts from users.

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.

As the popularity of generative AI continues to increase, many GenAI experts have emerged from the field of AI, such as Nina Schick. Analysing how this field of AI will change humanity, Nina is the Founder of Tamang Ventures – a leading advisory firm dedicated to the study and adoption of generative AI. Also renowned as the Creator of The Era of Generative AI, a substack project spreading awareness of generative AI, Nina is also highly sought after as a company advisor – working with companies such as Synthesia and Truepic.

We are not, I hope, just building code, but building business outcomes, and we mustn’t just trust what a Generative AI tells us. There is intelligence there, but it is ant-like intelligence, Dr Pound suggests, not human intelligence as we understand it. Another AI advantage is the ability to help small business owners maintain a consistent posting schedule, which ensures your business remains visible on social media platforms. Additionally, AI can automate the process of content scheduling and distribution across various channels, allowing you to reach your customers with consistent and timely communication.

Google has recently launched a new tool called ‘About This Image’ to help people spot fake AI images on the internet. The tool will provide additional context alongside pictures, including details of when the image first appeared on Google and any related news stories. This new feature will help people identify hyper-realistic pictures from the real ones, including those generated using tools such as Midjourney, Stable Diffusion, and DALL-E. An artist named Justin T. Brown who created AI-generated images of politicians cheating on their spouses to highlight the potential dangers of AI. He shared the images on the Midjourney subreddit, but soon after, he was banned from the platform. Brown expressed conflicting feelings about the ban, acknowledging the need for accountability but questioning the effectiveness of regulating content.

This poses a problem when designing cyber security policies and processes because the AI doesn’t know anything about how your organisation works or your secure practices. Also it can’t know the language of your organisation and how best to present information; it is genuinely robotic in its approach which could lead to a lack of engagement. Generative artificial intelligence (such as ChatGPT or the currently in testing M365 Copilot) is a type of AI technology that can produce various types of content, including text, imagery, audio and synthetic data.

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. 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 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.

• Cyber security and Infrastructure Security Agency (CISA), National Security Agency (NSA), and the National Aeronautics and Space Administration (NASA).
• When given a topic or starting point, LLMs create sentences that make sense and sound natural by choosing words based on what they’ve learned from their training.
• On the other hand, used incorrectly, this technology has the capability to produce inaccurate or even plagiarised information – and, beneath all that, there is the worry about AI “replacing” human staff.
• Recent improvments in machine learning and deep learning algorithms have made it possible to create more realistic and high-quality generative models.