Most organisations in Luxembourg are aware of the enormous advantages of Cloud Computing and increasingly recognise the business benefits of integrating AI, especially when considering the cost/benefit ratio of AI in the Cloud. However, how can the benefits of AI be fully exploited without compromising security and confidentiality, which are particularly critical in Luxembourg? Private AI could be a first-rate solution to this urgent question.
Cloud deployment is inevitable for any organisation looking to expand its digital business in a profitable and sustainable way. Concerns about privacy and security are no longer holding back the trend towards more Cloud computing. Opting for a Hybrid Cloud enables organisations to take advantage of the scale and scalability offered by the Public Cloud, while addressing privacy, security and compliance concerns through the integration of a Private Cloud component. Hybrid and multi-cloud cloud environments, such as those developed as part of DEEP's Strategic Cloud initiative, represent the sovereign, trusted path for any digital enterprise.
Balancing privacy and unlimited power: why compromise when you can have both?
When it comes to AI, an additional concern arises when it comes to personal data. Companies need to take extra care to comply with data privacy regulations and address any potential concerns related to this issue. AI has been on everyone's lips for some time now, and it is generally known that powerful AI tools can unlock significant business opportunities.
However, for many businesses, access to the scale, scalability and cost-effectiveness of the Public Cloud, where these AI solutions thrive, remains a challenge. Unfortunately, the Public Cloud raises precisely those privacy and security concerns that these businesses seek to avoid.
So how do you combine the power of the Public Cloud while respecting strict privacy and security regulations, especially for personal data? One potential solution is to embrace private AI. With private AI, promoted by vendors such as DEEP, organisations can maintain the confidentiality and security of sensitive data in a secure Cloud environment. This data can still be used to analyse and train analytical models to gain new insights and business opportunities, even when this training requires substantial computing power.
Preserving data confidentiality with synthetic data solutions
Private AI can reconcile these two seemingly opposing business objectives by using synthetic data. This data is functionally identical to real data, but all synthetic data is created by AI and has no direct link to private data. In other words, the data is a reflection of real data (like your image in a mirror) and therefore cannot be traced back to individual personal data. Using this synthetic data, AI models can create syntactic data that can be used to train a model in the public cloud, with all the necessary computing power, without having to invest in buying or renting vast private clouds to carry out this computing effort. Once an AI model has been trained and validated, it can seamlessly move on to work with real data in an operational environment.
Smaller companies that cannot afford to train their own models will also eventually benefit from these private AI environments. Once AI models have been developed in this privacy-friendly way and proven their value, they can be established as base models to bring benefits to a wider range of organisations. This democratisation of AI, facilitated by private AI offerings, makes advanced AI capabilities more accessible and affordable for organisations of all sizes and types.
Data quality: unlocking the potential of AI requires strategic preparation
This means that you first need to prepare your data carefully. This means analysing all the data, classifying it, providing it with metadata, and so on. Only then will your data be ready to be used in any AI model. You also need to ensure that any future use of AI models will comply with AI law. This means you need to properly test your AI-based application with other models, making sure your application works with other models as a cross-check. Applying AI to your data will never be a piece of cake.
Fortunately, AI and data specialists are available to help you get your data and AI models right. At DEEP, for example, we have an entire team of data and AI consultants at your service, even when you're still in the early stages of understanding how AI could be useful with your specific available data.
Maximise the opportunity, minimise the risk
AI is a huge opportunity. It can help you detect anomalies in large sets of structured and unstructured data. Generative AI can automate many tasks, improving the profitability of your business. If you want to discover the opportunities offered by AI without compromising the security, privacy and safety of your data, diving into our private AI environment or similar offerings is certainly worthwhile.
