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It is proving difficult to keep pace with the level of innovation in the artificial intelligence (AI) space in 2023. Since the arrival of generative AI platforms like ChatGPT nearly a year ago, a plethora of other AI-powered tools and solutions have emerged. The possibilities and applications seem to be endless.
To focus attention amidst the noise, below we offer investor readers 5 exciting horizons in generative AI which could be suitable for different portfolios. To learn more about our EIS projects and other early-stage opportunities, visit our portfolio page here. For enquiries regarding our latest projects and funding, you can reach us via:
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#1 AI-enhanced creativity
So far, we have seen the arrival of Midjourney which allows users to enter text prompts into a Discord server and receive AI images based on the input commands. These images can then be used to create colouring books, comics and even logo designs. Then there is Runway, an AI-powered video generation platform which allows users to create short videos containing content requested by the user.
These AI innovations are likely to turbo-charge the creative sector in the coming years. Adobe, for instance, has now integrated “generative fill” into its latest version of Photoshop – allowing designers to add objects to images, change backgrounds and pave over cracks (e.g. skin blemishes).
#2 Computing power
The world’s demands for data and computer power are not slowing down in 2023. New deep learning models, powered by AI algorithms, are particularly intensive – fuelled by constant “pushing” in the AI community to try out new ideas and experiments.
This all raises questions about the sustainability of our current global hardware infrastructure. Can we simply keep building large data centres (the “Web 2” internet model followed by tech giants) to meet this demand? Here, decentralised approaches to data storage and cloud computing – such as NexGen Cloud – are set to play a key role by making use of idle hardware such as PCs, laptops and other devices (following a kind of “Airbnb model” of cloud computing).
#3 Legislation & regulation
Generative AI is so transformative to human society that lawmakers are struggling to develop robust legal frameworks to govern its responsible, effective use. Many governments (including the UK) are keen to let their countries emerge as world leaders in the AI space. Yet they are aware of the potential risks to data security, privacy and news/fact accuracy.
The US is still taking a cautious approach as it crafts AI legislation with its “Blueprint for an A.I. Bill of Rights”. In the UK, the Government is lobbying to have an AI and Employment Bill ready in ready in 2024. At least four issues need to be addressed by lawmakers when striving to govern AI – protecting citizens whilst encouraging innovation and commercial growth:
- Reliable data (so AI makes informed “decisions”)
- Avoiding/mitigating data bias.
- Upholding privacy and data protection rights
- Maintaining trust and transparency in the creation, use and application of AI tools.
#4 Synthetic data & AI training
An AI model is only as powerful as the quality of the data supplied to it. If the dataset is outdated, poorly-constructed or filled with biases, then the results will be inaccurate (at best). Vast, unimaginable amounts of high-quality data are required to meet the generative AI needs of today. One interesting area of debate on this subject is “synthetic data”.
Synthetic data, in simple terms, is artificial data which is created to replicate data in the real world. It does not trace back to actual events but rather uses mechanisms, such as rule-based generation, to create synthetic samples which the AI algorithm can then apply to sampling and modelling. This approach could address many issues such as data confidentiality and data scarcity. However, synthetic data could miss many of the intricacies of real-world data. At present, its suitability seems to depend on the specific application and its end goals.
#5 AI and the workforce
Amazon is now using over 750,000 robots in its warehouses to do heavy lifting and relieve employees from “monotonous tasks”. There is, of course, a big debate in 2023 about whether AI will completely eradicate human jobs. Yet it seems that the trend is towards augmentation rather than replacement.
Almost every job can be impacted by AI. Customer service representatives can collaborate with AI tools to deliver a faster, more enjoyable experience to buyers and prospects. Financial advisers could use AI-powered platforms to automate mundane back-office tasks and improve their analytical abilities when conducting client reports.
AI could spark the birth of new jobs and industries such as prompt engineers and AI ethicists. The key will be continuous employee education and training as AI is brought into new operations, systems and roles. The benefit of generative AI is that it is very accessible, user-friendly and intuitive – holding out great potential for employees to use it to enhance their work, provided they are taught how to collaborate with it.
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