The Future of AI

Hello there and welcome back, this week we are having a little look at the future of AI written by one of our researchers Mr W. Daly in a compressed article.

He has a good knowledge across alot of topics but has an interst in most things scientific.

We hope you enjoy the read 🙂 if you have any questions or information for us please leave them in the comments.

The Future of AI: What You Need to Know

Artificial intelligence (AI) is changing our world in ways that we could not have imagined a few years ago. From chatbots and voice assistants to self-driving cars and medical diagnoses, AI is increasingly touching our lives in various settings and domains. But what does the future hold for AI and how will it impact us in the coming years? Here are some key trends and challenges that you should be aware of:

AI will become more multimodal and conversational

One of the most impressive advances in AI in the last five years has been the development of generative AI systems that can produce natural language, images, sounds and videos from data or text. For example, OpenAI’s ChatGPT chatbot can answer questions, write poetry, generate computer code and carry on conversations. It can also describe images from the Hubble Space Telescope in painstaking detail. These multimodal systems will enable new ways of interacting with AI, such as using natural language to request images or videos, or using voice or gestures to control devices. They will also make AI more accessible and engaging for users who prefer different modalities of communication.

Some examples of multimodal AI applications that are already available or under development are:

Google’s Duplex, which can make phone calls on behalf of users to book appointments or reservations using natural language.

Adobe’s Photoshop Camera, which can apply filters and effects to photos based on user requests or suggestions.

Facebook’s Horizon Workrooms, which can create virtual meeting spaces where users can interact with each other using avatars, spatial audio and hand gestures.

Microsoft’s Mesh, which can enable holographic collaboration and mixed reality experiences across devices.

AI will augment and assist human experts

Another promising direction for AI is to leverage its strengths in data analysis, pattern recognition and optimization to augment and assist human experts in various domains. For example, AI can help with drug discovery by finding novel molecules or targets, with decision making by providing a menu of likely treatment options for patients, or with basic assistance by providing lane keeping while driving or text-to-speech based on images for the visually impaired. In many situations, people and AI have complementary skills and can work together as a team. However, this also requires AI to be transparent, explainable and trustworthy, so that human experts can understand its reasoning and actions.

Some examples of AI applications that are already augmenting or assisting human experts are:

IBM’s Watson, which can provide insights and recommendations for various domains such as healthcare, finance and education.

Google’s DeepMind AlphaFold, which can predict the 3D structure of proteins from their amino acid sequences.

Amazon’s Alexa Care Hub, which can help caregivers monitor the well-being and activity of their loved ones using voice commands and alerts.

Tesla’s Autopilot, which can assist drivers with steering, acceleration and braking under certain conditions.

AI will pose ethical and social challenges

As AI becomes more powerful and pervasive, it also raises ethical and social challenges that need to be addressed. For example, how can we ensure that AI is fair, accountable and respectful of human values and rights? How can we prevent AI from being misused or abused for malicious purposes? How can we mitigate the potential impacts of AI on jobs, privacy and security? These are not only technical questions, but also moral and political ones that require interdisciplinary collaboration and public engagement. As the recent report from the One Hundred Year Study on Artificial Intelligence (AI100) states: “The choices we make today about how to use these technologies will shape our future.”

Some examples of ethical and social challenges posed by AI are:

Data scarcity: The lack of sufficient or diverse data for training AI systems can limit their performance or introduce biases.

Limited implementation: The gap between research and practice can hinder the adoption or scaling of AI solutions in real-world settings.

Data privacy and security: The collection, storage and sharing of personal or sensitive data by AI systems can expose users to risks of data breaches or misuse.

Transparency of algorithm bias: The complexity or opacity of AI algorithms can obscure their logic or assumptions, making it hard to detect or correct errors or biases.

Computing power: The high demand for computing resources by AI systems can increase energy consumption or environmental impact.

Trust deficit: The lack of trust or understanding between users and AI systems can affect their acceptance or satisfaction.

Limited knowledge: The difficulty of transferring or generalizing knowledge across domains or tasks can limit the scope or robustness of AI systems.

Human-level: The possibility of creating AI systems that can surpass human intelligence or capabilities can raise existential or ethical questions.

Conclusion

AI is an exciting and transformative field that offers many opportunities and benefits for humanity. But it also poses significant challenges and risks that need to be carefully considered and addressed. As users, developers and policymakers of AI, we have a responsibility to shape its future in a way that aligns with our goals and values. The future of AI is not predetermined; it is up to us to make it happen.

References

: The Future of AI: What Comes Next and What to Expect - The New York Times : The present and future of AI - Harvard John A. Paulson School of Engineering and Applied Sciences : Future of AI – less artificial, more intelligent (part one) : Five main challenges of Artificial Intelligent Technology

Well we thought that was quite an informative article and gave a good insight into the future of AI, as much as it is a bite sized article to fit in with a blog there is alot more to come as AI becomes further interfaced with all aspects of our day to day life, but we can touch on that another day.

Thank you as always and until we see you again stay safe and be strong ❤️