Unlocking the Power of AI: 5 Key Trends Shaping the Future of Artificial Intelligence

As AI systems become more complex, there are concerns about transparency, fairness, and bias. In this blog post, we will explore five key trends that are shaping the future of AI and how NexTech Solutions (NTS) can help you leverage these trends to stay ahead of the curve.

INCREASED FOCUS ON EXPLAINABILITY

As AI systems become more complex, there is a growing demand for explainable AI. Explainable AI refers to AI systems that can provide clear and understandable explanations for the decisions they make. This is particularly important in sensitive areas like healthcare and finance, where people’s lives and livelihoods are at stake. Or, for example, the military. The importance of explainable AI for military end-users cannot be overstated. Those who depend on these decisions made by AI systems need to understand and trust the rationale when it comes to mission operations.

Explainable AI is not only important for ethical reasons but also for practical reasons. Without explainability, it’s difficult to know whether an AI system is making the right decision or not. For example, in the case of a medical diagnosis, a doctor needs to know how an AI system arrived at a particular diagnosis to make an informed decision.

ADVANCEMENTS IN NATURAL LANGUAGE PROCESSING (NLP)

Natural Language Processing (NLP) is the technology that enables machines to understand and interact with human language. Recent advancements in NLP are making it possible for machines to understand language with more nuance and accuracy than ever before. This has led to breakthroughs in areas like machine translation, sentiment analysis, and chatbots.

For example, chatbots are becoming increasingly popular in customer service. With NLP, chatbots can understand natural language and provide responses that are relevant and helpful to the customer. This can improve customer satisfaction and reduce the workload of customer service representatives.

EDGE COMPUTING

Edge computing refers to processing data on local devices rather than sending it to the cloud for processing. With the proliferation of IoT devices and the need for real-time data processing, edge computing is becoming increasingly important. AI systems that can run on local devices will be critical for applications like autonomous vehicles and industrial automation.

For example, autonomous vehicles need to process large amounts of data in real-time to make decisions about steering, braking, and acceleration. With edge computing, the data can be processed locally, reducing the latency and improving the safety of the vehicle.



INCREASED FOCUS ON ETHICAL AI

As AI becomes more integrated into our lives, there is growing concern about the ethical implications of AI systems. There is a need for AI systems that are transparent, fair, and unbiased. This has led to the development of ethical frameworks for AI and the creation of AI governance bodies.

For example, in the case of hiring, there is concern about bias in AI systems that use data from previous hires to make decisions about future hires. Without careful consideration of the data being used, these systems can perpetuate bias and discrimination.

CONTINUED GROWTH IN DEEP LEARNING

Deep learning is a subset of machine learning that uses artificial neural networks to model and solve complex problems. Deep learning has led to breakthroughs in areas like computer vision, speech recognition, and natural language processing. As more data becomes available, and as computing power increases, deep learning will continue to drive advancements in AI.

For example, gathering vast amounts of data information, intelligence, insights, etc. that is generated continuously by defense systems is critical to support military capabilities and operations. With the growth of this generated information, it is overwhelming for human operators alone to analyze, whereas trained artificial intelligence can sift through the data, capture key trends and organize it to be digestible for the user. 

CONCLUSION

AI is a rapidly evolving field, and has played an increasing role in a range of systems and capabilities in enabling warfighters to maintain a battlefield advantage. The five key trends that we’ve discussed in this blog post – increased focus on explainability, advancements in NLP, edge computing, increased focus on ethical AI, and continued growth in deep learning – are shaping the future of AI.

At NTS, we have the expertise and experience to help our clients leverage these trends to improve their business operations and stay ahead of the curve. Whether you’re looking to develop a system from scratch or optimize an existing one, we can work with you to ensure your success.