Artificial intelligence (AI) is a buzzword that’s changing the world. Machine learning (ML), which dominates headlines, has revolutionised how we work.
Cambridge Advance Online’s online short courses provider, Cambridge University, draws on the expertise of Dr Russell Hunter to identify the top ML trends that business leaders should be aware of as they navigate the rapidly changing landscape.
As more UK companies integrate AI into their daily operations, and as more UK professionals pursue careers in ML:
- IBM’s latest global AI Adoption Index found 42% of enterprises-scale companies are actively deploying AI. This is the same number that was still exploring AI’s use a year ago.
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According to the latest Google Trends data, searches for “machine-learning jobs” have increased by 30% MoM. Queries such as “how do I become a machine-learning engineer” or “machine-learning engineer jobs” also experienced a 300% interest increase over the past five years.
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Often, questions about how to enter the industry accompany the term “machine-learning”, such as “What are the requirements for learning machine-learning?” or “Should i go into AI?
Russell Hunter is a Professor of Engineering in the Department of Engineering of the University of Cambridge. He leads the Leveraging Big Data course for Business Intelligence at Cambridge Advance Online.
ML Operation
ML Ops, or operationalisation management of ML, focuses on deployment, monitoring and governance for ML models. In the early stages of our innovation in this area, Dr Hunter recalls that there were concerns about drifting performance, managing different variations of models and retraining data without affecting business.
ML Ops has become essential for businesses as they scale their AI capabilities. This trend is gaining traction in the industry and enables faster deployment and maintenance ML models.
Autonomous decision-making
These advanced systems transform industries by increasing the speed and accuracy of decision-making and driving greater efficiency. They also enhance customer experience. Automating manual processes can help businesses analyse large amounts of data faster, uncover patterns and make informed decisions.
Dr Hunter explains the application of autonomous systems to industries like healthcare. “Sophisticated AI multimodal can analyse genetic data, patient histories and recommend personalised treatment plan. It leads to a more individualised and effective health care. These systems can also predict outcomes and complications by using data from electronic records. This allows proactive intervention .”
Quantum Machine Learning
Dr Hunter notes that as AI grows and advances, computational resources will also grow exponentially. This innovative area is attracting research and investment from big names like IBM and Google, as well as high-risk industries such a finance and pharmaceuticals.
Dr Hunter continued, “Quantum AI is a promising future that can allow for more accurate and complete model because they aren’t constrained by traditional computing.” It’s a more futuristic frontier, but one that has the potential to solve issues beyond the reach classical algorithms .”
EdgeAI
Edge AI is another cutting-edge technology that brings immediate processing capabilities. This is important for applications such as autonomous vehicles, industrial automation, and healthcare monitoring where timely responses are required. Dr Hunter says that this is done by reducing the latency of the data, enabling real time decision making, and minimizing the amount of data transmitted to central servers.
This also improves privacy and security by reducing the risk that data will be compromised during transmission. Dr Hunter points out, however, that “challenges like hardware limitations, integration complex, and the requirement for efficient management of and maintenance of many edge devices curtails the full efficacy of edge AI .”
Expanded workforces
There are fears that AI could replace workers in the workplace. Dr Hunter, however, believes that AI can enhance rather than diminish human contributions. “The augmented worker trend uses AI to transform job roles and boost productivity across different sectors.
This collaboration between humans, and AI, allows AI to handle repetitive and data-intensive tasks, while humans concentrate on creative, interpersonal, and strategic activities that require emotional intelligence, and critical thinking. AI does not eliminate jobs; it reshapes and creates new ones that require management, programming, and collaboration with AI systems .”
As a leader in business, it is important to stay abreast of these developments to ensure that your organization is well-equipped to leverage AI and ML to gain an advantage.
To get a detailed look at these trends and other insights, read Dr Hunter’s Machine Learning Trend Analysis on the CAO Blog .
The original version of this article Five Machine Learning Trends Business Leaders Should Take Away From 2024 appeared first on HR News.
