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Thematic Analysis
NewSemiconductors Sector Scorecard, Q1 2024 Update – Thematic Intelligence
Companies scoring strongly in artificial intelligence (AI) and geopolitics-related themes lead the thematic screen of GlobalData’s semiconductors sector scorecard. Indeed, the AI, AI chips, geopolitics, and China impact themes jointly account for 50% of the weighting of the thematic screen, reflecting both the growing importance of AI, particularly generative AI, in the industry and the impact of the ongoing US-China trade dispute. Among the thematic leaders are companies with either advanced AI products, such as Nvidia, Amazon, Tesla, and Alibaba,...
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Analyst Opinions
Scaling at the Edge: How Edge Computing is Augmenting Data Processing
Edge Computing Market Report Overview Edge computing is an emerging computing architecture that processes data close to the source with an aim to resolve latency issues for critical applications across sectors. It minimizes the processing and transmission strain on cloud computing centers by reducing the time it takes for users to input data and moving computing capacity to the network's edge. This can transform various business processes, notably for data-intensive services. The report highlights various innovations with contemporary use cases...
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Thematic Analysis
Machine Learning – Thematic Intelligence
Machine Learning Thematic Intelligence Report Overview Machine learning is a subset of artificial intelligence (AI) that allows computer systems to learn and improve from data without being explicitly programmed. It is the most practical application of AI currently available for enterprise adoption. The machine learning thematic intelligence report highlights key technology trends, macroeconomic trends, and regulatory trends impacting the machine learning theme. Furthermore, it discusses machine learning value chains, mergers & acquisitions activities, and major milestones in the journey of...
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Thematic Analysis
Artificial Intelligence (AI) Chips – Thematic Research
Recent progress in machine learning on the back of improved algorithms and increasing computing power has made it possible for AI to solve real-life problems. However, as these AI models dramatically grow in complexity, chips specifically optimized for AI become imperative. To deploy AI capabilities at the consumer's fingertips, it will be necessary to deploy cloud resources at the edge and support high throughput and ultra-low latencies, both of which call for a widespread full (standalone) 5G rollout. The AI...