The project's ultimate goal is to meet the country's need for improved telecommunications. On the second day of the mammoth event at the Expo Centre in Karachi, attendees of the International Defence Exhibition and Seminar 2022 (IDEAS-22) showed great enthusiasm for the'One Network' initiative of the Frontier Works Organization (FWO). In a cutting-edge communication initiative called "One Network," workers in Pakistan's highway tunnels are laying 3,000 kilometers of fiber optic cable underneath. Once the project is finished, it will fulfill all of Pakistan's communication needs. The COO of One Network claims that 2,000 kilometers of fiber optic cable have been deployed under the communication backbone of major highways.

Artificial Intelligence (AI) has moved from "when will we do it?" AI passed some important tests during the pandemic, says David Tareen, director of AI and analytics at SAS. "The pandemic put AI and chatbots in place to answer a flood of pandemic-related questions. Computer vision supported social distancing efforts. Machine learning models have become indispensable for modeling the effects of the reopening process." But the future upside of AI is still considerable.

In this age of "big data," artificial intelligence (AI) has become a valuable ally for scientists. Machine learning algorithms, for instance, are helping biologists make sense of the dizzying number of molecular signals that control how genes function. But as new algorithms are developed to analyze even more data, they also become more complex and more difficult to interpret. Quantitative biologists Justin B. Kinney and Ammar Tareen have a strategy to design advanced machine learning algorithms that are easier for biologists to understand. The algorithms are a type of artificial neural network (ANN).

IMAGE: A mathematical thermodynamic model for gene regulation (top, left) is formulated as an artificial neural network (ANN) (bottom, left). Large DNA datasets are fed through the new ANN (right). In this age of "big data," artificial intelligence (AI) has become a valuable ally for scientists. Machine learning algorithms, for instance, are helping biologists make sense of the dizzying number of molecular signals that control how genes function. But as new algorithms are developed to analyze even more data, they also become more complex and more difficult to interpret.