Update app.py

app.py

@@ -15,16 +15,41 @@ def summarise(text):
 
 # Two example passages for quick testing
 example_texts = [
-    ["Artificial intelligence has progressed rapidly over the past decade. "
-     "New methods in deep learning have made it possible to process vast amounts of data, "
-     "leading to significant advances in language modelling, computer vision, and reinforcement learning. "
-     "As organisations adopt these technologies, questions emerge regarding transparency, fairness, "
-     "and the wider societal impact of automated decision-making."],
-
-    ["The Industrial Revolution transformed Europe’s economic landscape. "
-     "Mechanised production replaced traditional craft methods, enabling factories to produce goods at a scale "
-     "previously unimaginable. These developments shifted labour patterns, encouraged urban migration, "
-     "and laid the foundations for modern industrial capitalism."]
+    ["""
+    Over the past half-century, the relationship between technology and society has undergone a profound transformation. 
+    The earliest digital systems were narrow in scope, expensive to maintain, and accessible only to governments and large research 
+    institutions. Their primary function was to accelerate numerical calculations, simulate complex physical systems, and automate a 
+    limited range of administrative tasks. By contrast, contemporary digital technologies influence almost every aspect of social, 
+economic, and cultural life. The proliferation of personal devices, the rise of global communication networks, and the emergence of 
+intelligent systems have collectively reshaped the way individuals interact with information, institutions, and one another.
+A particularly significant development has been the shift from passive computation to adaptive, data-driven systems capable of learning 
+from examples. Machine learning, and deep learning in particular, now underpin applications ranging from medical diagnostics and financial 
+forecasting to translation services and autonomous vehicles. These systems exhibit performance that, in some domains, 
+rivals or exceeds that of trained human experts. Their growing prominence has prompted renewed interest in the ethics of automation, 
+including concerns regarding fairness, accountability, transparency, and the potential reinforcement of existing social inequalities.
+    """ ],
+     [""""
+     In recent years, debates about the future of work have intensified as automation and artificial intelligence continue to 
+     advance at an impressive pace. Industries that once relied upon large numbers of routine, manual workers have begun adopting 
+     sophisticated systems capable of performing complex tasks with remarkable consistency. 
+     Manufacturers now use intelligent robotics to monitor supply chains, maintain production lines, and 
+     identify defects in real time, while service providers increasingly rely upon algorithmic tools to streamline logistics, 
+     customer support, and administrative processes. Although these developments promise efficiency and cost savings, 
+     they also raise important questions about job security, professional identity, and the capacity of existing institutions 
+     to support individuals whose roles may change or disappear. The transformation is not confined to industrial labour; 
+     professions such as law, journalism, and medicine are also beginning to feel the effects of algorithmic decision-making, 
+     prompting renewed discussions about the value of human judgement in an environment shaped by relentless technological acceleration.
+     Alongside these economic and professional considerations, attention has turned towards the broader societal implications of widespread 
+     automation. Public discourse frequently highlights the tension between technological progress and social wellbeing, particularly in 
+     light of concerns about privacy, data ownership, and democratic accountability. As more personal information is collected, 
+     processed, and acted upon by automated systems, citizens increasingly seek assurances that these technologies are 
+     deployed responsibly and transparently. Policymakers, however, often struggle to keep pace with innovation, 
+     resulting in regulatory frameworks that are uneven, reactive, or insufficiently aligned with public expectations. 
+     The challenge is further complicated by global inequalities: nations with limited technical infrastructure may find 
+     themselves dependent upon systems developed elsewhere, with little influence over how those systems evolve. 
+     These realities underscore the need for thoughtful governance, interdisciplinary dialogue, and inclusive decision-making to 
+     ensure that the benefits of automation are shared widely rather than reserved for a narrow segment of society.
+     """]
 ]
 
 with gr.Blocks(title="BART Text Summariser") as demo: