<ul data-eligibleForWebStory="true">Researchers faced obstacles in the early years of AI development impacting academic research, industry investment, and public interest.Challenges included lack of computational power, data availability, and high costs for computing resources.Unrealistic expectations in the 1960s and 1970s led to 'AI winters' when funding and support declined.Establishing strong foundational knowledge through education programs helped maintain AI momentum.Replicating human-like intelligence proved complex due to challenges in natural language processing and system integration.Historical challenges laid the groundwork for today's AI advancements, enhancing research, funding models, and collaborations.Cloud computing, big data, and open-source tools have addressed earlier limitations in AI development.Joining an AI training program provides hands-on experience with technologies once considered impossible.Current AI landscape benefits from past challenges, fostering innovation and progress in the field.Visualpath is highlighted as the best online software training institute in Hyderabad for AI courses.