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Top 8 AI and ML Trends to Watch in 2022

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Google CEO Sundar Pichai said that the impact of AI would be even more significant than that of fire or electricity on the development of humans as a species. It may be an ambitious claim, but AI's potential is very clear from the way it has been used to explore space, tackle climate change, and develop cancer treatments. Now, it may be difficult to imagine the impact of machines making faster and more accurate decisions than humans, but one thing is certain: In 2022, new trends and breakthroughs will continue to emerge and push the boundaries of AI and ML. Here are the top eight AI and ML trends to watch out for in 2022. Since the advent of AI and ML, there have always been fears and concerns regarding these disruptive technologies that will replace human workers and even make some jobs obsolete.


AI Research

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The study of heuristic algorithms that solve "difficult" (e.g., NP) issues is known as artificial intelligence (AI). The search for alternative solutions that AI algorithms perform, as well as the knowledge that they use (e.g., from a domain expert) to focus the search on promising answers, define AI algorithms. Expected (vs worst-case) time/space costs to identify answers, as well as the quality of discovered solutions in comparison to ideal solutions, are frequently used to assess AI algorithm performance. Think of a world where intelligence isn't limited to people!!! A future in which machines can think and collaborate with humans to build a more fascinating universe.


Biggest AI and Machine Learning Trends that Will Shift Tech Investments in 2022

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Machine Learning trends continue to enthrall analysts all over the world. It's true that AI adoption is on the rise but the real push into 2022 comes from the evidence-based approach to building a more sustainable and human-friendly environment. According to a recent report, 56 percent of the global business leaders have stated AI adoption in at least one function. Leading AI companies such as NVIDIA, Microsoft, Google, Amazon Web Services (AWS), Alibaba.com and Tencent Cloud made remarkable investments in the last 2-3 years to develop cutting-edge capabilities in AI Machine Learning, data science, and automation domains. Today, artificial intelligence (AI) and machine learning (ML) trends have become the key barometers for industrial development, enabling organizations to progress toward becoming the most disruptive and revolutionary enterprises in the world.


Artificial intelligence in cybersecurity - Dataconomy

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Artificial intelligence in cybersecurity is a must-have combination for organizations nowadays. Artificial intelligence (AI) assists under-resourced security operations analysts in keeping pace with attacks, and this technology will have a greater role as cyberattacks increase in volume and complexity. AI technologies, such as machine learning and natural language processing that analyze millions of research papers, blogs, and news stories, provide rapid insights to cut through the noise of daily alerts. AI provides analysts with a method to connect the dots between threats. The enterprise attack surface continues to expand and get more complex.


Why We Need To Democratise AI To Harness The Future Of Technology - ET CIO

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By Raghu Ravinutala As the world embraces the post-pandemic environment, enterprises are undergoing rapid business transformation. Companies are reshaping their marketing, HR, sales and customer support strategies to survive and then thrive in the new normal. Now more than ever, technology driven innovation has become important for devising and executing novel ways to bridge the gap of demand and supply in these unprecedented times. The biggest problems enterprises are trying to solve include - engaging with customers and employees more digitally without losing personal touch, increasing automation and safeguarding business from disruption, marketing and selling digitally, and onboarding and training employees remotely. Before covid, artificial intelligence and deep technology innovation was being rolled out over several years with pilots and proof of concepts.