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Cognitive Computing; Practical Applications of AI
Google suspends Gemini; AI researchers' open letter demands action on deepfakes before they destroy democracy
Ishaan Mahajan
February 26, 2024
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Welcome to learning edition of the Data Pragmatist, your dose of all things data science and AI.
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Today we are talking about self-learning systems utilizing data mining, pattern recognition, and natural language processing to emulate the complexity of human cognition. As part of our learning series, Practical Applications of AI.
📝 Practical Applications of AI
Healthcare: AI improves diagnostics, personalized medicine, and mental health care through wearables and virtual therapists.
Customer Service: Virtual assistants and chatbots enhance support and sentiment analysis improves response quality.
Finance: AI aids in fraud detection, algorithmic trading, robo-advisors for wealth management, and compliance automation.
Manufacturing: AI optimizes quality control, predictive maintenance, supply chain, and robotics for increased productivity.
Transportation: Self-driving vehicles, traffic management, route optimization, and drone delivery enhance safety and efficiency.
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🧠 Cognitive Computing
Cognitive computing represents the pinnacle of artificial intelligence, simulating human thought processes within a computerized model. It encompasses self-learning systems utilizing data mining, pattern recognition, and natural language processing to emulate the complexity of human cognition. Unlike traditional AI, cognitive computing tackles ambiguous and uncertain scenarios, making a new class of problems computable.
While cognitive computing and AI are currently in the limelight, their roots trace back decades. Early applications, like expert systems in medicine, showcased the potential of AI. However, the journey towards realizing AI's promise has been marked by hype cycles and occasional setbacks.
Practical Applications
Cognitive computing and AI offer transformative potential across various domains:
Enhancing Decision-Making
Cognitive computing augments human decision-making capabilities by providing relevant insights promptly. It empowers individuals to make better decisions, act swiftly, and achieve successful outcomes.
Augmenting Human Capabilities
Cognitive computing tools, such as IBM Watson and expert systems, extend human capabilities in understanding, deciding, and acting. They serve as invaluable aids in navigating complex situations and avoiding potential pitfalls.
Future Directions
The potential of cognitive computing is vast, but realizing its full benefits requires identifying compelling use cases and overcoming implementation challenges. As organizations continue to explore the possibilities, cognitive computing stands poised to revolutionize decision-making and problem-solving across industries.
🤖 Google suspends Gemini from making AI images after backlash LINK
Google has temporarily halted the ability of its Gemini AI to create images of people following criticisms over its generation of historically inaccurate and racially diverse images, such as those of US Founding Fathers and Nazi-era soldiers.
This decision comes shortly after Google issued an apology for the inaccuracies in some of the historical images generated by Gemini, amid backlash and conspiracy theories regarding the depiction of race and gender.
Google plans to improve Gemini's image generation capabilities concerning people and intends to re-release an enhanced version of this feature in the near future, aiming for more accurate and sensitive representations.
🛑 AI researchers' open letter demands action on deepfakes before they destroy democracy LINK
An open letter from AI researchers demands government action to combat deepfakes, highlighting their threat to democracy and proposing measures such as criminalizing deepfake child pornography.
The letter warns about the rapid increase of deepfakes, with a 550% rise between 2019 and 2023, detailing that 98% of deepfake videos are pornographic, predominantly victimizing women.
Signatories, including notable figures like Jaron Lanier and Frances Haugen, advocate for the development and dissemination of content authentication methods to distinguish real from manipulated content.
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