Deepfakes

Deepfakes upsc mind map
Context
Deepfake video
Rashmika Mandanna (actress)
Outrage online
Debunked by journalist
Featured British influencer
Zara Patel
Source
ET
What are Deepfakes
Digital media
Edited and manipulated
Using Artificial Intelligence
To inflict harm
Can damage
Reputation
Fabricate evidence
Defraud public
Undermine trust
In democratic institutions
Blend of terms
Deep learning
Subset of machine learning
Artificial neural networks
Fake
What countries are doing
China
New policy
Requires labelling
Traceability of doctored content
Prohibits production
Without user consent
European Union
Updated Code of Practice
Mandates tech companies
Google
Meta
Twitter
Counter deepfakes
United States
Deepfake Task Force Act
Department of Homeland Security
Counters deepfake technology
Bletchley Declaration
Twenty-eight countries
Collective action
Address risks of AI
Google
Introduces tools
Watermarking
Identify synthetic content
Paris Call
For Trust and Security in Cyberspace
Enhance trust and security
Global Partnership on AI
Collaborative effort
Ensure responsible AI development
Legal provisions in India
No specific laws
Against deepfake technology
Section 66E IT Act 2000
Indian Copyright Act 1957
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$Machine Learning and Artificial Intelligence Technology Hub (MATH) mind map Recent News Automated math for decision-making under uncertainty Research by MIT Addresses trading off risk and reward Useful across AI Climate Finance Fixes deep learning errors New algorithm aces university math Developed by MIT and others Answers university-level math problems 100% accuracy Enhances machine learning education When Recent advancements Highlighted in 2023 and 2024 Why Improve decision-making in uncertain scenarios Enhance accuracy and efficiency in math education What ADEV tool for probabilistic models Simplifies work with probabilistic models Applied in Climate modeling Financial modeling Operations research e.g., call center queues Machine-learning model for math problems Combines text and code Uses Program synthesis Few-shot learning Over 80% accuracy on unseen problems Where Massachusetts Institute of Technology (MIT) Who Researchers and academics Alex Lew Lead author, MIT PhD student Vikash Mansinghka Co-author, MIT's Probabilistic Computing Project Iddo Drori Project lead, MIT and Columbia University How ADEV tool Automates differentiation of expected values Probabilistic programming Machine learning model for math Pretrained on text and code Fine-tuned on code (Codex by OpenAI) Significance Facilitates experimental work with probabilistic models Opens new possibilities in AI and related fields Significantly improves learning and automation in education Challenges ADEV Perceived complexity of probabilistic models Machine learning model for math Limitations in visual components and computational complexity Way Forward Expand application areas Overcome current limitations and challenges Explore further integration into education and research$

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