9-Feb-2023: Quad Nations are launching Quad Cyber Challenge
Quad Cyber Challenge
- The Quad Nations are launching the Quad Cyber Challenge. The challenge aims to improve cyber security across the 4 nations.
- The challenge is a public campaign. Internet-users worldwide are being invited to join the Challenge.
- The challenge aims to promote safe and responsible cyber habits
- The National Cyber Security Coordinator with National Security Council Secretariat is coordinating the challenge.
Cybercrime and malicious cyber threats target internet-users worldwide. Cyber threats cost trillions of dollars each year and compromise sensitive, personal data.
Simple preventative measures can guard against cyber-attacks
Examples of preventative measures:
- Routinely installing security updates
- Utilizing stronger and regularly changing passwords
- Awareness of common online scams, like phishing
The Quad Nations comprise of India, Australia, the US, and Japan. The Quad Nations aim to ensure and support a “free, open and prosperous” Indo-Pacific region.
6-Feb-2023: Generative Artificial Intelligence (GAI) gathers steam
Generative Artificial Intelligence
- A rapidly growing branch of AI
- Focuses on generating new content based on learned patterns and rules
- Enabled by advanced generative models such as GANs and VAEs
Generative Models
- Trained on large amounts of data
- Able to generate new outputs similar to training data
- Examples: GANs, VAEs
GANs (Generative Adversarial Networks)
- Consist of a generator and a discriminator
- Generator creates new content
- Discriminator distinguishes between real and generated content
- Training process involves competition between the two components
VAEs (Variational Autoencoders)
- Consist of an encoder and a decoder
- Encoder compresses input data into a lower-dimensional representation
- Decoder generates new outputs based on the compressed representation
Applications
- Used in sectors such as education, manufacturing, healthcare, finance, and others
- Originally used for automating digital image and audio correction processes
- Can generate realistic synthetic images, audio, and text
- Also associated with ChatGPT and deep fakes
- Machine learning and deep learning can be considered types of GAI.
Applications of AI
Art and Creativity: AI can be used to generate new works of art that are unique and innovative, helping artists and creatives explore new ideas and push the boundaries of traditional art forms.
- DeepDream Generator: An open-source platform that uses deep learning algorithms to create surrealistic, dream-like images.
- DALL·E2: An AI model that generates new images from text descriptions.
Music: AI can help musicians and music producers explore new sounds and styles, leading to more diverse and interesting music.
- Amper Music: An AI-powered platform that creates musical tracks from pre-recorded samples.
- AIVA: Uses AI algorithms to compose original music in various genres and styles.
Computer Graphics: AI can generate new 3D models, animations, and special effects, helping movie studios and game developers create more realistic and engaging experiences.
Healthcare: AI can improve the accuracy and efficiency of medical diagnoses and treatments by generating new medical images and simulations.
Manufacturing and Robotics: AI can help optimize manufacturing processes, improving the efficiency and quality of these processes.
Significance for India
- AI employment in India: The overall AI employment in India is estimated at about 416,000 professionals with a growth rate of about 20-25%.
- Economic impact: AI is expected to contribute an additional USD 957 billion to India’s economy by 2035.
Concerns Related to GAI
- Accuracy: Developing advanced generative models to accurately capture the patterns and rules learned from data.
- Partisan GAI Models: Risk of biased outputs due to biased data. This can lead to discrimination and reinforce existing societal biases.
- Privacy: Risk of unethical use of personal and sensitive data for unethical purposes, such as for targeted advertising or for political manipulation.
- Ethical dilemmas over responsibility for malicious content: Since GAI models can generate new content, such as images, audio, or text it may be used to generate fake news or other malicious content, without knowing who is responsible for the output. This could lead to ethical dilemmas over responsibility.
- Automation and Lowering Job: GAI has the potential to automate many processes, which could lead to job displacement for people who are skilled in those areas. This raises questions about the ethics of using AI for job displacement and the potential impact on workers and society.
Related Indian Initiatives:
- National Strategy for Artificial Intelligence - To develop an ecosystem for the research and adoption of Artificial Intelligence.
- National Mission on Interdisciplinary Cyber-Physical Systems
- Technology Innovation Hubs on AI and Machine Learning at IIT Kharagpur to provide the state-of-the-art training and capacity building for the creation of next-generation scientists, engineers, technicians, and technocrats in the field of Artificial Intelligence.
- Artificial Intelligence Research, Analytics and Knowledge Assimilation Platform
- Aims to transform sectors like education, health, agriculture, urbanization and mobility.
28-Jan-2023: Scientists have developed Artificial Synapse for Brain-Like Computing or Neuromorphic Computing.
Artificial Synapse for Brain-Like Computing or Neuromorphic Computing:
- Developed by scientists at Jawaharlal Nehru Centre for Advanced Scientific Research.
- Uses scandium nitride (ScN) as a semiconducting material.
- ScN provides stable, Complementary Metal-Oxide-Semiconductor (CMOS)-compatible optoelectronic synaptic functionalities.
- Mimics synapse that controls signal transmission and remembers signals.
- Potential to be translated into an industrial product.
Working Mechanism
- Millions of artificial neurons in Artificial Neural Network model (ANN).
- Neurons pass signals in layers.
- Convert input to output through electric spikes or signals based on architecture of Spiking Neural Networks (SNN).
- Mimics neuro-biological networks in human brain.
- Performs tasks such as visual recognition and data interpretation.
Significance of Neuromorphic computing
- Revolutionary concept in realm of Artificial Intelligence.
- Provides better technology and rapid growth in computer engineering.
- Advanced process of information processing.
- Enables computers to work with better and bigger technology.
Expectations
- Brain-like computing can meet escalating computational demands in the era of artificial intelligence.
- Opens doors to better technology and more efficient data processing.
Traditional Computers vs. Human Brain
- Physically separated memory storage and processing units in traditional computers.
- Enormous energy and time required to transfer data between units.
- Human brain is a smaller and more efficient biological computer.
- Presence of synapse allows for processor and memory storage in one unit.