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141 Terms

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Sustainable Development Goals

A set of 17 global goals adopted by the United Nations in 2015 to address social, economic, and environmental challenges for a sustainable future.

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No poverty

Goal to end all forms of poverty and protect the poor and needy.

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Zero hunger

Goal to end hunger worldwide and ensure access to food and nutrition.

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Good health and wellbeing

Goal to ensure healthy lives and lower mortality rates.

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Quality education

Goal to provide quality and free education for all.

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Gender equality

Goal to achieve equality for girls and women and end discrimination and violence.

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Clean water and sanitation

Goal to ensure access to clean water, sanitation, and hygiene.

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Affordable and clean energy

Goal to provide affordable, reliable, and sustainable energy for all.

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Decent work and economic growth

Goal to promote fair and decent employment and sustainable economic growth.

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Industry, innovation, and infrastructure

Goal to build resilient infrastructure, promote innovation, and access to technology.

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Reduce inequalities

Goal to reduce inequalities for all social groups.

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Sustainable cities and communities

Goal to have accessible housing, sustainable transport, and disaster risk management.

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Responsible consumption and production

Goal to ensure sustainable consumption and production patterns.

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Climate action

Goal to fight the climate crisis and promote awareness and policy change.

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Life below water

Goal to protect the ocean and marine life from pollution and overfishing.

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Life on land

Goal to conserve and restore ecosystems and prevent habitat destruction and biodiversity loss.

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Peace, justice, and strong institutions

Goal to build peaceful and inclusive societies with law and accountability.

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Partnerships for the goals

Goal to strengthen international cooperation and support developing countries in sustainable development.

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Importance of SDGs

The SDGs are important for addressing global challenges, promoting holistic development, having a universal scope, leaving no one behind, fostering partnerships, and ensuring monitoring and accountability.

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Use of technology to achieve SDGs

Technology plays a crucial role in achieving the SDGs by providing innovative solutions, improving efficiency, enabling access to information, and promoting collaboration.

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Advantages of digital products

Convenience, cost efficiency, scalability, easy updates and upgrades, flexibility, and customisation.

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Disadvantages of digital products

Digital divide, dependency on technology and infrastructure, potential for piracy and copyright infringement, lack of tangibility, and security and privacy concerns.

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Advantages of physical products

Tactile experience, perceived value, no dependency on technology, and physical ownership.

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Disadvantages of physical products

Higher production and distribution costs.

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Limited reproducibility and scalability

The need for individual production, packaging, and distribution of physical units, which can be time-consuming and costly.

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Inventory management and obsolescence

The risk of financial losses and product obsolescence due to overstocking or understocking and changing consumer preferences or market demands.

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Environmental impact

The contribution of physical products to resource depletion, pollution, and waste generation through the use of raw materials, energy, and transportation.

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Impact on the economy

The increased productivity and efficiency brought about by digital products through automation, streamlined processes, and digital tools.

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New business models and industries

The opportunities created for entrepreneurs and startups through e-commerce platforms, digital marketplaces, and software-as-a-service (SaaS) models.

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Job creation and transformation

The generation of employment in software development, digital marketing, data analytics, and e-commerce logistics, as well as the displacement of jobs in traditional industries.

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Impact on culture

The global connectivity and communication facilitated by digital products, enabling cultural exchange, idea sharing, and virtual communication.

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Access to information and knowledge

The increased accessibility of online libraries, educational resources, and search engines, bridging the digital divide and empowering individuals with information.

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Transformation of creative industries

The changes in content production, distribution, and consumption brought about by online platforms and streaming services, creating opportunities and challenges for artists, filmmakers, writers, and content creators.

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Cultural preservation and digitization

The wider accessibility, conservation, and protection of books, photographs, artworks, and historical documents through digitization.

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Emergence of digital media and entertainment

The shifts in business models and revenue streams in the entertainment industry due to streaming platforms, online gaming, and digital content creation.

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Impact on the environment

The potential for environmental sustainability through remote work, reduced commuting, and decreased demand for physical goods, as well as the challenges posed by electronic waste.

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Impact on ethics

The ethical considerations raised by the collection and use of personal data, as well as the ethical use of AI and automation in employment and decision-making processes.

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Impact on designing digital products

The use of design thinking, agile methods, user interface (UI) design, and user experience (UX) design in the creation of digital products.

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Low code no code technology

The democratization of technology use through low code and no code tools, enabling business users to create their own solutions and improving productivity, agility, and cost savings.

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Opportunities of low code no code technology

The potential for increased productivity, cost savings, and collaborative work, as well as the ability to address delays in application development and replace paper-based processes.

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Impact of generative AI on no code

The opportunities for innovation, specialisation, collaboration, and market growth presented by the proliferation of AI tools and startups.

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Artificial intelligence types

The classification of AI into artificial narrow intelligence (ANI), artificial general intelligence (AGI), and artificial superintelligence (ASI) based on their capabilities.

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Artificial general intelligence (AGI)

The concept of a machine with general intelligence similar to that of a human, capable of solving any problem in any given situation.

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Natural language processing, understanding, and generation

The processes involved in natural language generation (NLG), discourse generation, lexical choice, sentence planning/generation, realisation, document structuring, named entity recognition, part-of-speech tagging (POS), syntactic parsing, conference resolution, machine translation, lexical ambiguity/analysis, sentiment analysis, topic classification, information extraction, entity detection, summarization, semantic parsing, and syntactical analysis.

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Application of machine learning

The use of machine learning in various applications, such as text analysis, image recognition, speech recognition, recommendation systems, and predictive modeling.

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Ethics guidelines for trustworthy AI

The seven key requirements for trustworthy AI, including human agency and oversight, technical robustness and safety, privacy and data governance, transparency, diversity, non-discrimination and fairness, environmental and societal well-being, and accountability.

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The AI debate

The discussion surrounding the development of superintelligent general AI, including the beneficial AI movement, digital utopians, concerns about regulation, the potential of AI to solve problems and improve human life, the need for robust and bug-free AI systems, and the potential risks to human autonomy, rights, and dignity.

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Generative AI

The use of algorithms to create new content, including audio, code, images, text, simulations, and videos, leveraging sophisticated machine learning techniques to produce fresh and original content.

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Types of generative AI models

The different methodologies and strengths of generative adversarial networks, variational autoencoders (VAEs), diffusion models, and transformer-based models in generating new and compelling content.

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Applications of generative AI

The use of generative AI

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Sentiment Analysis

The process of determining the sentiment or emotion expressed in a piece of text.

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Language Translation

The task of converting text from one language to another.

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Text Summarization

The process of condensing a piece of text to its main points or key ideas.

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Traditional NLP Techniques

Conventional methods used in Natural Language Processing, such as text extraction and rule-based approaches.

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Transformer-based Architectures

Neural network architectures that are effective in capturing the sequential nature of text data and accounting for long-range dependencies.

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Knowledge Limitation

The fact that AI models only have knowledge up to the point when they were last trained.

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Generative Image Models (GIMs)

Models capable of capturing the structure and patterns within image data to generate new images.

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Diffusion Models

Recent models that combine the strengths of Generative Adversarial Networks (GANs) and Variational Autoencoders (VAEs) to generate images.

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Generative Video Models (GVMs)

Models designed to comprehend the temporal dynamics and spatial relationships within video data.

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Generative Audio Models (GAMs)

Models that capture the time-sequential patterns and nuances within audio data.

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Ecosystem of Generative AI

The dynamic and evolving network of hardware providers, software developers, data scientists, and application builders working together to advance Generative AI.

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Plugins

Software components that add specific features to existing programs, enhancing their functionality and versatility.

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Prompt Engineering

An AI technique that involves crafting input instructions to guide language models in understanding tasks and producing desired responses.

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Text Prompts

Instructions given to language models, including role, task description, examples, context, and question.

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Model Hyperparameters

Configuration settings that control different aspects of a language model's behavior, such as temperature and top p.

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Temperature

A measure of how frequently a language model outputs less likely words, with higher values leading to more creative outputs.

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Top p

A mechanism that controls the randomness of a language model's output by selecting tokens whose cumulative probability exceeds a threshold.

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Image Prompts

Instructions given to generative image models, including subject, medium, style, artist, website, resolution, color, and additional details.

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Best Practices for Prompting

Guidelines for creating effective prompts, including starting simple, being detailed and consistent, framing from the positive, and using artist styles sparingly.

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Biotechnology

The discipline that applies advances in molecular biology to various fields, such as health, agriculture, environment, and biochemical manufacturing.

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Genetic Engineering

The process of modifying an organism's DNA to alter its form or function, often done in a laboratory setting.

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Gene

The basic physical and hereditary unit, consisting of DNA sequences that encode proteins and determine certain functions in organisms.

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Central Dogma

The principle that genetic information flows from DNA to RNA to protein, representing the basic language of life.

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CRISPR Technology

A revolutionary gene editing technology that allows precise modifications to genomic DNA using CRISPR-Cas9 or other techniques.

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Genomic Data

Large-scale genetic data that can be studied, curated, and treated as computational code, enabling advancements in precision medicine and other fields.

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Precision Medicine

A medical approach that tailors treatments to individual patients based on their genetic makeup, lifestyle, and environmental factors.

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Digital Healthcare

The use of big data and analytics to improve wellbeing activities, predict diseases, prevent treatments, and enhance treatment outcomes.

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Synthetic Biology

The use of engineering principles to design and build novel life forms for sustainable production of bioenergy, materials, drugs, and food.

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Bioprinting and Tissue Engineering

Techniques that involve the printing of tissues and the creation of genetically tailored animals to produce human organs for transplantation.

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Ecological Engineering

The application of agrotechnology and engineered ecosystems to optimize food production, decontamination, pollution prevention, and energy use in a sustainable and efficient manner.

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Nanotechnology

The technology that allows manipulation of matter on a near-atomic scale to produce new structures, materials, and devices.

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Nanoparticles

Particles with sizes ranging from 1 to 100 nanometers, used in various fields such as electronics, medicine, energy, and environmental science.

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Nanomaterials

Materials that are lighter, stronger, more durable, and more reactive at the nanoscale, with enhanced electrical conductivity and complex architectures.

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Nanosensors

Tiny devices made from nanomaterials that measure physical, chemical, biological, or environmental information at the nanoscale level and transfer it into data for analysis.

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Nanodevices

Devices with at least one overall dimension in the nanoscale or comprising one or more nanoscale components essential to its operation. They can be reduced in size to the nanoscale and make use of the unique properties of nanomaterials to detect and measure events at the nanoscale.

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Safety concerns for nanomaterials and nanodevices

Due to the rapid evolution of nanotechnology, regulations surrounding nanomaterials and nanodevices are still in development, affecting research and policymaking specific to each field of application.

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Nanomanufacturing

The process of manufacturing at the nanoscale, involving the scaled-up, reliable, and cost-effective manufacturing of nanoscale materials, structures, devices, and systems.

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Applications of nanotechnology

this is improving and changing various technology and industry sectors, including electronics, energy, biomedicine, the environment, and food safety.

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Nanomaterials for industrial uses

Advances in nanomaterials have opened up new possibilities in various industries, including the use of nanoparticles, carbon nanotubes (CNTs), and nanocomposites for stronger materials and accelerated material science.

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Nanotech for electronics and photonics

Nanoscale materials are used in IT and electronic applications due to their electrical and optical properties, enabling smaller, faster, portable, and more efficient electronic devices.

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Nanomedicine - biomedicine and healthcare

Nanotechnology enables targeted drug delivery systems, improved imaging techniques, and sensitive diagnostic tools, specifically targeting disease cells or delivering drugs with greater precision and efficacy.

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Nanostructures - energy

Nanotechnology is being explored for energy-related applications, including solar cells, energy storage devices, and fuel cells, aiming to reduce energy consumption, environmental toxicity burdens, and develop clean, affordable energy.

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Climate technologies

The application of technology and innovation to mitigate and adapt to the challenges posed by climate change, promoting sustainability, energy efficiency, and reducing greenhouse gas emissions.

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Sustainable agriculture and farming

this aims to reduce the environmental impact of farming practices, including precision agriculture techniques, smart irrigation farming systems, organic farming methods, and innovative approaches for crop/livestock protection and nutrient management.

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Energy storage

Technologies vital for balancing the intermittent nature of renewable energy sources, including advanced batteries, pumped hydro storage, compressed air energy storage, and thermal energy storage.

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Waste management

Technologies for innovative waste management and recycling solutions, reducing waste generation, promoting recycling and reuse, and minimising the environmental impact of waste disposal.

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Internet and the data economy

The origin and evolution of the internet, its protocols, and the rise of big corporations shaping the online landscape.

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Data economy

The collection, analysis, and monetization of data, providing valuable insights for decision-making, personalization, operational efficiency, and innovation.

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Data generation

The continuous creation of data from various sources, including traditional business operations, social media interaction, and IoT devices.

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Data collection

The gathering of data from various sources, including direct customer interactions, digital platforms, third-party data brokers, or publicly available data.