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An overview of past AI and text creation works
The section summarizes AI and text creation research. Recent AI developments have dramatically influenced text generation. Artificial intelligence and natural language processing research has improved by simplifying language models and applying deep learning. However, previous study has found constraints. Some AI-based text-generating models have consistency, coherence, and copyright issues. Many areas and services can automate and speed up content generation with AI models. This research aims to improve previous studies and construct a more robust and creative AI model to improve text output.
AI Model and Technologies
• Deployed AI model functionality: AI generates text and articles. The latest NLP approaches empower models. Language-specific deep learning neural network AI. Many corpora teach language structures. The model's multilayered linked neurons analyze complicated language with success. With their vast vocabulary and simple syntax and semantics, AI models can produce contextually relevant and coherent phrases across languages and disciplines. Using complex algorithms and text creation data, AI models predict words. Context is flexible language. We create language through backpropagation and gradient descent in our AI model. Language changes prompt model content to adapt. To conclude, a cutting-edge NLP-based neural network lets the AI model grasp and use various language patterns and context to generate high-quality content.
• Used natural language processing: Advanced AI employs NLP. Text is generated by NLP from speech. Understanding written language's meaning, structure, and context, our AI model's NLP algorithms provide coherent and useful information. Text-based NLP approaches like Named Entity Recognition may classify persons, businesses, places, and dates for AI models. AI gains facts. Grammar labels enhance our AI system's word functions and links with POS tagging. NLP sentiment analysis. Matching emotional tone to writing style helps AI deliver text's instructional, persuasive, or emotive meaning. The NLP multilingual text processing AI model meets our worldwide users' linguistic demands. This AI system's text analysis calculates words and phrases using strong tokenization and word embedding. Our AI model creates high-quality, relevant content for many applications using NLP to assess language and context.
• Training and updating models: Learning-based AI model creates high-quality content. Huge data sets teach AI language-learning models. AI model training requires a large corpus of literature from many areas and languages. Instances generalize model. Less language synthesis errors and more neural network parameters enhance backpropagation and gradient descent models. Quality is assessed via AI model training. Writing improves with AI after training. AI helps write. Improved language, industry trends, and user input. Keeping NLP and language modeling updated helps the AI model generate more accurate and engaging content. Future-proof AI keeps up with user needs and leads text creation technology with quick upgrades. Our latest AI model outputs autonomous text.
Safety and Morality
1. Protective measures against harmful applications: We protect our AI-powered text producing technology. We regularly evaluate user-generated material to ensure appropriate use. No hate speech, prejudice, or destruction is promoted by our AI model. AI system security safeguards user data and content from hackers. Our terms of service and acceptable usage standards provide use limitations and banned items. Our service allows users to report dangerous or unethical material. As risks develop, we modified our AI model's filtering to detect and block hazardous content that may escape safety protections. Our platform follows ethical and best practices thanks to industry leaders, AI ethicists, and lawmakers.
2. Focus on ethics and AI use: Our project emphasizes AI ethics. We value AI's societal effect and ethical deployment. After AI ethics study and expert consultation, our development and implementation process was ethical. Our AI is ethical, fair, and responsible. Content is harmless and impartial. Our respect for intellectual property and copyright laws requires users to attribute AI-generated content. Data security and privacy are important. We safeguard and acquire consent for user data. Instructors and recommendations enhance AI biases and hazards awareness. We improve and stay ethical with AI ethicists, regulators, and users. Our study aims to encourage ethical AI technologists.
ROADMAP
2022 Q4: Concept Generation and Identification of Team Tasks
2023 Q1: Validation and Development of the Concept's Viability
2023 Q1: Completion of the Whitepaper
2023 Q2: Backend Preparation for Token Launch
2023 Q2: Launching Token O ering Phase
2023 Q4: Listing of BiCity on Prominent Cryptocurrency Exchanges
2024 Q1: Announcement of Major Partnership for BiCity Listing on Various Cryptocurrency Exchanges
2024 Q2: Launch of Beta Version of BiCity's Android and iOS App
2024 Q4: Release of Full Version of BiCity's Android and iOS App Listing on Major Global Cryptocurrency Exchanges
2025 Q1: Evaluation of Market Developments and Use Cases Strengthening Investor Relations and Regular Update Releases Enhancing Technical Infrastructure and Security Measures
2025 Q2: Cultivation of New Business Partnerships to Expand BiCity Ecosystem Advancement of Smart Contract Capabilities and Diversification of Use Cases
2025 Q3: Reinforcement of Marketing and Advertising Strategies to Expand BiCity User Base O ering Community Engagement Activities and Enriching Content
2025 Q4: Pivot towards DeFi (Decentralized Finance) Integrations within the BiCity Platform Participation in Global Media and Events to Heighten Worldwide Recognition
2026: Provision of Application and Operational Development Tools for the BiCity Ecosystem Initiation of Projects and Collaborations in Social Impact and Sustainability
2027: Incorporation of User Feedback into Continuous Platform Enhancement Innovation in Digital Asset Management and Educational Initiatives
In conclusion, AI-driven text producing technologies might change content production. Businesses, schools, content providers, and academics utilize our AI platform to produce high-quality content in several languages and formats. Our AI model's versatility allows marketing, e-commerce, education, and journalism to use efficient and creative content solutions. Our trustworthy, user-centric platform respects ethical principles and encourages transparency by prioritizing ethical issues and responsible AI use. We are assessing user feedback and adding language support, advanced AI technology, and novel uses beyond text generation. We want to do cutting-edge research, form strategic partnerships, and lead AI-driven content development. Our innovative and collaborative endeavor aims to change global content development, dissemination, and consumption.
For more information visit:
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Whitepaper: https://www.bicity.com/wp-content/uploads/2023/08/bicity-whtie-paper.pdf
AUTHOR
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