2024 Bored Peanut Outlook Series with ChatGPT #3.

This time, these are the start-ups and Nature papers that will be coming up in 2024. #BelieveIt or Not

Let’s predict that notable start-ups in AI and LLM will appear in 2024. These predictions are based on current technology trends and future market demand.

1. NeuroSync: specializes in the development of advanced machine learning algorithms via brain-computer interface (BCI).
2. QuantumLeap AI: Delivering the next generation of machine learning solutions that combine quantum computing and AI.
3. EcoAI Analytics: AI-powered data analytics services for sustainability and environmental protection.
4. MediPredict: Customized medical diagnosis and treatment plan proposal service using LLM.
5. AgriGrowth AI: Development of agricultural optimization and crop management systems using AI.
6. CyberGuard AI: AI-powered threat detection and response solutions in cybersecurity.
7. Creative AI Studio: Design and creation support services using AI.
8. EduAI Tech: Developing a personalized AI-based education and learning platform.
9. SmartCity AI Solutions: AI analytics and optimization tools for urban planning and management.
10. HealthTrack AI: LLM-based health monitoring and prediction systems combined with wearable devices.

Next, let’s predict AI-related scientific achievement paper titles that are expected to be published in prominent scientific journals such as Nature in 2024.

1. “MIT’S INNOVATION: Optimizing Neural Networks Using Quantum Computing”
2. “Stanford University: Developing a New Form of Anti-Cancer Drug Using AI”
3. “Harvard Medical School: A Customized Disease Prediction Model Based on LLM”
4. “Caltech: Analyzing Space Exploration Data Using Artificial Intelligence”
5. “University of Cambridge: AI-led Climate Change Response Strategy”
6. “Max Planck Institute: Language Restoration Technology Using Advanced AI Algorithms”
7. “CERN: AI Applications for Large Hadron Collider (LHC) Data Analysis”
8. “NASA and AI: New Horizons in Space Mission Using Advanced Robotics”
9. “Imperial College London: AI-led Next Generation Energy Storage System”
10. “Tsinghua University: Deep Sea Exploration and Ecosystem Monitoring with AI,” predicted by ChatGPT as a simple peanut in 2024.

The second field is the competition between open-source LLM and commercial LLM, the performance based on the number of parameters, the development of AGI, and the development of medical devices utilizing LLM in the medical field.

It’s a teen news story. #Believe or not

1. 1. “GPT-6 vs. OpenAI’s Latest: The Battle of Open-Source and Commercial LLMs Intensifies”
2. 2. “Trillion-Parameter LLMs: Breaking New Ground in Language Understanding and Generation”
3. 3. “AGI Milestone Achieved: AI Model Exhibits Near-Human Level Cognitive Skills”
4. 4. “FDA Approves First LLM-Integrated Medical Device for Personalized Diagnosis”
5. 5. “AI in Healthcare: LLM-Powered Predictive Models Revolutionize Patient Care”
6. 6. “The Rise of OpenAI Equivalents: Community-Driven LLMs Challenge Industry Giants”
7. 7. “LLM in Drug Discovery: AI Models Accelerate Path to New Pharmaceutical Breakthroughs”
8. 8. “Scaling AI: How Larger LLMs Are Redefining Performance Benchmarks”
9. 9. “AI Ethics in Focus: AGI Development Sparks Global Regulatory Conversations”
   10. “LLM-Enhanced Wearables: The New Frontier in Real-Time Health Monitoring”

The reasons for choosing it as a forecast for 2024 are as follows.

1. Competition between open source and commercial LLM:
   • 2023: Commercial LLM prevails, but the growth of the open-source community begins.
   • 2024: Open source LLM makes significant progress, intensifying competition with commercial models.
2. Number of parameters and performance:
   • 2023: Models with tens of billions of parameters are mainstream.
   • 2024: Trillian parameter models emerge, enabling more complex and sophisticated tasks than previous models.
3. AGI Advancement:
   • 2023: Early stage research and theoretical approach to AGI development.
   • 2024: AGI models begin to exhibit cognitive abilities close to human levels.
4. LLM integration into medical devices:
   • 2023: early application of LLM in healthcare.
   • 2024: FDA formally approves medical devices incorporating LLM, starting use in real-world medical settings.
5. LLM utilization in healthcare:
   • 2023: Medical research and experimental application with LLM.
   • 2024: Predictive models using LLM play a key role in patient care and diagnosis.
6. Rise of community-led LLM:
   • 2023: Open source LLM is establishing its position as a replacement for early stage, commercial models.
   • 2024: Community-led open-source LLM achieves significant performance improvements, becoming a practical alternative to commercial models.
7. LLM utilization in drug discovery:
   • 2023: Drug discovery studies using LLM begin and derive initial results.
   • 2024: Drug discovery methodology through LLM develops more systematically and efficiently, accelerating the drug development process.
8. LLM Performance Benchmarks:
   • 2023: Existing LLM performance evaluation and benchmarking.
   • 2024: LLM with Trillian parameters sets a new performance benchmark, widening the performance gap with previous models.
9. AI Ethics and AGI Regulation:
   • 2023: initial discussion and policy making attempts on AGI and AI ethics.
   • 2024: Global regulatory and ethical standards following the development of AGI are clearly laid out, and the need for international cooperation is increased.
10. LLM Integrated Health Monitoring Wearable:
    • 2023: Initial development and testing of wearable health monitoring technology using LLM.
    • 2024: Advanced health monitoring wearables incorporating LLM are commercialized, revolutionizing real-time health tracking and diagnosis. Simpuri is 2024, forecasting it as ChatGPT as lightly as peanuts.

The first area is the title of the arXiv paper, which will appear like a comet in 2024. #BelieveIt or Not

1. 1. “Self-Evolving Artificial Intelligence: Integration of Real-Time Learning and Adaptation Mechanisms”
2. 2. “High-Speed Machine Learning Algorithms Utilizing Quantum Computing”
3. 3. “Human-Machine Interaction: Latest Advances in Emotional Recognition and Response Technologies”
4. 4. “New Deep Learning Architectures for Maximizing Data Efficiency”
5. 5. “AI for Environmental Sustainability: Optimization and Resource Management Methodologies”
6. 6. “AI-Based Design of Personalized Cancer Treatment Strategies through Micro RNA Analysis”
7. 7. “Creative Content Generation by Artificial Intelligence: New Horizons in Art, Music, and Literature”
8. 8. “Neural Network Models for Integrating Multimodal Data: Fusion of Image, Text, and Audio”
9. 9. “Ethical Decision Making in AI: Algorithmic Responsibility and Transparency”
   10. “The Convergence of Artificial Intelligence and Robotics: New Frontiers in Autonomy, Collaboration, and Interaction”

The differences between 2023 and 2024 in the above papers are as follows.

1. Self-evolving AI:
   • 2023: early-stage self-learning algorithms and adaptation techniques.
   • 2024: more advanced and efficient real-time learning and adaptability, increasing applicability in real-world environments.
2. Quantum computing and machine learning:
   • 2023: Basic machine learning research using quantum computing.
   • 2024: Reaching the stage of practical use of high-speed machine learning algorithms using quantum computing.
3. Human-machine interaction:
   • 2023: Basic Emotional Awareness and Response Skills.
   • 2024: more sophisticated emotional awareness and interaction skills, broad application in real life.
4. Data Efficiency:
   • 2023: Developing an initial model for optimizing data usage.
   • 2024: A practical application of advanced deep learning architectures that maximize data efficiency.
5. AI for environmental sustainability:
   • 2023