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Generative AI approach to unsolved problems in Chemistry ,Math , Physics and Computer by analysis of massive data saving research cost and time .

A robot equipped with IoT (Internet of Things) devices and generative AI powered by GPT (Generative Pre-trained Transformer can become an intelligent and adaptive home assistant. Here's an idea on how such a robot could be useful:

1. Personalized Home Management:
The robot would learn the preferences and habits of the household members through conversation and observation. It could control various IoT devices, such as lights, thermostats, and security systems, to personalize the environment according to individual needs. For example, it could automatically adjust the temperature, lighting, and play preferred music based on the household member's prior choices.

2. Health and Wellness Companion:
With access to health-related IoT devices like smartwatches, fitness bands, and even medical sensors, the robot can serve as a health and wellness companion. It could monitor vital health metrics, remind individuals about medication schedules, offer personalized exercise routines, and even provide recommendations for healthy recipes or grocery shopping based on an individual's dietary needs.

3. Entertainment and Information:
The robot can act as a source of entertainment and information by leveraging its GPT-powered generative AI. It would understand natural language and have knowledge across various topics, making it capable of engaging in intelligent conversations, answering queries, and providing recommendations for movies, books, music, or other recreational activities. It could also act as a tutor, guiding individuals through educational content or providing assistance with homework.

4. Home Security and Automation in engineering sensing:
Integrated with a network of IoT security devices, such as cameras, motion sensors, and door/window sensors, the robot can enhance home security. It can detect unusual activities, identify intruders, and promptly notify homeowners or authorities. The generative AI can provide real-time insights and suggestions to optimize home automation, making the house more energy-efficient, secure, and convenient. Robot and generative GPT in construction automation is to leverage technology to enhance construction robotics, enabling them to perform tasks more efficiently, accurately, and safely, ultimately revolutionizing the construction industry. Road will be able to perform task based algorithm daily using neural networks connected to clouds with power CPU from Intel and GPU from NVida in large data center for computing.

5. Personalized Assistance and Task Management:
By keeping track of household tasks and utilizing natural language understanding capabilities, the robot can efficiently manage to-do lists, reminders, and schedules. It can help plan and prioritize tasks, manage shopping lists, and even order groceries online when needed. The robot would adapt approaches based on individual preferences and provide personalized recommendations to enhance productivity.

This integration of IoT devices with generative AI GPT technology in a robot would bring about a versatile and intelligent companion that can enhance various aspects of daily life, making the home experience more personalized, secure, and convenient.

telim:
You need maths to develop algoirthm. Without having a sound mathematical skills for developing formulars to process a specific task continuously you won't be able to develop logic to process real problems.

You need math if you want to work with Google, Intel ,Microsoft and Amazon because of data structure algorithm (DSA) to help you in problem solving interview questions

peterincredible:
Is this visual studio free and can I use it on Linux(Ubuntu)

U can use VScode for ASP.NET and console program

peterincredible:
Is this visual studio free and can I use it on Linux(Ubuntu)

Microsoft is retiring Mac but no Linux support yet . Only windows os for windows form .

https://visualstudio.microsoft.com/downloads/

Fluent UI blazor is now Opensource

Tools

Visual studio 2022

Sql server and SQL management studio

WinForms is a graphical user interface (GUI) framework developed by Microsoft for creating Windows desktop applications. It allows developers to design and build interactive and visually appealing applications with various controls and components.You use the designer and drag the controls from the toolbox in visual studio 2022 and create the main logic in C#







https://www.youtube.com/watch?v=plBPiTrLCoA?si=Ub5AsEC0jMolkbZ8



winform controls tutorials for beginners>>>

http://www.java2s.com/Tutorial/CSharp/0460__GUI-Windows-Forms/Catalog0460__GUI-Windows-Forms.htm

Coocon
SUPREMOTM
CodingSoft
Benjatoba
mark2k
Mention the once I missed

We now have ChefGPT and Farm GPT next is order GPT as an enterprise logistics AI platform.By leveraging the power of AI, Order GPT can automate and optimize numerous logistics processes, leading to improved efficiency, reduced costs, enhanced customer experiences, and ultimately, increased profitability for enterprise logistics operations.

The AI platform can provide real-time tracking of orders and shipments. It can integrate with GPS technology and logistics systems to monitor the movement of goods throughout the supply chain. Order GPT can also send automated notifications to customers, keeping them informed about the status of their orders and any potential delays.

The Windows UI Controls are a set of pre-built user interface components provided by Microsoft for designing and building Windows applications. These controls are designed to help developers create consistent and visually appealing user interfaces across different Windows devices and platforms. The latest is winUI 3 . The user interface is in XAML and the logic is in C# .


https://learn.microsoft.com/en-us/windows/apps/design/controls/

qtguru:
I use Github CoPilot

It is inbuilt in the lastest android studio but you sign with your Google mail . It is now available in Nigeria for all android developers .

Have anyone started using studio bot it is a Chatbot like ChatGPT but especially for mobile apps development in Android studio

parkervero:
Thank you.

Bookmarked already.


I've been using bezkoder for some time now l.

U are welcome

parkervero:
Could you recommend any Swagger book or course for my API documentation? I'm really good at it and I need a better explanation on it

Look at this tutorials with list of codes on swaggers 3 . The Swagger Codes is in config and close to spring security class .


https://github.com/bezkoder/spring-boot-swagger-3-example

parkervero:
I know. I just like the simplicity of thymeleaf in rendering view (although, it's not as aesthetic as Angular & React) than React & Angular.

Thymeleaf offers a lightweight and intuitive option for rendering views in Spring Boot applications .You are right in thymeleaf the components are still in simple HTML 5 just few differences while using Vue , Angular,or React the components are From scratch

parkervero:
Do you consider using thymeleaf to render view as a backend developer?

Yes but in Spring Boot, you can integrate various front-end frameworks and templating engines like React, Vue, Bootstrap, Angular and Thymeleaf .

Have you learn using HTTP mapping annotations in Controller all based on @RequestMapping

@GetMapping
@PostMapping
@PutMapping
@DeleteMapping
@PatchMapping


U will design the frontend and then the backend , models , entity and use the id or class of the frontend to the controller as usual

Puremind1225:
You sound like AI here,

I am not an AI

Learning coding through code architecture is an excellent approach as it emphasizes the organization, structure, and design principles of writing code. Here are some steps to learn coding through code architecture in spring boot 3 .



https://github.com/bezkoder/spring-boot-3-rest-api-example


https://github.com/Sirajuddin135/E-Commerce-Application

https://github.com/nahwasa/spring-security-basic-setting-for-spring-boot-3


https://github.com/Zhuohua-Huang/Springboot-Vue-Javaweb-Project-SCUT

https://github.com/macrozheng/mall/tree/master


https://github.com/ZHENFENG13/My-BBS

1. Set Clear Goals: Clearly define what you want to achieve with coding. Identify the specific programming languages or technologies you want to learn and the projects you want to work on. Having clear goals will help you stay focused and motivated.

2. Start with Fundamentals: Begin by mastering the basics of programming concepts, such as variables, data types, loops, conditionals, and functions. This foundation will make it easier to grasp more complex concepts later on.

3. Choose a Learning Path: Select a structured learning path that suits your learning style. Online platforms like Codecademy, Coursera, or FreeCodeCamp offer comprehensive courses and tutorials for various programming languages. Follow their curated curriculum to ensure a logical progression in your learning journey.

4. Practice Regularly: Consistency is key. Dedicate regular time to coding practice, ideally daily or multiple times per week. Regular practice helps reinforce concepts, build muscle memory, and improve problem-solving skills.

5. Build Projects: Apply what you learn by building projects. Projects provide hands-on experience, help you understand real-world applications, and strengthen your problem-solving abilities. Start with small projects and gradually work your way up to more complex ones.

6. Seek Resources and Support: Utilize online resources such as documentation, forums, and coding communities like Stack Overflow or Reddit. These platforms can help you find answers to specific questions or provide guidance when you encounter challenges.

7. Collaborate and Share: Engage with other learners or join coding communities where you can collaborate on projects, exchange ideas, and learn from others. Participating in coding challenges or hackathons can also enhance your coding skills and provide valuable feedback.

8. Break Down Problems: When faced with a coding challenge or task, break it down into smaller, manageable parts. This approach, called "divide and conquer," makes problem-solving more approachable and less overwhelming.

9. Embrace Mistakes , refactoring and Debugging: Coding involves trial and error. Embrace mistakes as learning opportunities and be patient with the debugging process. Debugging skills are crucial for identifying and fixing issues in your code.

10. Stay Updated: The tech industry evolves rapidly. Stay updated with the latest trends, best practices, and new technologies by following relevant blogs, newsletters, or podcasts. Continuous learning ensures you stay relevant and adaptable.


11. Learn coding through code architecture is an excellent approach as it emphasizes the organization, structure, and design principles of writing code. Here are some steps to learn coding through code architecture. Observation of samples codes on GitHub, documentations and on articles .

12 . By using Chatbot like bard or ChatGPT to explain the codes in more simpler terms for beginners to understand.

Remember, learning to code is a journey, and everyone progresses at their own pace. Enjoy the process, be persistent, and celebrate your achievements along the way.

Temyaz:
Please,who have a j2me phone that can give me?
i want use it for programming

U will love this


http://www.java2s.com/Tutorial/Java/0430__J2ME/Catalog0430__J2ME.htm

In healthcare GPT needs real-time visualization and analysis of simulation result Researchers can explore the data generated by the simulations or modelling in a dynamic and interactive manner, facilitating a deeper understanding of the compound and complex biology systems from the body. Using machine learning such system needs high end CPU and GPU to query large dataset of compounds or molecular biology from CT scan , MRI scan and X-RAY scan.

Microscopy techniques combined with advanced labeling methods, such as immunofluorescence and fluorescence resonance energy transfer (FRET), allow scientists to study molecular interactions and dynamics within living cells. Software/Application or plugin for molecular biology needs to be created .

Alphabyte2:
GPT is already making drug Discovery a reality and it can detect symptoms nearly accurate.
AI can assist in the design of new drugs and the optimization of existing ones, leading to faster and more efficient drug development processes. Medical generative AI is growing and we already have robot assistant which won't replace human . The goal is to make work easier.


AI video art you can generate a video using text prompt from an image it can even mimic normal human voice. The art is more futuristic in quantitative reasoning.

Coding with ChatGPT you gets all the answers about the codes in details. It is a tool that help you generate codes in fraction to build games , apps or website. Animation or short cartoon is done by prompt engineering . Argumented reality or VR AI assistant will help in teaching from a video recording software.

I made some predictions before some of these AI tools where created . You can make accurate predictions by analyzing patterns in data, but these predictions are based solely on the information and patterns . ChatGPT is not perfect but it is a good invention in the age of AI

Create MOBA game like league of legends using unity or unreal.These games often have a free-to-play model, where the base game is available to all players without any upfront cost. However, they may offer optional in-game purchases or ads rewards, allowing players to acquire items, character skins, or other enhancements. In some cases, the game also organize tournaments or competitive events where players can participate and potentially earn rewards or prizes. To enter these tournaments, players may need to pay an entry fee, which can be in the form of real money or in-game currency earned through gameplay.

tollyboy5:
I've not got any reason to use the stuff.

It is good for code review about warning or bugs and in education it can explain things in simpler terms for students to understand while learning. In cybersecurity it is faster to detect threat more AI are coming. Some advance robots are already running on ChatGPT. What people needs to be worried about is ethics and security.

Cognitive Artificial General Intelligence (AGI) refers to the development of highly autonomous systems that possess human-level cognitive capabilities across a wide range of tasks and domains.

Researchers and organizations are exploring different approaches to AGI, including machine learning, cognitive architectures, symbolic reasoning, and hybrid models that combine multiple techniques.

Autonomous agents powered by large language models (LLMs) have the potential to play a significant role in the development of drones, robotics, and autopilot systems for flying cars. These LLMs, such as OpenAI's GPT-3, are trained on vast amounts of data and can generate human-like text, making them valuable tools for various applications.

In the context of drones, LLMs can assist in tasks such as mission planning, obstacle avoidance, and real-time decision-making. By analyzing data from sensors and combining it with their language processing capabilities, LLM-powered autonomous agents can quickly process information and make complex decisions to ensure safe and efficient drone operations.

Similarly, in the field of robotics, LLMs can help in tasks like object recognition, natural language understanding, and human-robot interaction. By understanding and generating human-like text, these agents can facilitate seamless communication between robots and humans, enabling more intuitive and efficient collaboration.

When it comes to autopilot systems for flying cars, LLM-powered autonomous agents can assist in navigating complex airspace, route planning, and optimizing flight parameters. By leveraging their language processing capabilities, these agents can analyze and interpret real-time data, such as weather conditions and air traffic, to make informed decisions and ensure safe and efficient autonomous flight.

It's important to note that while LLMs have shown great promise in assisting with these tasks, they are not standalone solutions. They need to be integrated with other technologies such as computer vision, sensor fusion, and control systems to create robust and reliable autonomous systems.

Furthermore, the development of drones, robotics, and flying cars involves various legal, ethical, and safety considerations. Autonomous agents should be designed with these factors in mind, ensuring compliance with regulations and prioritizing safety at all times.

In conclusion, autonomous agents powered by LLMs have the potential to revolutionize the development of drones, robotics, and flying cars by enhancing their autonomy, decision-making, and human interaction capabilities. However, it's important to approach their integration with caution, considering the various challenges and ensuring a responsible and safe deployment.

Quantum LLMs are an exciting area of research, it is important to note that quantum computing is still in its early stages of development. Building practical and scalable Quantum LLMs is a significant challenge, as it requires advancements in both quantum hardware and quantum algorithms

The field of Quantum Natural Language Processing (QNLP) focuses on developing quantum algorithms and models for language processing tasks. QNLP researchers are exploring ways to leverage quantum computing's unique properties, such as quantum parallelism and quantum entanglement, to improve language models' efficiency, accuracy, and performance.

It means there will be a fusion between classical and quantum computing in future.

Youth unemployment rate:

🇿🇦 South Africa: 60.7%
🇳🇬 Nigeria: 53.4%
🇪🇸 Spain: 27%
🇷🇸 Serbia: 24.7%
🇱🇰 Sri Lanka: 23.8%
🇬🇷 Greece: 23.2%
🇦🇱 Albania: 22.5%
🇷🇴 Romania: 22.3%
🇮🇹 Italy: 22.09%
🇮🇷 Iran: 21.6%
🇨🇳 China: 21.3%
🇭🇷 Croatia: 20%
🇸🇰 Slovakia: 19.9%
🇵🇹 Portugal: 19.2%
🇪🇪 Estonia: 18.7%
🇹🇷 Turkey: 18.6%
🇱🇺 Luxembourg: 19.6%
🇸🇪 Sweden: 17.9%
🇯🇲 Jamaica: 16.7%
🇨🇾 Cyprus: 16.4%
🇫🇷 France: 16.2%
🇧🇪 Belgium: 14.2%
🇹🇼 Taiwan: 12.44%
🇬🇧 United Kingdom: 12.3%
🇫🇮 Finland: 12.1%
🇭🇺 Hungary: 12%
🇦🇹 Austria: 11.6%
🇩🇰 Denmark: 11.5%
🇨🇦 Canada: 11.3%
🇮🇪 Ireland: 11.2%
🇵🇱 Poland: 11.2%
🇳🇴 Norway: 10.7%
🇳🇿 New Zealand: 10.3%
🇸🇮 Slovenia: 10.3%
🇨🇿 Czechia: 9.8%
🇱🇻 Latvia: 8.7%
🇦🇺 Australia: 8.62%
🇳🇱 Netherlands: 8.6%
🇺🇸 United States: 8.6%
🇱🇹 Lithuania: 8.4%
🇻🇳 Vietnam: 7.41%
🇹🇭 Thailand: 6.5%
🇭🇰 Hong Kong: 6.1%
🇰🇷 South Korea: 6.1%
🇩🇪 Germany: 5.6%
🇯🇵 Japan: 4.2%
🇰🇿 Kazakhstan: 3.6%
🇨🇭 Switzerland: 2.2%


Source: world of statistics (X)

The repository is a valuable resource for developers who want to learn ASP.NET Core or enhance their existing skills. By exploring the code samples and examples, developers can gain practical insights into building real-world web applications with ASP.NET Core.


Practical-aspnetcore is a collection of practical examples and code samples for building web applications using ASP.NET Core. https://github.com/dodyg/practical-aspnetcore

Source: Artificial intelligence