Coding is just like the language we use to talk to computers. It's not the skill itself, but rather how do I innovate? How do I build something interesting for my end users?
In a recently leaked recording, AWS CEO told employees that most developers could stop coding once AI takes over, predicting this is likely to happen within 24 months.
Instead of AI replacing developers or expecting a decline in this role, I believe he meant that responsibilities of software developers would be changed significantly by AI.
Being a developer in 2025 may be different from what it was in 2020, Garman, the CEO added.
Meanwhile, Amazon's AI assistant has saved the company $260M & 4,500 developer years of work by remarkably cutting down software upgrade times.
Amazon CEO also confirmed that developers shipped 79% of AI-generated code reviews without changes.
I guess with all the uncertainty, one thing is clear: Ability to quickly adjust and collaborate with AI will be important soft skills more than ever in the of AI.
In a recently leaked recording, AWS CEO told employees that most developers could stop coding once AI takes over, predicting this is likely to happen within 24 months.
Instead of AI replacing developers or expecting a decline in this role, I believe he meant that responsibilities of software developers would be changed significantly by AI.
Being a developer in 2025 may be different from what it was in 2020, Garman, the CEO added.
Meanwhile, Amazon's AI assistant has saved the company $260M & 4,500 developer years of work by remarkably cutting down software upgrade times.
Amazon CEO also confirmed that developers shipped 79% of AI-generated code reviews without changes.
I guess with all the uncertainty, one thing is clear: Ability to quickly adjust and collaborate with AI will be important soft skills more than ever in the of AI.
👍2
👩🏫🧑🏫 PROGRAMMING LANGUAGES YOU SHOULD LEARN TO BECOME.
⚔️[ Web Developer]
⚔️[ Game Developer]
⚔️[ Data Analysis]
⚔️[ Desktop Developer]
⚔️[ Embedded System Program]
⚔️[Mobile Apps Development]
⚔️[ Web Developer]
PHP, C#, JS, JAVA, Python, Ruby⚔️[ Game Developer]
Java, C++, Python, JS, Ruby, C, C#⚔️[ Data Analysis]
R, Matlab, Java, Python⚔️[ Desktop Developer]
Java, C#, C++, Python⚔️[ Embedded System Program]
C, Python, C++ ⚔️[Mobile Apps Development]
Kotlin, Dart, Objective-C, Java, Python, JS, Swift, C#👍7
Artificial Intelligence isn't easy!
It’s the transformative field that enables machines to think, learn, and act autonomously.
To truly excel in Artificial Intelligence, focus on these key areas:
0. Understanding AI Foundations: Learn the core concepts of AI, such as search algorithms, knowledge representation, and logic-based reasoning.
1. Mastering Machine Learning: Deepen your understanding of supervised and unsupervised learning, as well as reinforcement learning for building intelligent systems.
2. Diving into Neural Networks: Understand the architecture and workings of neural networks, including deep learning models, convolutional networks (CNNs), and recurrent networks (RNNs).
3. Working with Natural Language Processing (NLP): Learn how machines interpret human language for tasks like text generation, translation, and sentiment analysis.
4. Reinforcement Learning and Decision Making: Explore how AI learns through interactions with its environment to optimize actions and outcomes, from gaming to robotics.
5. Developing AI Models: Master tools like TensorFlow, PyTorch, and Keras for building, training, and evaluating machine learning and deep learning models.
6. Ethical AI and Bias: Understand the challenges of fairness, transparency, and ethical considerations when developing AI systems.
7. AI in Computer Vision: Dive into image recognition, object detection, and segmentation techniques for enabling machines to "see" and understand the visual world.
8. AI in Robotics: Learn how AI empowers robots to navigate, interact, and make decisions autonomously in the physical world.
9. Staying Updated with AI Trends: The AI landscape evolves quickly—stay on top of new algorithms, research papers, and applications emerging in the field.
AI is about developing systems that think, learn, and adapt in ways that mimic human intelligence.
💡 Embrace the complexity of building intelligent systems that not only solve problems but also innovate and create.
Free Books and Courses to Learn Artificial Intelligence👇👇
Introduction to AI Free Udacity Course
13 AI Tools to improve your productivity
Introduction to Prolog programming for artificial intelligence Free Book
Introduction to AI for Business Free Course
Top Platforms for Building Data Science Portfolio
Artificial Intelligence: Foundations of Computational Agents Free Book
Learn Basics about AI Free Udemy Course
Amazing AI Reverse Image Search
By focusing on these skills, you’ll gain a strong understanding of AI concepts and practical skills in Python, machine learning, and neural networks.
Like for more similar content ❤️
Join @free4unow_backup for more free courses
ENJOY LEARNING 👍👍
#artificialintelligence
It’s the transformative field that enables machines to think, learn, and act autonomously.
To truly excel in Artificial Intelligence, focus on these key areas:
0. Understanding AI Foundations: Learn the core concepts of AI, such as search algorithms, knowledge representation, and logic-based reasoning.
1. Mastering Machine Learning: Deepen your understanding of supervised and unsupervised learning, as well as reinforcement learning for building intelligent systems.
2. Diving into Neural Networks: Understand the architecture and workings of neural networks, including deep learning models, convolutional networks (CNNs), and recurrent networks (RNNs).
3. Working with Natural Language Processing (NLP): Learn how machines interpret human language for tasks like text generation, translation, and sentiment analysis.
4. Reinforcement Learning and Decision Making: Explore how AI learns through interactions with its environment to optimize actions and outcomes, from gaming to robotics.
5. Developing AI Models: Master tools like TensorFlow, PyTorch, and Keras for building, training, and evaluating machine learning and deep learning models.
6. Ethical AI and Bias: Understand the challenges of fairness, transparency, and ethical considerations when developing AI systems.
7. AI in Computer Vision: Dive into image recognition, object detection, and segmentation techniques for enabling machines to "see" and understand the visual world.
8. AI in Robotics: Learn how AI empowers robots to navigate, interact, and make decisions autonomously in the physical world.
9. Staying Updated with AI Trends: The AI landscape evolves quickly—stay on top of new algorithms, research papers, and applications emerging in the field.
AI is about developing systems that think, learn, and adapt in ways that mimic human intelligence.
💡 Embrace the complexity of building intelligent systems that not only solve problems but also innovate and create.
Free Books and Courses to Learn Artificial Intelligence👇👇
Introduction to AI Free Udacity Course
13 AI Tools to improve your productivity
Introduction to Prolog programming for artificial intelligence Free Book
Introduction to AI for Business Free Course
Top Platforms for Building Data Science Portfolio
Artificial Intelligence: Foundations of Computational Agents Free Book
Learn Basics about AI Free Udemy Course
Amazing AI Reverse Image Search
By focusing on these skills, you’ll gain a strong understanding of AI concepts and practical skills in Python, machine learning, and neural networks.
Like for more similar content ❤️
Join @free4unow_backup for more free courses
ENJOY LEARNING 👍👍
#artificialintelligence
👍3