How can I get up to speed on AI?

Anyone have any recs for useful AI programs or tools on their computer? 

What specifically are you looking for?

Industry events. From what I witnessed from a recent one I went to, VC investors on average seem to understand it better than most.

All in podcast

Getting up to speed on AI can seem daunting, but there are many resources available to help you learn about the fundamentals, applications, major themes, and key players in the field. Here's a roadmap to guide you:

1. Understand the Basics:

• Books: Start with introductory books like "Artificial Intelligence: A Guide to Intelligent Systems" by Michael Negnevitsky or "Artificial Intelligence: Foundations of Computational Agents" by David L. Poole and Alan K. Mackworth.
• Online Courses: Platforms like Coursera, Udacity, and edX offer beginner-friendly courses on AI, such as "Introduction to Artificial Intelligence" by Stanford University on Coursera or "Artificial Intelligence for Beginners" on Udacity.
• YouTube Channels: Channels like Two Minute Papers, sentdex, and AI for Everyone provide accessible explanations of AI concepts.

2. Learn about Major Themes:

• Machine Learning: Understand the basics of machine learning algorithms, including supervised learning, unsupervised learning, and reinforcement learning.
• Deep Learning: Explore neural networks, convolutional neural networks (CNNs), recurrent neural networks (RNNs), and deep learning frameworks like TensorFlow and PyTorch.
• Natural Language Processing (NLP): Learn about how AI processes and understands human language, including tasks like sentiment analysis, text generation, and language translation.
• Computer Vision: Dive into the field of computer vision, which focuses on teaching machines to interpret and understand visual information.

3. Stay Updated on Industry Trends:

• Follow AI News: Subscribe to newsletters, follow AI-focused websites (e.g., Towards Data Science, Synced, AI Weekly), and join AI communities on platforms like Reddit and LinkedIn.
• Attend Conferences and Webinars: Keep an eye out for conferences like the Conference on Neural Information Processing Systems (NeurIPS), the International Conference on Machine Learning (ICML), and webinars hosted by companies like NVIDIA and Google.

4. Explore Key Companies:

• Big Tech Companies: Research major players like Google (Google Brain), Facebook (FAIR), Amazon (AWS AI), Microsoft (Microsoft Research), and IBM (IBM Watson).
• AI Startups: Look into emerging startups in the AI space, such as OpenAI, DeepMind, SenseTime, and UiPath.
• Industry-Specific Companies: Investigate how AI is being applied in various industries, including healthcare (e.g., Babylon Health), finance (e.g., Ant Group), and autonomous vehicles (e.g., Tesla).

5. Hands-on Practice:

• Coding: Learn programming languages commonly used in AI, such as Python and libraries like NumPy, pandas, scikit-learn, TensorFlow, and PyTorch.
• Projects: Work on AI projects to apply your knowledge. Platforms like Kaggle offer datasets and competitions to practice your skills.

6. Ethical and Societal Implications:

• Ethics in AI: Consider the ethical implications of AI, including bias in algorithms, privacy concerns, and the impact on jobs and society.
• Readings: Explore books and articles on AI ethics, such as "Weapons of Math Destruction" by Cathy O'Neil and "Artificial Unintelligence" by Meredith Broussard.

By following these steps and continuously learning and exploring the field, you'll gradually become more knowledgeable about AI and its various aspects. Remember that AI is a rapidly evolving field, so staying curious and adaptable is key to staying up to speed.

Amazon has a program called ready AI. I havent looked into it much, but could be a good place to start.