- Think of reading as an active pursuit rather than being passive.
- Don’t get bogged down in details, try to sprint through them and look for the gist of the author.
- Read with the intention of finding out the gist and pace yourself accordingly.
- Learn to adjust your speed based on the complexity of the content.
- Skim through the content if you know what he is going to say.
- Stop vocalization during reading.
- Don’t be a word by word reader, be a phrase reader.
- Try to speed up yourself in your reading, that will help you more concentrated on the content.
- Develop your vocabulary.
- Like any other skill, more you practice, better you become. Make sure you practice with the above principles.
- Finally, Don’t consider it as an ephemeral course but as a lifelong journey of betterment.
Let’s say we have a machine that understands all the high-level abstractions and patterns in data. Let’s say it has built on its own models to predict what’s coming next. Data science ends here presenting models and predictions to Entrepreneurs or executives to make a decision. But Is it intelligent at this stage? No, it has to be able to make decisions on its own to be truly intelligent.
So, what guides decision making process?
A company makes its decision to maximize its profit. Profit is their value and that guides their decision-making process.
A man’s value of his survival deeply coded in his DNA motivates him to make proper decisions that could help him get proper food, shelter, clothes, sex etc.
Evolution has managed to deduce very rich and distinct emotions that could help us identify reinforcements in the real world. This makes it an imperative for any machine to be hard coded with these rules of value system to make use of reinforcement learning or other latest tech meme of that kind.
Whether it is chess or Go, if there is something it should definitely know before starting the game, it has to be the winning state and possibly evaluation functions for all different states possible in the Game. But that’s a small world to code valuations/reinforcements. How would you go about writing such codes for a machine to evaluate the humongous set of states, instances, objects in the real world? This makes me believe that modeling the value system or giving to a machine ability to build its own value system is at the core of AI. Too early to ignore Minsky’s rule-based systems.