updated docs

deepaksood619 · Oct 19, 2024 · bd8050b · bd8050b
1 parent 18ba102
commit bd8050b
Show file tree

Hide file tree

Showing 35 changed files with 679 additions and 77 deletions.
diff --git a/docs/.obsidian/graph.json b/docs/.obsidian/graph.json
@@ -19,4 +19,4 @@
   "linkDistance": 250,
   "scale": 0.1279275687532539,
   "close": true
-}
+}
diff --git a/docs/about-me/ideas/creating-a-business-startup.md b/docs/about-me/ideas/creating-a-business-startup.md
@@ -319,3 +319,4 @@ Discovery commerce is the equivalent of 'I'm feeling lucky' in Google searches.
 - [I Broke Down A Shocking Report About The Indian Luxury Market! - YouTube](https://www.youtube.com/watch?v=o5AAI5WaMFE)
 - [Co-Founder Equity Mistakes to Avoid | Startup School - YouTube](https://www.youtube.com/watch?v=DISocTmEwiI)
 - [Business Building Masterclass - Idea to Product ✈️ - YouTube](https://www.youtube.com/watch?v=juZmbYfGmiU&ab_channel=LabourLawAdvisor)
+- [How To Find A Co-Founder | Startup School - YouTube](https://www.youtube.com/watch?v=Fk9BCr5pLTU)
diff --git a/docs/about-me/ideas/education.md b/docs/about-me/ideas/education.md
@@ -96,9 +96,15 @@ Highly personalized education for each person
 ### Reporting / Observability
 
 - Send daily, weekly, monthly reports to students, parents and teachers
-   	- How many things you learned today
-   	- Summary and revision material in reviewable format
-   	- Send materials
+	- How many things you learned today
+	- Summary and revision material in reviewable format
+	- Send materials
+
+### Thoughts
+
+- Reading and writing is not required
+- And rote learning is not required
+- AI will be question and answer with voice, and all facts will be accessible all the time
 
 ### Links
 

diff --git a/docs/about-me/ideas/startup-ideas-physical.md b/docs/about-me/ideas/startup-ideas-physical.md
@@ -104,6 +104,10 @@ There are sweaters that can keep you warm, create a clothing that can keep you c
 - No large scale nuclear disaster
 - Smaller system can be stable
 
+### Reusable flex
+
+Flex that can be reprinted again and again. Or no need to print, just put up a flex, add a device which prints it. No need to remove and install new flex
+
 ## Civil Engineering
 
 ### Better and Cheap Pervious Concrete
@@ -193,11 +197,11 @@ Airline can be transporter of fuels if passenger occupancy is lower, i.e. based
 - Transport
 - Food
 
-## Autonomous Vehicles / Driverless Cars
-
-[New data shows Waymo crashes a lot less than human drivers](https://www.understandingai.org/p/new-data-shows-waymo-crashes-a-lot)
+## Autonomous Vehicles / Driverless Cars / Self-driving Car
 
-[Safety Impact](https://waymo.com/safety/impact/)
+- [New data shows Waymo crashes a lot less than human drivers](https://www.understandingai.org/p/new-data-shows-waymo-crashes-a-lot)
+- [Safety Impact](https://waymo.com/safety/impact/)
+- [Elon Musk wants to dominate robotaxis—first he needs to catch up to Waymo](https://www.understandingai.org/p/elon-musk-wants-to-dominate-robotaxisfirst)
 
 ## Others
 

diff --git a/docs/ai/llm/intro.md b/docs/ai/llm/intro.md
@@ -81,3 +81,5 @@ The architecture is a standard [transformer network](https://en.wikipedia.org/wi
 - [How might LLMs store facts | Chapter 7, Deep Learning - YouTube](https://www.youtube.com/watch?v=9-Jl0dxWQs8)
 - [Introduction to Generative AI - YouTube](https://www.youtube.com/watch?v=cZaNf2rA30k)
 - [Introduction to Large Language Models - YouTube](https://www.youtube.com/watch?v=RBzXsQHjptQ)
+- [Welcome to State of AI Report 2024](https://www.stateof.ai/2024-report-launch)
+- [How Much Trust Do You Have with LLM-Based Solutions? • Matthew Salmon • GOTO 2024 - YouTube](https://www.youtube.com/watch?v=uMhmvba7Z3I)
diff --git a/docs/ai/llm/models.md b/docs/ai/llm/models.md
@@ -138,3 +138,4 @@ Emotional prompting example - You are Dolphin, an uncensored and unbiased Al ass
 - [GitHub - nichtdax/awesome-totally-open-chatgpt: A list of totally open alternatives to ChatGPT](https://github.com/nichtdax/awesome-totally-open-chatgpt)
 - [GitHub - yaodongC/awesome-instruction-dataset: A collection of open-source dataset to train instruction-following LLMs (ChatGPT,LLaMA,Alpaca)](https://github.com/yaodongC/awesome-instruction-dataset)
 - [llama.ttf](https://fuglede.github.io/llama.ttf/)
+- [The Perfect Cheating Machine? - Cal Newport](https://calnewport.com/the-perfect-cheating-machine/)
diff --git a/docs/ai/others-resources-interview-learning-courses.md b/docs/ai/others-resources-interview-learning-courses.md
@@ -33,6 +33,7 @@
 - [Learn Machine Learning in 2024](https://www.freecodecamp.org/news/learn-machine-learning-in-2024/)
 - [5 Free AI Courses With Certifications In 2024](https://www.forbes.com/sites/rachelwells/2024/08/08/5-free-ai-courses-with-certifications-in-2024/)
 - [A Roadmap for Your Machine Learning Career - MachineLearningMastery.com](https://machinelearningmastery.com/a-roadmap-for-your-machine-learning-career/)
+- [AWS Certified AI Practitioner (AIF-C01) – Full Course to PASS the Certification Exam - YouTube](https://www.youtube.com/watch?v=WZeZZ8_W-M4)
 
 ## DS (Data Science) + DA (Data Analytics) + DE (Data Engineering)
 

diff --git a/docs/ai/readme.md b/docs/ai/readme.md
@@ -23,7 +23,7 @@
 
 ## Data & AI Landscape
 
-![Data & AI Landscape](media/Data-and-AI-Landscape-2021-v3-small.jpg)
+![Data & AI Landscape](../media/Data-and-AI-Landscape-2021-v3-small.jpg)
 
 ## AGI (Artificial General Intelligence) / Sentient
 

diff --git a/docs/book-summaries/alchemy-the-surprising-power-of-ideas-that-dont-make-sense.md b/docs/book-summaries/alchemy-the-surprising-power-of-ideas-that-dont-make-sense.md
@@ -60,38 +60,38 @@ The book covers several different ideas, but ultimately it all comes down to the
 
 ## Marcellus Summary
 
-As the title says, the talk is all about how we optimise for speed, often irrationally at that i.e, there are somethings which are counter-intuitively most productive when not done in the shortest possible time. He gives some brilliant examples to back this. He talks about the paceometer which sits alongside the speedometer in the car, except it shows “_how many minutes at that speed it will take you to go 10 miles. Assuming you’re going 10 miles at 10 miles an hour, it’ll take you an hour._  
-  
-_If you’re going 10 miles, or 20 miles, or 30 miles, something in that order of magnitude, there’s a big time-saving by going at 30 miles an hour rather than 20 miles an hour. In fact, you’ll save a whole 10 minutes just by accelerating about 10 miles an hour._  
-  
-_On the other hand, if you accelerate from 80 miles an hour to 90 for example, or 70 to 80, you basically save a minute._  
-  
-_Some of you may have noticed this if you’ve got a GPS in your car. You’re driving on the motorway at 60, you realize you’re going to be five minutes late for an appointment, so you welly it. And after driving at an insanely fast and dangerous speed for about eight minutes, you suddenly realize your arrival time has only improved by one minute._  
-  
-_This is fascinating. Because to a physicist, they’re exactly the same. But when I present the information about time and distance in a different way, your reaction is now completely different. What it effectively says is: going quite a bit faster when you’re going slowly is a really big gain. Going very fast when you’re already going fast is the action of a dickhead._  
-  
-_Basically, once you hit a comfortable 65 or 70 on the road, don’t bother. That’s enough. It’s a waste of time because the risk you encounter—the risk you incur on yourself, the risk you effectively impose on other people by going any faster—is utterly pointless in terms of time saved.”_  
-  
-Another example he gives is of how people actually enjoy their train commute home, contrary to the assumption of the train authorities:  
-  
-“_Quite a lot of people enjoy their commute time. And there’s good behavioral evidence for this because economists have noticed that people live a bit further from work than they optimally should in order to create a chronological buffer between where they work and where they live. We like that decompression time._  
-  
-_So this person announces the research to the people responsible for transport modeling at Transport for London, and they say, “You must never tell anybody that. It’s absolutely wrong for you to say that people might actually enjoy a train ride.”_  
-  
-_“Eh? But it’s true.”_  
-  
-_“Maybe it’s true, but all our models that justify transport investment assume that travel time is always a disutility. In other words, the more time you spend in transit, the worse off you are. If you come along with fancy ideas suggesting that people may sometimes prefer slower to faster, it fucks up our whole model.”_  
-  
-**_So this is what’s happened to the world: optimization trumps human preference. The people who want to win the argument are effectively prepared to ignore human truths to preserve the integrity of the artificial model._**  
-  
-_The Unaccountability Machine by Dan Davies is a fantastic book, which argues that people create these models because if you can reduce decision-making to an algorithm, or a formula, or a process, or a procedure, you avoid the risk of blame. Computer says no, effectively._  
-  
-_Instinctively, people love to codify things, and make them numerical, and turn them into optimization problems with a single right answer. Because the second you acknowledge ambiguity, you now have to exercise choice. If you can pretend there’s no ambiguity, then you haven’t made a decision, you can’t be blamed, you can’t be held responsible. And what’s the first thing you remove if you want to remove ambiguity from a model? You remove human psychology, because human psychology, particularly around time, is massively ambiguous.”_  
-  
+As the title says, the talk is all about how we optimise for speed, often irrationally at that i.e, there are somethings which are counter-intuitively most productive when not done in the shortest possible time. He gives some brilliant examples to back this. He talks about the paceometer which sits alongside the speedometer in the car, except it shows “_how many minutes at that speed it will take you to go 10 miles. Assuming you’re going 10 miles at 10 miles an hour, it’ll take you an hour._
+
+_If you’re going 10 miles, or 20 miles, or 30 miles, something in that order of magnitude, there’s a big time-saving by going at 30 miles an hour rather than 20 miles an hour. In fact, you’ll save a whole 10 minutes just by accelerating about 10 miles an hour._
+
+_On the other hand, if you accelerate from 80 miles an hour to 90 for example, or 70 to 80, you basically save a minute._
+
+_Some of you may have noticed this if you’ve got a GPS in your car. You’re driving on the motorway at 60, you realize you’re going to be five minutes late for an appointment, so you welly it. And after driving at an insanely fast and dangerous speed for about eight minutes, you suddenly realize your arrival time has only improved by one minute._
+
+_This is fascinating. Because to a physicist, they’re exactly the same. But when I present the information about time and distance in a different way, your reaction is now completely different. What it effectively says is: going quite a bit faster when you’re going slowly is a really big gain. Going very fast when you’re already going fast is the action of a dickhead._
+
+_Basically, once you hit a comfortable 65 or 70 on the road, don’t bother. That’s enough. It’s a waste of time because the risk you encounter—the risk you incur on yourself, the risk you effectively impose on other people by going any faster—is utterly pointless in terms of time saved.”_
+
+Another example he gives is of how people actually enjoy their train commute home, contrary to the assumption of the train authorities:
+
+“_Quite a lot of people enjoy their commute time. And there’s good behavioral evidence for this because economists have noticed that people live a bit further from work than they optimally should in order to create a chronological buffer between where they work and where they live. We like that decompression time._
+
+_So this person announces the research to the people responsible for transport modeling at Transport for London, and they say, “You must never tell anybody that. It’s absolutely wrong for you to say that people might actually enjoy a train ride.”_
+
+_“Eh? But it’s true.”_
+
+_“Maybe it’s true, but all our models that justify transport investment assume that travel time is always a disutility. In other words, the more time you spend in transit, the worse off you are. If you come along with fancy ideas suggesting that people may sometimes prefer slower to faster, it fucks up our whole model.”_
+
+**_So this is what’s happened to the world: optimization trumps human preference. The people who want to win the argument are effectively prepared to ignore human truths to preserve the integrity of the artificial model._**
+
+_The Unaccountability Machine by Dan Davies is a fantastic book, which argues that people create these models because if you can reduce decision-making to an algorithm, or a formula, or a process, or a procedure, you avoid the risk of blame. Computer says no, effectively._
+
+_Instinctively, people love to codify things, and make them numerical, and turn them into optimization problems with a single right answer. Because the second you acknowledge ambiguity, you now have to exercise choice. If you can pretend there’s no ambiguity, then you haven’t made a decision, you can’t be blamed, you can’t be held responsible. And what’s the first thing you remove if you want to remove ambiguity from a model? You remove human psychology, because human psychology, particularly around time, is massively ambiguous.”_
+
 The whole talk is full of blinding insights about human behaviour, contrary to popular perception.
-  
-In conclusion, he says: _“I think there are things in life that you want to telescope and compress and accelerate and streamline and make more efficient. And there are things where the value is precisely in the inefficiency, in the time spent, in the pain endured, in the effort you have to invest. And I don’t think we’re going to differentiate between those things. .._  
-  
+
+In conclusion, he says: _“I think there are things in life that you want to telescope and compress and accelerate and streamline and make more efficient. And there are things where the value is precisely in the inefficiency, in the time spent, in the pain endured, in the effort you have to invest. And I don’t think we’re going to differentiate between those things. .._
+
 _The general assumption driven by these optimization models is always that faster is better. I think there are things we need to deliberately and consciously slow down for our own sanity and for our own productivity. If we don’t ask that question about what those things are, I think we’ll get things terribly, terribly wrong.”_
 
 [Rory Sutherland – Are We Now Too Impatient to Be Intelligent? | Nudgestock 2024 - YouTube](https://www.youtube.com/watch?v=Bc9jFbxrkMk&ab_channel=Nudgestock)

diff --git a/docs/book-summaries/others.md b/docs/book-summaries/others.md
@@ -23,6 +23,7 @@
 - [THE 6 TYPES OF WORKING GENIUS by Patrick Lencioni | Core Message - YouTube](https://www.youtube.com/watch?v=N4I4hA6u6CM)
 - [LEADERSHIP STRATEGY and TACTICS by Jocko Willink | Core Message - YouTube](https://www.youtube.com/watch?v=ol6UYlOPWWo&ab_channel=ProductivityGame)
 - [A book to build your first business | 12 MONTHS TO $1 MILLION | Core Message - YouTube](https://www.youtube.com/watch?v=nfhxEF7DgU4&ab_channel=ProductivityGame)
+- [YOUR NEXT FIVE MOVES by Patrick Bet-David | Core Message - YouTube](https://www.youtube.com/watch?v=-CyEpjm-sEE)
 
 ### [Learn to lead: THE 21 IRREFUTABLE LAWS OF LEADERSHIP by John Maxwell | Core Message - YouTube](https://www.youtube.com/watch?v=QQhdiktL99w)
 

diff --git a/docs/computer-science/distributed-system/cap-theorem.md b/docs/computer-science/distributed-system/cap-theorem.md
@@ -1,6 +1,6 @@
 # CAP Theorem
 
-## Proposed by Eric Brewer (Berkeley)
+Proposed by Eric Brewer (Berkeley)
 
 ## C - Consistency
 
@@ -16,7 +16,9 @@
 
 - The system continues to operate despite an arbitrary number of messages being dropped (or delayed) by the network between nodes
 - the system continues to work inspite of network partitions
+
 Can only achieve two of these.
+
 In the presence of a network partition, you must choose betwen consistency and availability
 
 ## Why is Availability Important?
@@ -88,7 +90,7 @@ Despite your best efforts, your system will experience enough faults that it wil
 
 In [theoretical computer science](https://en.wikipedia.org/wiki/Theoretical_computer_science), thePACELC theoremis an extension to the [CAP theorem](https://en.wikipedia.org/wiki/CAP_theorem). It states that in case of network partitioning (P) in a [distributed computer system](https://en.wikipedia.org/wiki/Distributed_computing), one has to choose between availability (A) and consistency (C) (as per the CAP theorem), but else (E), even when the system is running normally in the absence of partitions, one has to choose between latency (L) and consistency (C).
 
-## Database PACELC ratings
+### Database PACELC ratings
 
 - The default versions of [DynamoDB](https://en.wikipedia.org/wiki/Amazon_DynamoDB), [Cassandra](https://en.wikipedia.org/wiki/Apache_Cassandra), [Riak](https://en.wikipedia.org/wiki/Riak) and [Cosmos DB](https://en.wikipedia.org/wiki/Cosmos_DB) are **PA/EL systems**: if a partition occurs, they give up consistency for availability, and under normal operation they give up consistency for lower latency.
 - Fully ACID systems such as [VoltDB](https://en.wikipedia.org/wiki/VoltDB)/H-Store, Megastore and**[MySQL Cluster](https://en.wikipedia.org/wiki/MySQL_Cluster) are PC/EC**: they refuse to give up consistency, and will pay the availability and latency costs to achieve it.[BigTable](https://en.wikipedia.org/wiki/Bigtable) and related systems such as [HBase](https://en.wikipedia.org/wiki/Apache_HBase) are also PC/EC.
@@ -115,5 +117,8 @@ In [theoretical computer science](https://en.wikipedia.org/wiki/Theoretical_comp
 | Hazelcast IMDG | Yes | Yes | Yes | Yes |
 | FaunaDB | Yes | Yes | Yes |
 
-[PACELC theorem - Wikipedia](https://en.wikipedia.org/wiki/PACELC_theorem)
-[CAP Twelve Years Later: How the "Rules" Have Changed](https://www.infoq.com/articles/cap-twelve-years-later-how-the-rules-have-changed)
+## Links
+
+- [PACELC theorem - Wikipedia](https://en.wikipedia.org/wiki/PACELC_theorem)
+- [CAP Twelve Years Later: How the "Rules" Have Changed](https://www.infoq.com/articles/cap-twelve-years-later-how-the-rules-have-changed)
+- [CAP, PACELC, ACID, BASE - Essential Concepts for an Architect’s Toolkit](https://blog.bytebytego.com/p/cap-pacelc-acid-base-essential-concepts)