#054: Perplexity Just Got Better, MIT Lessons on Poker, Strength of Weak Ties

Hi All!

We are pleased to welcome you to this week's edition of Undiscovered, a newsletter with exclusive resources and insights expanding from the material found on our main site - becketu.com.

This week we will take a look at the newest feature update from Perplexity, a roadmap for studying Large Language Models & AI in just two weeks, MIT's class on what poker can teach you about life, and more.

Let's dive in:

Perplexity Just Keeps Winning

​Perplexity.ai is the best modern search engine, and will soon become the biggest in the world. I use it for 99% of the things I search and love it because it finds what I am actually looking for: answers.

I use the free version mostly, but recently their CEO Aravind Srinivas announced that Perplexity Pro will now transition to "a reasoning powered search agent for harder queries that involve several minutes of browsing and workflows".

This means it automatically detects hard prompts and can perform tasks you ask it like "pull me all the IMO medal winners from China in the last 5 years and give it to me as a table" and "read Buffett's shareholder letters and tell me the key highlight from each year".

One of the most impressive prompts I noticed in the replies came from KD's Burner, asking "Compare the environmental impact commitments of all Fortune 50 companies across their sustainability reports, CDP disclosures, and public statements, creating a timeline of major initiatives and their measured outcomes".

This is truly a revolutionary tool that will change how research and discovery is performed forever.

A Comprehensive Roadmap to Study LLMs In Two Weeks

I have been patiently waiting for the @Hesamation article on how he he studied Large Language Models (LLMs) in two weeks. You can find the article here, where it provides a guide and 'day-to-day detailed LLM roadmap from beginner to advanced, plus some study tips'.

Going through it, this seems to be one of the more approachable guides I have found for anyone eager to learn this technology. All the materials he lists are free, and he studied in three main steps:

1. Build and LLM from Scratch - Creating a large language model from the ground up, involving data collection, model architecture design, and training.
2. LLM Hallucination - A phenomenon where large language models generate inaccurate, nonsensical, or fabricated information that is not based on their training data
3. LLM Edge: beyond attention - An advanced technique in language model development that explores alternatives or enhancements to the traditional attention mechanism used in transformer architectures.

He provides his resources and lists all necessary prerequisites that are mostly math. And what I appreciate most of all, is that he even recommends to skip around and that we shouldn't feel obligated to finish anything that he shares.

He states that before starting any of the materials, you should identify the question that you have in your mind, and look specifically for the answer. All the advice he provides comes back to how personally relevant it is to you.

How to Win at Texas Hold 'em from MIT

One of the most underrated video courses you will find is the MIT "How to Win at Texas Hold'em Poker" on YouTube. The course take a broad-based look at poker theory and how you can apply poker analytics to investment strategy and trading.

It's one of those topics that seems surface level, but has tons of use cases for life. If you'd like to get a taste of the entire series, this one hour course overview will get you interested in the subject right away.

It made me think about how I approach odds and probabilities in my own life. What can I do to increase them? How much luck is involved in certain decisions? If you're interested in the subject, we highly recommend checking out Annie Duke's book, Thinking in Bets, which goes deeper in exploring the implication of these statistics in everyday life.

Strength of Weak Ties for a Fulfilling Social Life

As we get older, maintaining social lives becomes more difficult, and sadly, many people end up seeing their friends less frequently. But with so much of our personal and professional growth depending on connections, how do we balance everything out?

A recent Twitter discourse had someone argue in favor of having "shallow friendships" and that "not every connection needs to be deep". This reminded me of an article I had read a while back, named "The Strength of Weak Ties", by Mark S. Granovetter.

It states that 'weak ties' are often more valuable than strong ties for certain purposes, like job searching, sharing dense information, or social mobility. Granovetter even had a brilliant quote on the relevance of weak ties within today's age of automation:

Westworld is Here

​Clone Robotics has just released their latest bimanual android, Torso. It has "artificial muscles, an actuated elbow, cervical spine & neck, anthropomorphic shoulders", and more. Essentially, it looks like something out of Westworld:

Clone @clonerobotics Introducing Torso, a bimanual android actuated with artificial muscles. 3:10 PM • Oct 23, 2024 177 Retweets 1195 Likes Read 135 replies

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Elon Musk recently shared updates of his latest humanoid robot, Optimus, at the recent Tesla, 'We, Robot', event which featured impressive capabilities like handling delicate objects, performing household chores, and even playing Rock, Paper, Scissors.

It's an extremely impressive step forward for the robotics community, and in some ways an unnerving one. Combining these two types of technical progress may bring Westworld closer to reality, than fiction.

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J.B.