Abstract Algebra is very different than the algebra most people study in high school. This math subject focuses on abstract structures with names like groups, rings, fields and modules. These structures have applications in many areas of mathematics, and are being used more and more in the sciences, too
Seeker examines a leaked paper from Google claimed that a quantum computer demonstrated “quantum supremacy.”
But what does that mean exactly?
Quantum computers’ potential and the advantages they promise over classical computers all remain largely theoretical, and hypothetically speaking, it is predicted that quantum computers will be able to solve problems that are beyond the reach of the classical computers we use today. Passing such a threshold will be considered proof of what we call “quantum supremacy.”
Siraj Raval interviews Vinod Khosla in the latest edition of his podcast.
Vinod Khosla is an Entrepreneur, Venture Capitalist, and Philanthropist. It was an honor to have a conversation with the Silicon Valley legend that I’ve admired for many years. Vinod co-founded Sun Microsystems over 30 years ago, a company that grew to over 36,000 employees and invented so much foundational software technology like the Java programming language, NFS, and they pretty much mainstreamed the ‘idea’ of open source. After a successful exit, he’s been using his billionaire status to invest in ambitious technologists trying to improve human life. He’s got the coolest investment portfolio I’ve seen yet, and in this hour long interview we discuss everything from AI to education to startup culture. I know that my microphone volume should be higher in this one, I’ll fix that the next podcast. Enjoy!
Time markers of our discussion topics below:
2:55 The Future of Education
4:36 Vinod’s Dream of an AI Tutor
5:50 Vinod Offers Siraj a Job
6:35 Choose your Teacher with DeepFakes
8:04 Mathematical Models
9:10 Books Vinod Loves
11:00 What is Learning?
14:00 The Flaws of Liberal Arts Degrees
16:10 Indian Culture
21:11 A Day in the Life of Vinod Khosla
23:50 Valuing Brutal Honesty
24:30 Distributed File Storage
30:30 Where are we Headed?
33:32 Vinod on Nick Bostrom
38:00 Vinod’s Rockstar Recruiting Ability
43:00 The Next Industries to Disrupt
49:00 Vinod Offers Siraj Funding for an AI Tutor
51:48 Virtual Reality
52:00 Contrarian Beliefs
54:00 Vinod’s Love of Learning
55:30 USA vs China
Siraj Raval just posted this video on defending AI against adversarial attacks
Machine Learning technology isn’t perfect, it’s vulnerable to many different types of attacks! In this episode, I’ll explain 2 common types of attacks and 2 common types of defenses using various code demos from across the Web. There’s some really dope mathematics involved with adversarial attacks, and it was a lot of fun reading about the ‘cat and mouse’ game between new attack techniques, followed by new defense techniques. I encourage anyone new to the field who finds this stuff interesting to learn more about it. I definitely plan to. Let’s look into some math, code, and examples. Enjoy!
Here’s an interesting look at Python from the point of view of a hard core developer – anyone that remembers IRQs has been around a while.
From the video description:
The Python language’s memory model can be deduced from first principles: simply take modern C++ conventions and drive their safety and generality to infinity. But this limiting case generates its own compromises and opens its own categories of possible runtime errors. We will explore the position Python has staked out in the language design space of correctness versus performance, the choices Python programmers make when they need to move closer to C++, and the ways that the C++ community keeps adopting conventions that look suspiciously like Python.
Jim Simons was a mathematician and cryptographer who realized: the complex math he used to break codes could help explain patterns in the world of finance. Billions later, he’s working to support the next generation of math teachers and scholars.
In this video, TED’s Chris Anderson sits down with Simons to talk about his extraordinary life in numbers.
Every since getting into Data Science, I have been fascinated with the idea of exploring data in higher dimensions. Actually, this fascination dates back to a lecture in college on data structures, where the professor talked about visualizing five dimensional arrays. What does this space look like? Are we capable of even imagining such spaces?