Serendipity35

Andrew Ng's Machine Learning course on Coursera has been revamped and updated and it is getting good student ratings.

There are fewer online courses that I consider to be true MOOCs now. Massive is small. Open is more closed. But the "OC" portion remains for many. The three courses that make up the Machine Learning Specialization offered by DeepLearning.AI and Stanford on the Coursera platform still fit the MOOC definition more closely.

You can earn a certificate at the end, and enjoy the full experiences including quizzes and assignments if you enroll and pay a monthly subscription but the courses are free (Open) to audit and view the course materials. The Massive in this course is massive with over 20,000 students enrolled.

Andrew Ng is the co-founder of Coursera and was the founding lead of Google’s Brain Project, and served as Chief Scientist at Baidu. He then did two artificial intelligence startups - Deeplearning.ai (a training company founded in 2017) and Landing.ai (for transforming enterprises with AI). He remains an adjunct professor at Stanford University. His course on Machine Learning was one of the very first courses from Coursera when it first launched in 2012. I audited the course that year though I knew the content was way above my abilitiees but I was curious as to the structure of the course from a design perspective.

At that time, Machine Learning was a new concept and was close to applied statistics. Ng goes way back because his Stanford lectures were on YouTube in 2008 and got 200,000 views. Then, he converted them to an online format in Fall 2011 and they were offered for free. He had 104,000 students and 13,000 of them gained certificates.

On the tech side, this updated version:
uses Python rather than Octave
expanded list of topics including modern deep learning algorithms, decision trees, and tools such as TensorFlow
new ungraded code notebooks with sample code and interactive graphs to help you visualize what an algorithm is doing
programming exercises
practical advice section on applying machine learning based on best practices from the last decade

 

On April 14, 2022, business magnate Elon Musk proposed to purchase social media company Twitter, Inc. for $43 billion. He had previously acquired 9.1 percent of the company's stock for $2.64 billion and thereby became its largest shareholder. Twitter invited Musk to join its board of directors and he accepted and then changed his mind. Musk is certainly one of the most unorthodox business leaders of our time. The general opinion seems to be that he would likely make changes to the platform that go well beyond revamping its content policies.

Twitter was generally not in favor of Musk taking control and so used what is known as a "poison pill" strategy. They would allow shareholders to purchase additional stock in the event a buyout should occur. But on April 25, Twitter's board of directors unanimously accepted Musk's buyout offer of $44 billion. There was also talk that Musk would make the company private.

Besides the business aspects of all this, many users were apprehensive about a Musk takeover and really about anyone taking over. The fear was not about stock prices or advertising. It is about how the platform would change.

Elon Musk published his first tweet on his personal Twitter account in June 2010. He had 80 million followers at the time of the purchase. Musk's most vocal comment about the purchase was that he wanted to protect "freedom of speech." Of course, that is something protected by the government and doesn't really apply to most private companies.

Elizabeth Lopatto of The Verge made some predictions about what a Musk takeover might mean. She thought that a mass employee exodus might occur. She also saw the reinstatement of some accounts, such as Donald Trump's account.

The New York Times wrote that Musk's acquisition was "about controlling a megaphone" rather than free speech. Kate Klonick, a law professor at St. John's University, went as far as to say that allowing "all free speech" would open the door to the spread of pornography and hate speech on Twitter.

A number of commenters have said that Musk's purchase just adds fuel to the controversy about the power that wealthy people have in influencing the democratic process.

Musk has said that he thought that Twitter should make the algorithm that determines what users see open-source and more transparent.

READ MORE
https://www.wsj.com/articles/twitter-under-elon-musk-what-an-open-source-and-free-speech-oriented-platform-could-look-like-11651091515

The term "walled garden" once only meant a literal garden that was enclosed by walls.  Though I tagged this post as "tech" and "Open Everything," this topic is not about things being open at all - which of course is a topic of those who discuss openness.

There are literal walled gardens in the world. These gardens are surrounded by walls to keep out animals, unwanted human visitors and in some places, the walls shelter the garden from wind and frost. They can also be decorative and there may be smaller walls within the walled perimeter. These days if you hear the term there is a good chance that it is a figurative walled garden which is a closed platform or closed technology ecosystem. Since we borrowed the term "ecosystem" from nature and have since created manmade ecosystems (or damaged natural ones), it makes sense that we turn botanical garden ecosystems into technology ecosystems.

A tech walled garden is a closed platform or closed technology ecosystem which is a software system wherein the carrier or service provider has control over applications, content, and/or media.With that control, they can restrict convenient access to non-approved applicants or content.

We contrast this with an open platform, wherein consumers generally have unrestricted access to applications and content.

Whether on the broader Internet or a smaller network, a walled garden is a restricted section that only approved users can access. I first encountered this in the earliest days of the Internet with the walled garden of the school nework where I taught. Their server granted access only to students and staff and even that larger walled garden had smaller walled sections withing delegated only to faculty or administration.

It all sounds like something safe - maybe even comfortingly safe. A walled garden can also refer to a closed or exclusive set of information services where a user is unable to leave the closed environment without the owner giving limited points of entry. One example of this comes from Apple’s hardware, software and services work. They work well together as long as you use Apple's devices and services. (see this Wall Street Journal video report)

The Apple walled garden is so closed that it has been targeted for antitrust scrutiny. The recent Epic vs. Apple case is an example of that. The Fortnite video game developer made the case that Apple's walled garden is a monopoly that forces developers to use Apple's in-app purchase system, which gives Apple a 30% cut of all sales.

Walled gardens - literal and figuartive, botanical and technological - have their purposes and will continue to exist, but it is very nice to see gardens and tech ecosystems that are open too.

The organization schoolhouse.house hits a lot of things that I am interested in wth education. It is a free, peer-to-peer tutoring platform on which anyone, anywhere can receive live help. It is no surprise that Sal Khan of Khan Academy is working with them (CEO) since the share similar goals.

The thing that sets schoolhouse.world apart from other free services (such as MOOCs) is that you can earn shareable certifications in the topics you learn about. You also have the option to become a tutor in the topics that you have mastered.

Their current focus is on high school math and SAT prep, with plans to expand to other areas soon. All the small-group tutoring sessions happen over Zoom. During the pandemic and learning from home by choice or necessity, this is surely something many of us felt there was a need for in the K-12 world.

But there is also a higher education connection. The University of Chicago is one institution supporting schoolhouse.world in their effort to connect high-quality peer tutors with students around the world. Those tutors also have the opportunity to showcase their contributions on their college applications.

Jim Nondorf, Dean of Admissions at the University, and Sal Khan joined a group of schoolhouse.world tutors on Zoom to discuss the new program and what it means for the future.

Says Khan, "It was wonderful to hear the stories of these amazing young people admitted to one of the top universities in the world based on their ability to certify their knowledge and tutor others! I suspect more colleges like University of Chicago will value this type of evidence soon."

I hope Sal's suspicion will be confirmed.