The book Godel, Escher, Bach: An Eternal Golden Braid, is widely praised as being an important, mind-bending, eye-opening book, but the reviews I’ve seen generally fall have fallen into two categories:

• people who have tried to read it but quit about 1/3 of the way through, but still proudly display it on their shelves as a badge of honor
• b) people who have read it and understand it, but don’t feel like trying to explain it to the uninitiated.

Since the MIT OCW course was a summer lecture series for high school students, I figured I could keep up. And by watching the lectures first, I’m hoping the book will be easier when I get around to reading it. It doesn’t seem like a book where I should worry about spoiling the ending.

There was one problem that took me a while to overcome: the lectures were in streaming .rm (Real Media) format. That means RealPlayer. I am not friends with RealPlayer – I cut my ties with Real in 2002 and vowed never to have their software on any of my computers again. If you don’t understand my revulsion, just Google “real player sucks” (477,000 hits).

So after a few days of tinkering, I came up with this solution for ripping rm streams and encoding them in a different format (I chose .mp4 so I can watch them on computer or video iPod). It takes about 20-25 mintues per hour of media but can be setup up in batches to run overnight. In my opinion, that’s a small price to avoid dealing with RealPlayer.

[NOTE: This is for Windows XP. YMMV on other platforms]

First, install these 3 programs:

• MPlayer – DON’T download the GUI version – you need the command line options to rip the stream.
• Real Alternative Lite – RealPlayer codecs without the player
• Free iPod Video Converter – there are zillions of programs that convert media files if you have the right codecs (it took me a while to figure that out) – this was the simplest, most straightforward one I came across

Second, rip the stream from the web. Open a Command window, go to the MPlayer directory, and type:

• mplayer -playlist [file URL] -dumpstream -dumpfile [destination file name]

This takes a while – streams download at 1-5x real time, so the 60 minute GEB lectures each took about 15-20 minutes each for me. Also, it doesn’t appear to be doing anything when it runs – it says something like “Cache set to 320KB”. It’s working, just walk away. You might be able to get multiple streams with one command by tweaking the command line args – let me know if you find something like it in the MPlayer documentation.

[EDIT: Apparently for MIT OCW streams, you can download them directly by changing the URL. Just change " http://mfile.akamai.com/7870/rm/mitstorage.download.akamai.com/7870" at the beginning of the streaming URL with "http://ocw.mit.edu/ans7870". This way you can download them at full speed instead of streaming speed. Thanks Sharma!]

Third, once you have the ripped files, open Free iPod Video Converter, add the .rm files you ripped, and hit “Convert”. The defaults are fine – it sets video and audio quality based on the values in the source. This took about 5 minutes per hour on the MIT OCW files I used.

That’s it! Now instead of being tied to a computer with internet connection, you can take your learning on the go! Now go back to the Hidden Video Courses in Math, Science, and Engineering page and prepare for some seriously nerdly workouts!

————–

UPDATE: My original streamdumps on a DSL line (~200K/sec) did not work right – the had correct file sizes but blacked out 50-70% of the way through.  The mp4 conversions from those files just clipped off when the files blacked out.  I tried downloading them using the direct downloads but the files got clipped and were only 30-40% of the expected file size.  I tried the direct downloads when I had access to a T1 line and they all downloaded completely and played to the end.  I’m not sure what the difference was, but check your .rm files to make sure they are the right size and play all the way to the end.

Here are our attendees:

Peter Christensen
John Quigley
Craig Luddington
Matt Bone
Brendan Baldwin
Andrew Wolven
Bruce Burdick
Chad Slaughter
Kurt Stephens
Steve Githens
Alex Hemard

ITEMS OF BUSINESS:

Name – None of the name ideas got much support, so we’re sticking with Chicago Lisp until someone comes up with something awesomer.

Project – No one had any ideas for or time to work on a project as a group so that’s also waiting for an awesomer idea.

Server – John and Craig both have servers where they can host things but not allow remote access to. John has a basic homepage at http://www.chicaglisp.org and has a mailing list setup. There might be a wiki in the future. Meeting announcements and recaps will continue to be on Peter’s Chicago Lisp page and then cross posted to the two mailing lists and the chicagolisp.org site.

Next Meeting

WHEN: Friday, May 16th at 7pm.

WHERE: CashNetUSA offices. 200 W. Jackson Blvd, 14th floor, Chicago. Map.

WHAT: Lightning talks. The following people have signed up, more welcome (email Peter if interested or add a comment at Coordinatr)

• Grant Rattke – A simple object system using macros
• Steve Githens – Scripting a Java SOA system using Kawa and Clojure
• Dry runs from the people presenting at the Intro to Lisp Workshop

Intro to Lisp Workshop: We did some pre-planning and delegation. See details here.

Presentation on Combined Object-Lambda Architectures (COLAs):

The inagural presentation of our group was about the work done by the Viewpoints Research Institure (VPRI). The most recognizable name associated with this is Alan Kay, Mr. Invent the Future himself. John Quigley made an excellent slide deck (pdf) where he reviewed the paper “Making COLAs with Pepsi and Coke” (pdf) by Ian Piumarta and put into slightly more comprensible language.

This paper is for the Fundamental New Computer Technologies project at VPRI. The aim of the project is to create a complete computing system in 20,000 lines of code. This system would be everything from the hardware to the UI and include both design and implementation. Having such a compact system would be a useful exploration and learning tool, so every part of it can be inspected and manipulated. They’re currently 18 months into a 5 year project but they already have made intriguing progress.

John’s presentation was about the architecture of the self bootstrapping system. I can’t claim that I understood it all, or even most of it. I was able to keep up mostly because I had come across VPRI’s work on Jeff Moser’s blog earlier in the week so I was familiar with the overview. What I did sort of grasp boggled my mind and definintely but VPRI on my technical radar, if for no other reason than as a technical challenge to aspire to.

If you can understand everything in Piumarta’s paper (or even in John’s summary deck), you’re a whiz. If not, don’t feel bad. I would recommend reading the NSF proposal (pdf) and the first year progress report (pdf). They’re in more accessible, less technically deep language and they have pretty pictures.

Thanks John for setting the bar high right out of the gate!

Before I started learning Lisp, I have (in reverse chronological order) worked with .Net for several years, disliked C++ in college, loved Pascal in high school, dabbled in (Assembly?) programming my TI-82 graphing calculator, and started with Hypercard. Here’s my advice based on ~1 year of part-time Lisp education.

• To learn “lispiness”, functional programming, and get a feel for the computational approach to programming, read The Little Schemer and The Seasoned Schemer. Also, use the resources for the MIT Intro course Structure and Interpretation of Computer Programs. Watch the video lectures (30 well spent hours) and if you’re ambitions, read the book (Amazon). Doing these things will help keep you from writing PHP in Lisp.
• To put it into practical perspective and learn the nuts and bolts of modern common Lisp, read Practical Common Lisp (Amazon).
• If you read PCL, you will run into Emacs and SLIME (the generally preferred [NO FLAMES, PLEASE. I KNOW VI IS AWESOME TOO] open source way to edit Lisp files). I wrote some resources to help with that:
  • Emac/SLIME Cheat Sheet
    
  • Commentary on the SLIME screencast
• I’m surprised no one has mentioned PAIP (Peter Norvig’s Paradigms of Artificial Intelligence Programming). Probably because there’s no free version online and it’s a pricey book. I got it for myself for Christmas and it’s well worth the price. It’s half AI book, half tutorial on Lisp programming and Lisp style. It’s a good read with lots of example programs written in good Lisp Style.

There are three hurdles people usually run into when learning Lisp:

1. The language looks different – this goes away with practice and familiarity. It starts looking normal fast. The parentheses are a bit tough to manage unless you use a capable editor, which leads to:
2. Emacs is different – really powerful, fun to use, but it takes investment in learning. It’s really tempting to quit when starting, but worth getting over the hump. Once you do that:
3. The way of thinking is different in Lisp – Lisp seems a little awkward to use until you get (don’t need to master them, just get the idea) the following ideas: 1) code can be manipulated as data because the syntax is so simple, 2) creating your own syntax (using macros – code that writes code) means that you can express your program in a way that closely matches the problem you’re trying to solve. Some good articles to help get these points are:
   1. The Nature of Lisp
   2. Functional Programming For The Rest of Us

Don’t worry if you don’t get these “big picture” things at first, they click at some point and everything makes a lot more sense. You can speed that up by putting a lot more Lisp in your head in the meantime.

Does anyone have any more tips on learning Lisp?

Also: read comments on this post at comp.lang.lisp, reddit, Hacker News

I got my opportunity to find out more and meet some of the kids at a the first meeting of the OLPC Chicago Interest Group, hosted at Google’s Chicago office. Most of the meeting was IMSA students presenting projects that they were working on. Here are some of the projects they mentioned:

• An EKG probe, including building a general purpose signal amplifier that could be used for other probes. This included learning electrical engineering, breadboarding, and how to solder (hand burns and all!). These students expressed interest in getting their design manufactured in a more robust and inexpensive package that could be added on to OLPC orders. This would turn the XO into a tool for health management in addition to education.
• An acoustic tape measure program that measures sound pulses to determine the distance between two laptops. This program is already included on the Give One, Get One laptops.
• A clock program that will show multiple interpretations of the time, starting with digital, analog, and the position of the sun or moon in the sky. These two students are learning PyGtk for the graphics and doing this in their spare time, in addition to writing a general CAPTCHA solver for a semester project.
• A Rosetta Stone-like language acquisition program. This is in the planning stage but the intention is for it to be as much as possible in the target language so that once the software is developed, it can be easily ported to other languages. I’ve offered to help in the design and coding of this software.
• In addition to the hardware and software projects, other students were helping plan teaching and demonstration events at area schools and organizing a bulk purchase of laptops in the Chicago area.

Did I mention that these are high school kids?!? My summary doesn’t begin to convey the confidence, enthusiasm, and intelligence that these kids radiated. Just a little background on IMSA and the OLPC project: IMSA was the first (and looks like still only) high school chapter of the University program to create communities of interest around the OLPC. The other schools (9 total) include some lofty company, like Olin College, Northwestern, and Duke. The students are in touch with some of the main contributors to the project, and their project have attracted attention and support from industry experts working who are also contributing to the OLPC ecosystem.

The students I met tonight were exceptional in many ways. They’re worth keeping an eye on, and fortunately, they’re documenting their progress on their chapter wiki. For anyone who expects great things to come out of the students at the Illinois Math and Science Academy, you don’t need to wait long.

P.S. Google puts on a nice spread!  If you ever have the chance to eat their food, take it!

It doesn’t take an economics professor or a petroleum geologist to know that energy is a big issue in all aspects of society: technology, politics, military, economics, and social issues.  And anyone who follows America’s energy policy know that it’s oriented towards resource extraction, increasing energy supply, and tax breaks for producers.  Lots of people criticize this approach, but one man has risen above the debate.

Amory Lovins is a founder of the Rocky Mountain Institute, which does more stuff than I can even begin to summarize.  The premise is that rather than viewing energy conservation as a social good or something to be done out of guilt, investment in energy efficiency can be done profitably and indeed must be done to remain competitive.  Mr. Lovins charges a $40,000 speaking fee (he’s obviously not going to be at my birthday party) but thanks to the internet, you can listen to a complete 9 part lecture series he gave at Stanford.  He covers energy efficiency in buildings, transportation, and industry, and the implications that this massive efficiency increase would have.  Most of his claims sounds too ridiculous to even be possible, but for almost all of them he points to a real client or implementation where actual results were obtained, not just theoretical projections.  It was so amazing that half the time I was either laughing out loud or my jaw was dropped in awe.

So without further ado, if you’re at all interested in the economics of energy, go to the Conversations Network and listen to all the talks in the MAP Energy Efficiency Series.  It’s an amazing 10 hour investment that will change your perspective completely forever.

(note #2: SecretGeek found this fantastic post by the greatly missed Kathy Sierra)

Anyone who spends 5 minutes reading technology news sites knows that there is FAR too much for any one person to learn (there’s almost too much for one person to be aware of). Between big companies, startups, open source, and research, there are thousands of new products, libraries, languages, technologies, etc every year. Thinking you’ll learn all of them (or even a significant fraction of them) is just madness. So here’s the process I’ve used to evaluate things.

First, I put each thing into three categories:

1. Things I’ll definitely learn soon
2. Things I might learn later
3. Things I’ll probably never get around to learning

These are the criteria I use determine which category something goes in:

1. Is this useful to me now? (for day job, startup, side projects, etc)
2. How long will it be useful? or When do I expect this to become obsolete?
3. How useful is it for the time it takes to learn? or How much bang do I get for my studying buck?

Incidentally, “fun” isn’t on the list, because there are so many options that the ones that look boring to me don’t even register. If they get far enough that I want to evaluate them, they look fun!

So here are some technologies along with the category they fall in and the grades they get on each of the criteria:

• Ruby on Rails – 2 or 3. I don’t use Ruby at work and didn’t choose it for my startup, so it’s not useful now. Despite its current popularity, I don’t think it will be that popular in 5 years and beyond. I think by that point, people will look at it the way RoR fans look at PHP right now. Good bang for the buck though, considering all the resources that have been created around it.
• Python – probably 2. Same as RoR, not used in day job or startup. I do think it will be around and popular longer than Ruby, because it has big, notable corporate users (Google and NASA, among others). I think this is more important to its future than the startups, hobbyists, and consultants that are driving RoR (Python has startups and hobbyists too). Good resources for learning as well.
• Microsoft Robotics Studio – 3. Last year I really wanted to work on Robotics, but I didn’t have any kind of hardware experience, I didn’t have a place to work on it, and I didn’t have extra money to buy parts. While general robotics principles would be useful for a long time, I don’t think MRS will be around by the time I get to work on robots more.
• LINQ – 2. I might end up using it at my day job because we do .Net, but I don’t know when that would be. Lots of people love it but who knows if it will become a big deal in .Net development in general. Also, Microsoft stuff tends to be complex because of the wide range of scenarios it’s engineered for, so I think it would be harder to learn.
• Perl – 3. I’ve head too much about how difficult it is to read and how languages like Ruby and Python are better for scripting. Perl is just something I don’t want to deal with.

Wait a minute, those are all 2 or 3! Where are the 1’s? What do I actually plan on learning?

• SICP – 1. Too many people (really smart people that I respect) have praised this book, with praise of the glowing sort that usually doesn’t come out of their mouths. And it’s almost 30 years old! The top-notch programming techniques will have already helped me program better, and the knowledge is so un-specific to any technology that it will be useful for as long as computers need programming. It’s a lot of work to get through a big textbook and 30 hours of videos, but the payoff is huge!
• Lisp – 1. Yes, I’ve drunk the Kool-Aid from Paul Graham. Sort of. I’ve read all his stuff saying why Lisp is so great, but I’ve read a lot of other people saying the same things. More importantly, I don’t find the criticisms of Lisp to be that bad. Since I’ve decided to use Lisp for my startup, learning it is of immediate importance to me (although this doesn’t apply to anyone else). I don’t expect it to become obsolete ever because 1) like SICP, the ideas are fundamental to Computer Science and will be around forever, 2) the strengths that other languages have are also strengths in Lisp (meta programming, HOFs, etc), and 3) since Lisp isn’t riding a wave of popularity, its community is sustainable in the very long run
• Artificial Intelligence – 1.  Not general intelligence (although On Intelligence is one of the most fascinating books I’ve read, ever), but the kind of smart algorithms for figuring things out about data and inputs.  Since the internet gives any program the ability to collect millions or billions of data points, anyone who can make sense of that input stream will have a competitive advantage.  On this note, I’ve started working through Paradigms of Artificial Intelligence Programming to get caught up on the last 40 years of work (and improve my Lisp chops), then I’ll move on to Artificial Intelligence: A Modern Approach.

To put this in perspective, this is basically my New Year’s Resolution regarding learning and investment in my skills.  It will provide me both immediate and long term benefit, and by studying three inter-related topics, I can probably get as much out of it as I would two unrelated topics.  So here’s my reading/working list for the year:

• The Little Schemer
• The Seasoned Schemer
• The Reasoned Schemer
• Structure and Interpretation of Computer Programs
• Practical Common Lisp
• ANSI Common Lisp
• OnLisp
• Paradigms of Artificial Intelligence Programming
• Artificial Intelligence: A Modern Approach

That, my boy, is a mountain of knowledge!  Good luck to me in getting through it and making the most of it!

“Diana E. E. Kleiner, Dunham Professor of the History of Art and Classics and the director of the project, noted that the full content of all the courses is now readily available online and may be accessed at the users’ convenience. ‘We wanted everyone to be able to see and hear each lecture as if they were sitting in the classroom … We hope this ongoing project will benefit countless people around the world.’”

The 7 courses they will start with are:

• Astronomy 160: Frontiers and Controversies in Astrophysics, with Professor Charles Bailyn
• English 310: Modern Poetry, with Professor Langdon Hammer
• Philosophy 176: Death, with Professor Shelly Kagan
• Physics 200: Fundamentals of Physics, with Professor Ramamurti Shankar
• Political Science 114: Introduction to Political Philosophy, with Professor Steven Smith
• Psychology 110: Introduction to Psychology, with Professor Paul Bloom
• Religious Studies 145: Introduction to the Old Testament (Hebrew Bible), with Professor Christine Hayes

You can debate whether these schools are doing this ot of educational philanthropy or to increase brand awareness among the international and the socially conscious, but either way, it’s a great resource for everyone!

1) Many courses do not have audio or video of lectures. The main goal is to provide course materials to anyone interested. This includes a schedule, lecture topics, lecture notes (powerpoints as pdfs), a syllabus, homework assignments, and additional reading materials. It does not include answer keys, solutions, access to faculty or TAs, or any necessary hardware or software resources.  Robotics or chemistry, for instance, might be difficult topics to learn using OCW.  Math might be a better choice.

Some courses have audio and video of lectures, but it is hit or miss. For instance, in the department of Electrical Engineering and Computer Science (which accounts for about 25% of MIT undergrads), there are 6 courses that have complete audio/video lectures out of about 175 courses offered. Don’t be fooled by all of the courses listed on the Audio/Video course pages, it includes courses with partial audio or video, pictures, or other materials included. So most of the courses offered give you little more than some PowerPoints, some homework assignments, and a schedule. Not even …

2) Textbooks. For any challenging course, you would need a textbook to learn most of the material, and it’s even more so if you don’t have an instructor. The pages for each course don’t make it clear which textbooks you need (it’s usually in the syllabus), and they give no indication of how much the textbooks might cost.  For some people this might not be a problem, and it’s still a bargain compared to MIT tuition, but textbooks, and technical niche books can cost hundreds of dollars apiece, so books for a single course might cost $200 or more.

I know, it sounds like I’m complaining about something that’s free (and that’s something I hate), so instead, I’m offering this as a field guide for other interested souls.  So here’s my $.02 regarding MIT’s OCW:

• Budget $100-$250 or more to buy the textbooks
• Unless you’re an excellent self-learner, stick to courses with lecture audio or video
• Courses with specialized hardware (laboratories, engineering tools) or software (simulations, etc) might not be a good choice
• You need discipline because there are no penalties or extrinsic rewards (degrees) for completing the courses
• You need organization because you have to be teacher and student and there are no facilities setup for you

This is if you’re too old to take advantage of MIT’s full-need financial aid.