Using a webcam to learn to speak or teach better in 30 minutes

Prof Andrew Ng of Stanford University, and a co-founder of Coursera, has an interesting article on how you can Learn to Speak or Teach Better in 30 Minutes with the help of a video camera or a webcam.

He points out that athletes and musicians improve by picking challenging/difficult tasks and practicing those until they improve. Why don’t we do that with teaching / public speaking?

Deliberate practice is common in music and in sports, but is rarely used in the context of speaking or teaching. In fact, knowledge workers in most disciplines rarely engage in deliberate practice. This limits how rapidly we get better at our jobs; it also means that deliberate practice might help you progress faster than your peers.Key elements of deliberate practice include:

  • Rapid iteration.
  • Immediate feedback.
  • Focus on a small part of the task that can be done in a short time.

Here’s a 30 minute deliberate practice exercise for improving your presentations:

  • Select a ~60 second portion of a presentation that you made recently, or that you plan to make.
  • Record yourself making that 60 second presentation. Use a webcam, camcorder, or your cellphone video camera to capture video and audio.
  • Watch your presentation. If you haven’t seen yourself on video much, you’ll be appalled at how you look or sound. This is a good sign; it means that your speaking ability is about to improve dramatically.
  • Decide what you’d like to adjust about your presentation. Then go back to Step 2, try again, making any changes you think will improve your speaking.
  • Repeat the cycle of recording, watching, and adjusting 8 – 10 times.

Read the full article for more details, including a FAQ at the end.

What is so ‘scientific’ about Sanskrit? #SeriousQuestion

@zeusisdead posted this query on twitter, and that finally prompted me collate all the material I could find on this topic; because this topic has bothered me for a long time.

“Sanskrit is the ideal language for computer science” is a view that is so widespread in India, that my mother, who is 70, and knows little about Sanskrit, and even less about computer science, passionately believes this, and I can’t convince her otherwise. Indians are in love with the concept that things invented in India 2000 years ago are still better than the best that the western world can throw at us today.

A broader question is the one that ZeusIsDead asked: what is so ‘scientific’ about Sanskrit?

As far as I can tell, there are two interesting aspects to Sanskrit:

  • Sanskrit is the first language to have a formal grammar defined; and there is evidence that Pāṇini’s work in this area influenced modern linguists like de Saussure and Chomsky. (And oh, Devanagari is awesome)
  • One guy in NASA in the 80s tried to push Sanskrit as an ideal language for Artificial Intelligence applications; he was neither able to convince the AI community of this, nor was he able to make much headway in this himself. This approach is largely dead, but Indian media and the ancient-Indians-were-the-best crowd did not get the memo.

In short: Pāṇini’s Grammar for Sanskrit was a phenomenal work that probably influenced modern linguists, but it is not particularly useful in Computer Science.

Influence of Sanskrit on Modern Linguistics

From the Wikipedia page on Pāṇini:

Pāṇini’s work became known in 19th-century Europe, where it influenced modern linguistics initially through Franz Bopp, who mainly looked at Pāṇini. Subsequently, a wider body of work influenced Sanskrit scholars such as Ferdinand de Saussure, Leonard Bloomfield, and Roman Jakobson. Frits Staal (1930-2012) discussed the impact of Indian ideas on language in Europe. After outlining the various aspects of the contact, Staal notes that the idea of formal rules in language – proposed by Ferdinand de Saussure in 1894 and developed by Noam Chomsky in 1957 – has origins in the European exposure to the formal rules of Pāṇinian grammar

How exactly did this influence modern linguists?

In particular, de Saussure, who lectured on Sanskrit for three decades, may have been influenced by Pāṇini and Bhartrihari; his idea of the unity of signifier-signified in the sign somewhat resembles the notion of Sphoṭa. More importantly, the very idea that formal rules can be applied to areas outside of logic or mathematics may itself have been catalyzed by Europe’s contact with the work of Sanskrit grammarians

Here, an important connection to computer science also can be seen:

Pāṇini’s grammar is the world’s first formal system, developed well before the 19th century innovations of Gottlob Frege and the subsequent development of mathematical logic. In designing his grammar, Pāṇini used the method of “auxiliary symbols”, in which new affixes are designated to mark syntactic categories and the control of grammatical derivations. This technique, rediscovered by the logician Emil Post, became a standard method in the design of computer programming languages. Sanskritists now accept that Pāṇini’s linguistic apparatus is well-described as an “applied” Post system. Considerable evidence shows ancient mastery of context-sensitive grammars, and a general ability to solve many complex problems. Frits Staal has written that “Pāṇini is the Indian Euclid.”

Sanskrit as an ideal language for AI applications

In 1985, Rick Briggs wrote a paper for the Association for the Advancement of Artificial Intelligence titled Knowledge Representation in Sanskrit and Artificial Intelligence. At that time, AI researchers were focused on trying to construct artificial languages that could be used in AI so that computers would not have to deal with the ambiguities of real languages. Briggs argued that instead of constructing artificial languages, we could simply use a highly structured language like Sanskrit.

Here is what he wrote in the abstract:

In the past twenty years, much time, effort, and money has been expended on designing an unambiguous representation of natural languages to make them accessible to computer processing. These efforts have centered around creating schemata designed to parallel logical relations with relations expressed by the syntax and semantics of natural languages, which are clearly cumbersome and ambiguous in their function as vehicles for the transmission of logical data. Understandably, there is a widespread belief that natural languages are unsuitable for the transmission of many ideas that artificial languages can render with great precision and mathematical rigor.

But this dichotomy, which has served as a premise underlying much work in the areas of linguistics and artificial intelligence, is a false one. There is at least one language, Sanskrit, which for the duration of almost 1,000 years was a living spoken language with a considerable literature of its own. Besides works of literary value, there was a long philosophical and grammatical tradition that has continued to exist with undiminished vigor until the present century. Among the accomplishments of the grammarians can be reckoned a method for paraphrasing Sanskrit in a manner that is identical not only in essence but in form with current work in Artificial Intelligence. This article demonstrates that a natural language can serve as an artificial language also, and that much work in AI has been reinventing a wheel millenia old.

The fact that someone from NASA (NASA!!!!) wrote this, and he claimed that Sanskrit is better than the efforts of modern researchers, gave the ancient-India-was-awesome crowd, and Indian media a collective orgasm. The web is full of people claiming that Sanskrit is the ideal language for computers, and if you follow the trail of references, all roads lead to this one paper by Briggs. (It is important to note that NASA itself has no official position on this; also, random rumors on the web about some “Mission Sanskrit” by NASA are hoaxes.)

Unfortunately for Briggs and for Sanskrit, this effort never did pan out. Looking at modern AI and natural language processing research, one is hard pressed to find any papers that reference Sanskrit in anything other than simple translation of Sanskrit or other Indian languages.

Vague Ramblings from the Internet

There’s this speech by Justice Markandey Katju titled “Sanskrit as a Language of Science. It rambles on for pages, but makes only two semi-relevant points:

  • [Sanskrit] enabled scientific ideas to be expressed with great precision, logic and elegance.
    • This is just proof by assertion. There is no real support provided for this statement.
    • Also, this is in direct contradiction to another article by a Sanskrit lover which claims that one of the great attributes of Sanskrit is that the same sentence can have two or more completely different meanings. (Scroll down on that page to “Sanskrit is a Context based Language”, and the next section.)
  • The alphabet of Sanskrit is arranged in a very logical and scientific manner.
    • This is certainly true. I’ve blogged about it here.
    • While this fact is pretty cool, it has no relation to the use of Sanskrit as a Language of Science

The rest of the article rambles on about ancient Indian philosophy, and the achievements of our ancestors in the fields of Science and Maths and Astronomy and Medicine and Engineering – all of this, while being interesting and impressive, does not really throw any light on the topic being discussed.

Overall, the internet is full of articles like this and this which go on for pages describing the various interesting features of Sanskrit. And people somehow list this as proof that Sanskrit is the ideal language for Science. A careful reading of the articles usually shows that there is no connection between the various cool features of Sanskrit and its suitability for Science.

Many people also point out that European languages are derived from Sanskrit. That is slightly inaccurate. Linguists have hypothesised the existence of a language called Proto Indo European which is the common ancestor of Sanskrit and most European languages. In any case, that has nothing to do with Sanskrit’s suitability for Science.

The best comment I got was this:

Vedas are in Sanskrit and Vedas are eternal. Hence, Sanskrit is the oldest language.

Sadly, that is the level of 90% of the discourse on this topic on the internet.

Follow-up Reading

Antariksh Bothale, who studies Computational Linguistics at the University of Washington, Seattle has this interesting answer to the question “Is Sanskrit over-rated as a language in India”. Lots of good nuggets of information.

Also, if you don’t know how awesome the Devanagari script is, check this out

Conclusion

In short, one guy thought Sanskrit might be a good language for AI applications, but that turned out to be a dead end. Sorry.

But, Pāṇini rocked!

Note: I am not an expert in this field, and this is just information I’ve collected from the internet. So if anyone is able to uncover any additional information, or even information that contradicts what I’ve said, please leave comments below. I’d love to be mistaken on this point.

Update: There are lots of comments below – some agreeing with me, and some disagreeing. None of the disagreeing comments have caused me to change my mind – so I’m sticking with my opinions above. Read on below if you want to see the alternative viewpoints.

Money does not buy happiness, but it buys the potential for happiness

We all have heard that money does not buy happiness. Clearly, lots of rich people are quite unhappy. And yet, it is quite clear that not having money is highly correlated with unhappiness. Brainpickings has a review of an interesting book on “How to Worry Less About Money”, which contains these two interesting graphs.

Money does not buy happiness

This one, we’re probably all familiar with. Everyone who wants to give “gyaan” says this.

However, here is the other graph, which I found more interesting:

Money does buy the potential for happiness (or more accurately, flourishing)

The graph for “potential for flourishing” does not flatten out like the graph for “happiness”.

What is “flourishing”?

Flourishing means getting on with the things that are important for you to do, exercising your capacities, actively trying to “realize” what you care about and bring it into life. But these activities involve anxiety, fear of failure and setbacks, as well as a sense of satisfaction, occasional triumphs and moments of excitement.

Basically, the higher levels of Maslow’s Hierarchy of needs.

But, the key thing to realize is that while the potential for flourishing is directly proportional to the amount of money, money is not the cause of flourishing, it is just one ingredient. Money needs to be combined with a lot of other things before it can help us flourish.

And the first step is to separate our wants from our needs.

Sometimes we need to lessen our attachment to the middle needs like status and glamor in order to concentrate on higher things. This doesn’t take more money; it takes more independence of mind.

It is important to realize that wants vs. needs is not the same as saying that you should buy only inexpensive things, or only basic/simple things. Sometimes, you need expensive things. How much you need something is often independent of how much it costs. You need to keep track of the difference between price and value.

Price is a public matter — a negotiation between supply and demand. A thing’s price is set in competition. So the price of a car is determined by how much some people want it, how much they are willing to pay, and how ready the manufacturer is to sell. It’s a public activity: lots of people are involved in the process, but your voice is almost never important in setting the price.

Value, on the other hand, is a personal, ethical and aesthetic judgment — assigned finally by individuals, and founded on their perceptiveness, wisdom and character.

Read the full review.