A few hands went up.

“Keep the hands up and look around”, I said.

A few more hands went up.  I picked one of the girls (there were very few with their hands up) and asked her –  “Why do you think you are creative? Do you have an idea?”.

“Not one, but many”. And before I could recover, she reeled them off one by one. There were quite a few good ideas.

This is why I love talking to students. You never know, when you find some of these gems. It is worth visiting colleges to find just one or two of these unusual people. It is also the reason, why I hire mostly freshers (with a few exceptions). I have had great experience in working with them.

I also, never forget these students and try to stay in touch.

Here’s an excerpt:

The concert hall at the Sydney Opera House holds 2,700 people. This blog was viewed about 20,000 times in 2014. If it were a concert at Sydney Opera House, it would take about 7 sold-out performances for that many people to see it.

Click here to see the complete report.

The mobile gaming market in North America continues to grow. As of Q3 2014, there are 141.9MM NA mobile gamers, up from 111.3MM NA mobile gamersin 2013. These mobile gamers spent an average of $32.65 in the last year,generating $4.63B in NA mobile gaming revenue.

For a great analysis please see this  free report.

Recently, we’ve made a series of changes to our data infrastructure that have all proven extremely valuable:

• Investing in monitoring, testing, and automation to reduce fire-fighting
• Moving from MySQL to Redshift for a scalable data warehouse
• Moving from local log processing to Hadoop for scalable log processing
• Introducing Business Intelligence tools to allow non-experts to answer their own data questions

Got this from Hadoop Weekly, Issue #95, 9 November 2014. It has many other valuable articles on scaling.

Click on these images to see a full page view.

This para from the TIOBE is worth noting.

Thanks to the big data hype, computational statistics is gaining attention nowadays. The TIOBE index lists various of these statistical programming languages available, e.g. Julia (position #126), LabView (#63), Mathematica (#80), MATLAB (#24), S (#84), SAS (#21), SPSS (#104) and Stata (#110). Most of these languages are getting more popular every month. The clear winner of the pack is the open source programming language R. This month it jumped to position 12, while being at position 15 last month.

Other trends:

1. The top 7 languages (from a year ago) retain their spots, but all of them drop a bit in popularity.
2. Dart, a programming language from Google,  jumps into Top 20 from a previous rank of #81. Dart is language for  building web and cloud apps.
3. Swift comes from nowhere and enters #18 spot. Swift is a new programming language from Apple for iOS and OS X.
4. Perl and Visual Basic.NET stay in Top 10. It will be interesting to watch their moves.
5. F# keeps moving up (from #23 to #16)
6. Watch the Top 50 languages (#21-#50). Some of them are leading indicators to future of computing.
7. To see potential new entrants into Top 20, you may want to watch the other languages in Top 50 in the  TIOBE site.
8. I expected Scala to be in this list but for some reason, I don’t see it. I think it will soon move up into the Top 20 list.
9. Three SQL dialects are still in Top 20. I am not surprised by that since SQL is still one of the most popular languages for database programming.
10. I keep hearing a lot about Julia. I will be watching it with interest.

The images in this page are from InfoMinder. InfoMinder is a tool for tracking web pages. I use it to track a few interesting pages on the web. When InfoMinder detects change in a page, it highlights it  and creates a new changed page. It is one of the tools we built over a decade ago and is still chugging along, helping me and others watch the web.

A few notes from one of the most inspiring startup stories.

• Growing up with technology at a young age changes your mindset and how you interact with the world.
• Doing end to end in technology is really complicated.
• The best teams are the ones with a culture that gets going when things go wrong.
• For startups, PR is the best means of early marketing.
• Growth metrics are very different for physical items. For  apps it may be  downloads in millions. For physical items, a few sales from each store is good.
• The early stages of a startup are fun but may be very glamorous – lots of market research, cold calling, talking to people to hire, white boarding, sketching, prototyping, brainstorming, trying out different things and building.
• To be a good startup, you need to have an intentional processes, deep technological integration and great design.
• You need to build things that are really easy to use.

I enjoy listening to ETL (Entrepreneur Thought Leaders) podcasts. They normally get good speakers and the audience ask great questions. I hope you enjoy this podcast as much as I did.

A couple of my favorite snippets from the podcast:

Knowledge and understanding have a funny way of expanding.

Creating to code is a gateway to thinking computationally

Thinking computationally? What does that mean? Why is that important?

Computational Thinking (CT) is a problem solving method that uses computer science techniques. The term computational thinking was first used by Seymour Papert in 1996.

Jeannette Wing, Head of the Department of Computer Science at Carnegie Mellon University (CMU) has been one of the most eloquent Computer Scientists to argue the case. Computational Thinking isthe skill of the 21st century

So what is Computational Thinking? Well it is a collection of diverse skills to do with problem solving that result from studying the nature of computation. It includes some obviously important skills that most subjects help develop, like creativity, ability to explain and team work. It also consists of some very specific problem solving skills such as the ability to think logically, algorithmically and recursively. It is also about understanding people. Computer Science is unique in the way it brings all these diverse skills together.

So back to the original question – how much should you know about computing? It depends.

• Everyone should have a  high level understanding of what computers are capable of, how they work and where they exist (in desktops, laptops, mobile devices, tablets, cloud and even in cars, smart devices)
• Engineers/Scientists should know how to use them as tools to improve their work. They may need to learn simple scripting language like Python
• Students should know “computational thinking” since it will help them build problem solving skills.
• Not every one needs to be a programmer but learning a simple language will give them a chance to appreciate thinking like a programmer. The essential skill one need to acquire is to take a complex problem, break it into simpler/manageable problems and apply existing knowledge to solve the simple problems.
• To find patterns (some level of abstract thinking) to apply solutions from one domain to an entirely different domain.

What do you think? Do you think Computational Thinking is an essential basic skill?

Multipliers are different. Some of the common attributes you can find in multipliers are that:

• They are supportive
• They trust people
• They listen a lot
• They make you feel important
• They seek help
• They give appreciation
• They get out of the way
• They are demanding and have high expectations of you
• They challenge you and let you suffer a bit
• They operate from a place of inquiry
• They push you out of your comfort zone into  spaces unknown
• They ask questions that focus the energy and intelligence of the group

Diminishers hire great talent, but do not allow them to operate at their full potential. Here is how to identify them.

• They micro manage people
• They adopt a subtle attitude of  “my way or high way”
• They typically operate in “tell” mode
• They constantly emphasize their superiority
• They remind you that you don’t know enough
• They constantly interrupt
• They operate from a place of knowledge (their knowledge)
• They create stress in the teams that work for them

Listening to this talk, made me think, how we have a mixture of the qualities of both multipliers and diminishers. I have noticed that good multipliers are comfortable in their own skin and make great mentors and coaches.

After listening to Liz, I am putting her books on my reading list. I highly recommend listening to this podcast. 

Can universities teach students about startups? Yes and no. They can teach students about startups, but as I explained before, this is not what you need to know. What you need to learn about are the needs of your own users, and you can’t do that until you actually start the company. So starting a startup is intrinsically something you can only really learn by doing it. And it’s impossible to do that in college.  Startups take over your life. You can’t start a startup for real as a student, because if you start a startup for real you’re not a student anymore. You may be nominally a student for a bit, but you won’t even be that for long.

In yet another amazing essay, Paul Graham talks about the counter intuitive nature of startups. A highly recommended reading.

And the first key, critical moment, of Pre-Success, that no one will appreciate but you — is when you get 10 Unaffiliated, Paying Customers.  I don’t mean friends of your investors, or your old co-workers or boss.  I don’t even mean folks you hustled at some conference or meeting (well done, there, though.  But that’s prospecting, which is something else.).

No, I mean 10 customers that Just Came in Through the Ether.  A raw, unaffiliated, lead, that somehow found you on their own, kicked the tires, and now — is actually paying you.  Every month.

Because here’s the thing.  10 customers may not seem like much.  We called these guys “Beer Money” in the early days at EchoSign.  10 customers was $200 a month. Didn’t really pay the bills on 4 engineers and 3 other guys.

It took us more than a few months to get them. They were not just 10 but 300. We got them because we gave the product away for unlimited use and watched them use it. Once we were convinced that they were using it regularly and heavily, we started asking them to pay. And they did.

Getting unaffiliated customers (without prospecting) is not easy. But it is one of the best validations that your product can do something useful for someone.

Read this great post for more information on the importance of these 10.

The goal is to help the 250 million school-age children in the world who can’t read or write. Contestants will build apps that kids can use on their own — because many of these kids don’t have access to the “unscalable” resources of teachers and schools.

The prize all ties into a philosophy known as self-organized learning — where kids learn autonomously by figuring out technology for themselves — that’s popular with the TED crowd. And of course, the other big idea is that contests are a peculiarly effective way of motivating people.

Keller said he anticipated that the winning app would use an artificial intelligence approach to figure out what an individual kid knows and does not know.

A few thoughts:

1. The kids (targeted by this effort) cannot read or write. So you need to starting points may be different (speech, images).
2. Kids should use these apps on their own. This means the apps need to be engaging and evoke curiosity constantly (the game community can contribute a lot).
3. Since there will be no teachers involved, this would encourage peer based learning (and students playing the role as teachers)
4. You cannot make any assumptions about what they know or what language they speak.
5. The app is supposed to use AI approach. So you need to use AI to mimic a teacher or a self learner or a combination of both.
6. To come up with a reasonable solution, you need to understand how kids learn.  That, in itself, is a fascinating area of exploration.
7. Kids don’t have access to “unscalable” resources (like teachers and schools). That points to tablets with long battery life, solar chargeable or something that requires hand cranked power. This is not actually the app quality but the need of the underlying platform. This also means, schools cannot the platform for distribution of apps or devices. Hopefully that will be a different challenge.

Rural India and countries in Asia and Africa will certainly benefit from the outcomes. No matter which app wins, we will get a lot of great ideas for self-organized learning. That is bound to change education as we know it.

• The traditional (row oriented) database technology is becoming obsolete
• The database market is at a tipping point
• DB market can be viewed as three segments – data warehouse market, OLTP market (both new and old) and a potpourri of other stuff
• The potpourri consists of various types of NOSQL, Graph databases, Column Stores, In Memory databases
• Databases currently spend 90% on overheads and only 10% on   value producing work (big Gasp!)
• The overhead consists of – feeding buffer pool, mapping buffer pools to disk, lock management, logging, multi-threading
• There are ways to reduce these overheads using shared data structures, removing the record level locking, implementing multi-version concurrency, logging commands instead of data changes, using replication, getting rid of buffer pools, getting rid of expensive multi-threading, optimistic concurrency control etc.
• He talks about Distributed concurrency vs eventual consistency
• Most database books cover traditional database architectures. He advocates teaching  – column stores, in memory databases, array databases and graph database architectures.
• He talks about embarrassingly parallel databases
• VoltDB evoloved from HStore prototype from MIT
• Applications are multiplayer games, high speed OLTP
• Some  examples of NewSQL databases – Hana from SAP, Hekaton from Microsoft, SQLFire by VMWare, NeuroDB, NetSQL
• Most of the db systems written in the past year are open source

He takes a lot of digs at the closed source sales models.  Deep dive into databases is an intoxicating topic and this was a great interview. Thanks to IEEE Software Engineering Radio folks for their indepth, high quality interview questions.

Here is a link to Dr Michael Stonebraker on Current Developments in Databases

Meta

• I was lucky to spend a lot of time in late 80s and early 90s reading Michael Stonebraker’s papers.
• I met him twice (once when I attended an RDB seminar at Palo Alto and once when we walked into Illustra offices (we built the ODBC driver for Illustra in my previous startup)
• I have been following him when I was working on complex event processing and looking at Telegraph (built on top of Postgres) and Streambase
• I lost touch even though I kept hearing about Vertica and other developments
• Michael Stonebraker inspires me and lots of other data geeks like me

Prepare for your meetings preferably with a list of questions

First, find successful, independent advisors who have achieved what you want to. Whether they have bootstrapped a small business to profitability, scaled a business to serve customers around the world or have been acquired by a conglomerate, they are worth talking to. Instead of asking to ‘pick their brain’, prepare for your meetings like you would prepare for a presentation to potential investors. You will be surprised at the results – advisors are very helpful when you value their time, ask targeted questions and follow up with them.

You may not like what you hear (as advise). Don’t be defensive, listen to the point of view and try to understand the context in which the advice is given.

The ‘right’ advice will make you feel uncomfortable, move you to action and potentially, change the course of your life.

A great advisor helps you focus on understanding what matters most, even when in retrospect, it seems like very simple advice.

Think about the advice before you start acting on it. Understand that:

Not every piece of advice is a pearl of wisdom.

Predicting the future is hard and risky. Predicting the future in the computer industry is even harder and riskier due to dramatic changes in technology and limitless challenges to innovation. Only a small fraction of innovations truly disrupt the state of the art. Some are not practical or cost-effective, some are ahead of their time, and some simply do not have a market. There are numerous examples of superior technologies that were never adopted because others arrived on time or fared better n the market. Therefore this document is only an attempt to better understand where technologies are going. The book Innovators Dilemma and its sequels best describe the process of innovation and disruption.

Nine technical leaders of the IEEE Computer Society joined forces to write a technical report, entitled IEEE CS 2022, symbolically surveying 23 potential technologies that could change the landscape of computer science and industry by the year 2022. In particular, this report focuses on:

1. Security cross-cutting issues
2. The open intellectual property movement
3. Sustainability
4. Massively online open courses
5. Quantum computing
6. Devices and nanotechnology
7. 3D integrated circuits
8. Universal memory
9. Multicore
10. Photonics
11. Networking and inter-connectivity
12. Software-defined networks
13. High-performance computing (HPC)
14. Cloud computing
15. The Internet of Things
16. Natural user interfaces
17. 3D printing
18. Big data and analytics
19. Machine learning and intelligent systems
20. Computer Vision and Pattern Recognition
21. Life sciences
22. Computational biology and bioinformatics
23. Medical Robotics

You can find the comprehensive report here.

CB Insights recently parsed 101 post-mortem essays by startup founders to pinpoint the reasons they believe their company failed. On Thursday the company crunched the numbers to reveal that the number-one reason for failure, cited by 42% of polled startups, is the lack of a market need for their product.

The post  Why startups fail is worth a read.

Many ideas in this thread apply to finding other software jobs when you don’t have prior job experience to show. Some of the techniques (from this thread and others):

1. Create useful apps (in your favorite language) and give them away.
2. Work on open source projects. I know a few people who were hired by open source project teams.
3. Create a YouTube video explaining how you developed this software and how it works.
4. Tweet that you are interested in working on your favorite language – Python/Ruby/PHP/Java
5. Try to find companies that use your favorite language and try to get internships while still in college.
6. Find out how your favorite language is used along with other relevant skills. For example, if you want a web application development job, besides your favorite language what other skills are needed. For Python web app development it may be Djano/Flask or some other web framework, for Ruby, it is Ruby on Rails, for PHP it may be Code Igniter. In addition to the framework, it helps if you know some HTML, Javascript, CSS
7. Try to get some part time assignments in your favorite language. You can do this even when you are in college.
8. Participate in discussion forums and answer questions with code samples. These questions will give you problems to work on. Solving these problems help others and let you learn.
9. Create a web presence (about.me is a great resource) and mention what you do. Keep them updated.
10. Blog about your efforts. Include code snippets, pointers to your github pages. Tweet these blog posts (or make them your email signature)

Keep following this thread  nd other similar threads on Quora for more ideas.

The Little Book of Talent gives us some ideas.

For most of us , the problem revolves around one word : “how.” How do we recognize talents in ourselves and in those near us? How do we nurture talent in its early stages? How do we gain the most progress in the least time? How do we choose between different strategies, teachers, and methods?

In the book Dan talks about Talent Hotbeds and the methods they use.  First:

You are born with the machinery to transform beginners’ clumsiness into fast, fluent action. That machinery is not controlled by genes, it’s controlled by you.Even the most creative skills— especially the most creative skills— require long periods of clumsiness.

This book provides a few tips.  It is worth running a few experiments and observing the results.