* Many of the leading BioInformatics researchers in Boston and in Israel are originally Israelis 🙂
* Bio-Informatics requires new methodologies which are different than traditional biologiets are used to. This is a good scenario for Israelis who tend to be more adaptive in an unknown territory.
* Bio-Informatics is across domains. Math, Computer Science , Chemistry ,Physics , Statistics and engineering all play a critical role. While Israelis ,some times, are not as good in structured and well known engineering domains, they work well in teams and move between domains relatively easily.On a side note – Intel, Teva, IAI and Iskar demonstrate that manufacturing can work well in Israel.
* Bio-Informatics industry would probably be more cash efficient than traditional drugs design that requires FAB likes investments of Billions of Dollars.Moving from hardware into software and from manual experiments into virtual ones can reduce costs in an order of magnitude.
* M.Sc and PHD in Biology make very little money in Israel, due to the lack of opportunities. This can get as bad as minimum wage or a high-school teacher salary.On the flip side, it means there is a large pool of extremely talented candidates.
On the next parts – what is the promise of bioinformatics? Why is Israel not there yet, and how can it get there?
Israel has an enormous potential to play a major role in the new “Big Data” and Data Science ecosystem. Data Scientist is becoming a very “sexy” profession and since “Big Data” is expected to create a huge market, the opportunity should not be missed.
Israel’s has the following advantages:
A World class academic activity in machine learning , pattern recognition & text analytics. Some example are: Prof. Yishay Mansour , Prof. Naftali Tishby ,Prof. Yair Weiss and Prof. Amnon Shashua.
Large supply of candidates – there are quite a lot of great PhD or MSC graduates in Applied math, Statistics Physics , Biology, Bioinformatics and Chemistry . Since the universities have a very limited supply for tenures, the pool is quite deep. In Europe and US there is shortage of these skills.
These are not new topics For the Israeli Intelligence community and broader Israeli security sector. There are experienced experts who built proven,production systems. The experts are not only on the math side, but also on the business analysis side.
Typical Israeli data scientist has more IT\programming skills. While these are not mandatory features for success,they tend to accelerate the discovery process and add a lot value.
There are quite a few business applied Data Mining companies in the commercial sector and in start-ups arena (e.g. Pursway).
The excellent communication skills, domain understanding and language diversity , especially compared to classical never-worked-outside-of-university PhD. Many Israeli PhD are “forced” to work in teams and in the industry to make a living, or during their army service, so even the more introvert types make a solid team player 🙂
50% reduced cost compared to US – for various historical reasons the PHD\Masters title is not as economical as in the states. An amazing Java developer with no degree at all would probably earn twice as much as an amazing chemistry POST-Doc from Harvard. While this is a shame, it presents an opportunity for Data Science service out of Israel. Moreover, there are less hedge-funds to waste people talent 🙂
There are various directions to capitalize the potential:
Providing Data Scientists as a service, out of Israel. While remoteness presents some challenges, we have seen early success. It seems that the pros outweigh the cons.
Build infrastructure products for Big data – around Hadoop, Hive, Mahoot etc. Adding the enterprise features and improving performance These are similar in nature to traditional Israeli expertise in networking, storage and security. In my opinion, there is higher chance for na Israeli start-up to succeed here, bigger than in a new social application.
Develop innovative services that use Machine Learning internally to gain a competitive edge (In advertisement, Retail or Medicine)
In a world where “old-fashioned” software engineers are more and more common, each one of these direction can help maintain Israel’s Hi-Tech uniqueness.
P.S
I just saw that other people also think Israel has the chance to be a world leader in big data . Although the quote is from EMC, I knew nothing about it 🙂
Product Manager – Backgammon, Company unspecified, Gibraltar
The world’s leading online gaming company, requires an innovative Product Manager to own, develop and manage the company’s suite of Backgammon products. This dynamic role will see you developing and owning the product roadmap for Backgammon, generating new product ideas and driving successful product rollouts.
I believe it is a shame when some of the top intellectual minds of our times devote their 12 hours work days to algorithmic trading, on-line gambling, “casual” gaming, search engine optimization , on-line porn, search diversion through “Freeware\Malware” and so on.
Of course, these ultra smart developers are not using these services (at least not all of them:) ). They are the brains that run the software and algorithms to operate the questionable services.
I’m not passing judgment on the need for the services , although I’m quite sure Algo Trading has no economical benefit to the world :). I do think that being a “Product manager for backgammon” is less important and satisfactory than “Product manager for diabetes cure” .
I see too many brilliant friends who want to make easy money by finding a loop-hole in the global financial system. While I can’t commit that I would never work in such company, I prefer not to do it, as long as I can.
Interestingly enough, these services are somewhat related. For example, a lot of the real good money in SEO is from references to gambling and porn sites . Forex trading is not really different from a legal(?) form of gambling and “casual gaming” ,IMO, is quite the same.
It just seems that developing the Google search engine is more productive than algorithms that create fake content that only seems real to Google, but no real person would ever want to read.
Our civilization moves forward from innovation like Bioinformatics and Wikipedia, even Facebook and Twitter. But it seems that we can leave SEO to the average developers….
Kaggle is an innovative solution for statistical/analytics outsourcing. We are the leading platform for predictive modeling competitions. Companies, governments and researchers present datasets and problems – the world’s best data scientists then compete to produce the best solutions. At the end of a competition, the competition host pays prize money in exchange for the intellectual property behind the winning model.
If we want to go for higher numbers: google paid $12B for Motorola patents. Most of these patents have probably never been used and are not-so-important-or-smart.
While I believe most software patents are idiotic, this is how the game is played these days. And in some sense it is encouraging that Intellectual property, in the form of Algorithms starts showing its economical value.
If you can claim to be a data scientist and have the chops to back that up, you can pretty much write your own ticket even in this tough job market. A quick search of the popular job posting sites –Indeed.com,SimplyHired.com, or Dice.com – shows a huge demand for data scientists or anyone who can demonstrate other “big data”skills.
And , most importantly, the funniest show in TV right now (except for Fox News) is Big Bang Theory, focusing on Algorithms to making Friends.
In the 20th century the majority of innovation started as evil nations wanted to destroy other nations.
As a result, the evil (and peaceful) nations devoted large chunks of their tax money to the defense budget.
The flow of research money was the following:
Public (taxes) -> Government -> Defense Agencies -> Universities -> Private Companies (implementation)
Research Budget Flow
Many of the most important contributions to technology and science were created or commercialized through this path: the internet, GPS, atomic energy , satellites and plenty more.
Space and Aviation -> Military -> Large Enterprises -> Civilian Government -> Small Enterprises -> Consumers
The early experiments or products were extremely expensive and sold in small quantities and required public financing.
In the 21st century the flow of innovation and new technology has reversed.
innovation Flow in a Consumer World
The recent launch of an iPhone into space with GPS tracking by civilians, is one amazing example.
The following stock chart provides more evidence. It plots the iSharesDow Jones U.S. Aerospace & Defense Index Fundcompared to some major consumer oriented companies like Google, Sony, Amazon.
Chart of Defense Index Vs Consumer Companies 2006-2011
The new innovations are derived from consumer demand and consumer services or products : cellular phones, smart Phones, social networks,cloud computing, personal computers and online advertisement.
I believe this is the reason the Intel, Apple and Google are now the largest companies in the world, displacing companies like SUN, Nortel, Lucent, HP , IBM and similar companies more focused on enterprise and governmental markets. While IBM, Microsoft and Intel are still leading the patent table, one can claim it implies more on the inflation of patents , rather than true innovation.
Top 10 Companies Patents ROI from MSN
The reversal of innovation can be explained by multiple theories:
Moral – the global society has become more civilian and democratic. Individuals have more civil rights, more control of the public spend and therefore there are fewer wars, less dictators and less weapons. Unfortunately , I’m not sure all of the facts support this theory. I have found some evidence. For example, from 1988 to 2009 the global military spending share of GDP has dropped by 34% from 3.5% to 2.4% , global average. The number of conflicts decreased by 40% from 1992 to 2009.
Share of Military Expenditure as Percentage of Gross Domestic Product 1988 2099
Armed Conflicts by Region 1946-2009
Economics – In the end of the day we are all consumers and individuals. Economics are driven by numbers and since there are about 1 Billion consumers with a high standard of living, it is the largest market for almost any product. Selling a $300 product to every consumer translates to $300 billion market, this is equal to the global IT market spend. Selling $30 of advertisement to one Billion people …. you can do the math on your own. Compare that with the cost of design and manufacturing of a new stealth plane.
The R&D alone would cost Billions of dollars, and each airplane would cost $336M million dollars , if it the project is not aborted during the 20 years of development. Programming an amazing computer vision system for smart missiles would only be relevant to 20-40 customers. Delivering an amazing face recognition for facebook generates access to 750 Million customers. The OCR domain is one example I already bogged about.
Sociological – Open source software has allowed sharing of innovation and technology with zero cost of patents, licensing and removing many anti-competitive habits , either explicit or hidden that were common in past years. It also allows sharing of development costs across organizations. Younger generations are used to great user experience, and would not “go back” when entering Enterprise office. Cloud computing is also helping to build start-ups in 50 dollars.
The fact that Google and Amazon are hosting funding challenged public database of bioinformatics, that used to be funded by the government is rather provocative.
To summarize, while there are still huge budgets in defense and commercial enterprises, there is strong trend driving innovation from the individual. Do you believe the trend is real?
It seems that software products are only created in very few countries around the world : United States, Israel , United Kingdom , Canada and Texas :).
However, there seem to be very few software products companies In non English speaking countries (I count both Canada and Israel as English speaking countries for in this blog context).
Germany has SAP and Software AG. France used to have Business Objects, but now it belongs to SAP so it is left with Dassau. Japan has Trend Micro, but that’s about it. China is not in a much much better situation with total of 29 companies listed in Wikipedia.
I have assembled a pseudo-arbitrary list of interesting Israeli start-ups. These are mostly companies whose product I got to try and whose team I met. Some bias to companies with real intellectual property in algorithms or products. They may have much in common,and there are many more around, but worth watching.
Two days שעם,during the Purim holiday, I tried to withdraw 1000 NIS from Bank Leumi in Dizengof. The ATM , aka “Kaspomat” returned an error an apologized.
As I was walking across the street to another ATM I was surprised to receive an SMS from Bank Poalim(my bank) confirming that 1000NIS have been withdrawn from my account.
The SMS was a result of a new cool service that Poalim provides sending SMS notifications on major account actions.
However, I was always under the impression that ATM transactions are Atomic in the database sense of transactions. A further check in my on-line account has shown that indeed 1000NIS withdrawal is listed there as well.
In the end of the day, the transaction was automatically canceled after 48 hours. My guess is that Bank Poalim and Bank Leumi “settle” their differences after 24 hours so the overall Action consistent , but it is not Atomic.
I know a spell
That would make you well
Write about love, it could be in any tense, but it must make sense
Belle & Sebastian – Write About Love
Some companies believe that product management can be reduced to scientific experiments.Instead of using intuition and customers interaction one should run experiments and measure results.
While I have great faith in measurable product management , I think that the dream of product management without the human factor is wrong and dangerous.
Everyone seriously involved in pattern recognition and data mining knows that one can’t just throw tons of raw data into an algorithm and expect to gain (artificial) intelligence.
In most cases it is hard to build a large data set to train the algorithm. Once such data set is built , the raw size is too big for any algorithm to train on. As a result ,the raw data needs to be reduced through feature extraction. For example, if we want to build a face recognition algorithm in a video stream we can help the algorithm by removing the soundtrack. While in theory the soundtrack can add information to the algorithm, we guess it is not very helpful.
The process of feature selection and even dataset selection involved intuition and domain knowledge. This is similar to the generic scientific model.
Google’s founding philosophy is that we don’t know why this page is better than that one: If the statistics of incoming links say it is, that’s good enough
But Google’s early success was not just because of the algorithm. The clean UI,text only ads and great performance were crucial. I’m confident it was intuition\product management that led into these decisions. Moreover, the statistics for incoming links from fraud (link farms) are also very high. The algorithms needs “help” on the features that identify fraud.
Google Suggest brings another example. It is a great feature which interactively “guesses” the search term for the end-user.
For example, typing the word “Robert” suggests the following :
Google Suggest For Robert
But looking for the word “Naked” brings no results at all:
Google Suggest For Naked
But “Nak”still shows some alternatives:
Google Suggest For Nak
Does anyone think the algorithm decided on this feature based on statistics 🙂 ?
Obviously, someone decided that following the real statistics of the human mind would be too dangerous.
I’m very much in flavor of usability research and detailed numerical specs. But in most scenarios, the psychology, human interaction and models are crucial for a building a great product.
It is fun for customers who use the features instead of watching fictitious “product road maps”.
It is fun for developers who see their work is actually used.
It is fun for the executives who can change the business priorities quickly.
If is fun for product managers who can measure actual usage.
It is fun for the R&D manager ,as the problems can not be hidden for long.
In my company, we delivered 72 versions to customers in three years.
Image via Wikipedia
Here is one way to do it:
Hire top talent for development , QA , IT and operations.
Deliver the product as a Service (SaaS). Upgrading one instance is much easier than upgrading 10,000.
Bi weekly synchronization meetings on Monday and Thursday. Monday is just team leaders and Thursday is all of R&D.
Invest early in QA automation. We invested $20,000 in Automation infrastructure at a very early stage.
Invest in Unit-Testing as much as possible.
Avoid branching. Branches are evil. Merges are Yikes. One branch is good, two is max.
Invest in the “Ugly stuff”. Deployment scripts, upgrade scripts, database consistency.
Constructive dictatorship. Every code change has a ticket. Every. No exceptions.Really.
First week is for coding. Than it is feature freeze. Three days for QA and bug fixes.Code freeze. Two days for final QA and critical fixes only. Release on Sunday.
In the next post I’ll try to answer the tricky questions: What about longer features? How not to scare the customers? and more.
Evil Fish 