I was reading an article titled ‘Engineering wants to rewrite‘ on the SVPG blog and couldn’t help keying in my own thoughts around the dynamics engineering has to work its way through in a technology startup. To quote the article:
When a company does get into this situation, everyone typically blames engineering. But in my experience, the harsh truth is that it’s usually the fault of product management. The reason is that for the past years the product managers have been pounding the engineering organization to deliver as many features as the engineering team possibly can produce. The result is that at some point, if you neglect the infrastructure, all software will reach the point where it can no longer support the functionality it needs to.
Most startups work at break-neck speed and the focus is always on features. The uncontrolled pace of piling up features without thinking of infrastructure and architectural limitations is a key component in this collapse. In a startup, a high rate of feature addition is inevitable and needs to happen. In this view, how should the Engineering and PM verticals be prepared to ensure a catastrophe is not waiting down the hill as products roll out? Here are some thoughts . Continue reading
It is encouraging to see some quality product development technology startups in India forming up steadily. We have finally broken the IT services jinx and are looking beyond the outsourcing model. It is taking time for this wave of change to hit the shores, but it is worth the wait.
I have been directly (I work for one!) and in-directly involved with some technology startups. I do experience the pains of building a product development company on several occasions, especially in the Indian context. Continue reading
Yahoo! Inc recently announced the release of BOSS – its open search (web-service based) platform. BOSS (Build your Own Search Service) exposes Yahoo Search through an App ID and a web-service. It will be interesting to see how BOSS matures around two main search engine buzz-words: vertical search and semantic search capabilities. I spent some time trying out BOSS on some of my favorite problems (Yes, I am going to share the URL on my website soon!). Here is a quick catch-up on the ‘cool’ and ‘not-so-cool’ BOSS features.
- Vertical Search Engines: It is not easy to construct a vertical search engine and use BOSS for searching on a few thousand sites. BOSS doesn’t support search for multiple sites (in fact it does it wrongly if you try to search for multiple sites through the web-service), nor does it allow regular expressions for sites to search. This doesn’t add up well for building up your own little vertical search engine. Google’s Custom Search Engine scores way higher on this one. With easy to configure websites and ability to tweak with the relevance and configurations Google CSE definitely scores higher. But BOSS has just arrived; I am sure changes will pour in soon.
- Semantic Search: Hakia has done it; many more will follow! This is a good value proposition by Yahoo and is primarily aimed at spicing-up the horizontal search market. It provides developers and researchers to try out their own versions of relevance and mash-ups on top of Yahoo’s rich information source. This however operates on a horizontal search model.
- Multi-modal Search: Yahoo has done a good job in providing Image and News Search features. Image searches however have relatively fewer use-cases, especially if the search is not based on Image content. A Riya like visual-search would have been awesome.
Currently there are no query limits on BOSS, but with rapidly increasing usage and adoption this is bound to change. The monetization abilities in both Yahoo and Google open search platforms is fairly limited and concentrates around Ads-World. For small enterprises and start-ups the ability to use these applications is therefore cumbersome, especially if the value proposition is being built around a vertical search model.
On a related note, Yahoo’s partnership with Hakia comes at an interesting time with Microsoft completing the Powerset acquisition. The semantic search war is catching up some steam!
PowerSet and MSFT finally announced this rumored acquisition. MSFT has acquired Powerset for close to $100 million. Powerset is a semantic search engine that extends the XEROX-PARC’s licensed linguistic technology. I have tried Powerset when it was a beta and when it got (almost abruptly) released (with search limited to wikipedia and freebase).
The use of semantic technologies for horizontol search engines look highly improbable. The nature of the web is too diverse to be nailed by a single hammer. A related article on making search relevance more meaningful is in this earlier post.
MSFT plans to integrate the Powerset team with its search relevance team and explore advanced search capabilities while taking the Powerset technology beyond wikipedia. MSFT has been creating noise around enterprise and local search, both of which are vertical in nature. This acquisition can add value in making vertical search offerings from live.com smarter and probably scaring the Mountain View behemoth. Whether MSFT takes Powerset’s saplings and nurtures it into its Redmond forests – this only time will tell.
On a related note, I find results from Hakia more useful. Try a sample search for “is EPS the right measure for stock performance” on both powerset and hakia and you will see the difference. Hakia gives results much more relevant to EPS – at least it displays on the very first page results about the use of EPS measure for measuring stock performance. Powerset returned results that had nothing to do with “EPS ~ Earnings per share”. The results from Powerset were purely keyword matches – it mostly matched Extended Play (EP) vinyl records.
In general, most semantic searches seem to be working better on Hakia than on Powerset. I am surprised why Hakia was not approached by suitors if the motivation has been to ramp up semantic abilities for search engines. Or may be it was!
Well they always were. We are beginning to realize the presence.
Dus Ka Dum (power of 10) is a reality show hosted by popular Indian actor, Salman Khan. The show progresses by asking the player a question, the answer of which tries to predict a percentage. A possible question is “What percentage of votes will the Congress Government win if India has a general election today?”. Answering five correct questions would bring Rs. 10 crores ($2.5M). The correctness of the answer is measured by the fact that it falls in a particular range of the correct answer. The first question allows a 40% window around the correct answer and wins you $250, the second allows a 30% window and wins $2500, the third allows 20% with $25,000 return, the fourth returns $250,000 with a 10% window. The bull’s eye is for the fifth answer with a $2.5M cash prize. Continue reading
The IEEE Spectrum in its April 2008 issue featured the ‘Top 10 Tech Cars’. This included the recent eye candy of India’s common man – Tata Nano. With Tata Motors planning to go full production in later 2008, this small car revolution is obviously creating excitement.
There are concerns about environmental hazards because of easy affordability of the vehicle due to its low cost. I wonder how much of that is a concern because the low cost would also mean easy replacement of the over-polluting Auto-rickshaw in the country and a much better comfort for local city travel. It is interesting to note that a petrol-driven three wheeler costs around Rs. 90,000, which is Rs.10-15K less than the Nano. With double the top-speed than an auto-rickshaw the Nano would also mean faster travel and lesser traffic congestion. The better speed probably over-compensating for the more space it would take on roads.
As an optimist, I look forward to see Nano hit the roads and replacing the more polluting vehicles on the Indian roads. In the process this also creates a better life for the common man.
There is a flurry of announcements around horizontal and vertical search engines offering ‘better’ and ‘more relevant’ content retrieval. SEOmoz.org has an interesting article on the ability (or inability) of search engines to return relevant results. In this entire discussion of retrieving more relevant there are two seemingly related problems – ‘personalized search’ and ‘disambiguation (of search terms)’.
Personalized search is the ability to convolute the search engine results with the user’s profile in order to return the most relevant search results. The user profile can be created by using the following information:
- User browsing (search, click-through, time-visited on site, etc) history
- Desktop data (files, content, most-accessed files)
- User feedback (asking users to rank order the results based on their preferences)