Over the years, the technology kept changing, and I was unable to have this blog keep pace with it. I recently reverted to a ‘basic’ template because the old feature-rich template wouldn’t work, and neither did I have the time or inclination to make it work. However, ‘The Wayback Machine’ does have a record of this blog, the way it was when it looked perfect.
Apart from looking perfect, the information was easily available up front. The current visitor is encouraged to have a look: especially at the post which pulls interesting posts from across the categories to give a bird’s eye view to this blog. If you want to determine, at a glance, what this blog is about, the current layout is helpless – please click here.
Digital cameras in the period 2000-2020 have a curious rise-and-fall history. The period 2000-2001 was a period of gadgets, Palmtops were doing brisk business, Camcorders and digital cameras were also selling well. Consumer and prosumer digital cameras were being released, having around 5MP. Previous to this timeframe there existed some Sony Mavica cameras but the quality of these 5MP ones was quite improved. Several cameras with large sensors (1/1.8″) were available then. Large sensor mostly means improved photo quality. Since DSLRs are out of scope for this post, we will consider 1/1.8″ sensor as large. Large sensor is a big advantage in consumer cameras.
As we move to the period 2008-2009 and beyond, the megapixels were on the rise. Now, 12-15MPs were easily available. Still companies were using large sensors to provide quality pictures. Higher zooms were available now, image stabilization had become the norm.
In the 2010-2012 period though, the sensor sizes became smaller and zooms became higher. This reduced photo quality. Why would companies want to do this? I can only guess that higher zooms would give the cameras a USP and allow them to be sold for a higher margin. At the same time, smaller sensor sizes would allow even more margins. Hoping the customer would not notice.
In the 2016-2017 period, smartphones started taking the lead in consumer photography and camera sales started declining. One important factor that added to this was the lack of innovation in digicams. Sales of consumer DSLRs such as the Nikon D5100 also started declining. As early as 2010 Nokia was talked about as the world’s largest seller of digital cameras, but the quality of photos from mobile phone cameras was poor. In 2010 – Nokia sold over 435 million camera phones worldwide, giving them over a 30% market share of all digital cameras sold globally that year. However the picture had changed by 2015. Nokia’s phone business had been sold off to Microsoft, and its worldwide phone sales for the full year were less than 30 million units. From leading the digital camera market in 2010 with over 30% share, Nokia had vanished from the top vendor rankings within just half a decade. iPhone 6 had been launched with a not-too-bad camera (though with a small sensor again). Most cellphones still had a small sensor to save cost (and because of space constraints in a phone), so the quality was still questionable in spite of technological improvements. No one was thinking about quality, only margins.
The above graph shows 2010 as year 1 and so on.
Around 2009-2013 several markets, esp in Delhi NCR were dedicated to cameras, lenses, repairs etc. By 2023 most of these had either closed or started catering only to professional gear.
In 2018, most mobile phones started shipping with two cameras on the back, which soon increased to 3 or 4 cameras. This, along with AI improvements allowed ‘background blur’ without using expensive lenses, in a never-before way. It dealt a serious blow to the digicam market. Overall, 2018 saw a significant improvement in mobile phone camera quality, both because of use of AI and multiple cameras. A battle was on among mobile companies to improve photo quality without increasing sensor size. Some of the more expensive phones did start getting larger sensors though of late.
As of 2023, only 1 – 2 models for new consumer digital cameras or consumer DSLRs were available in India, that too with difficulty. The consumers are at a loss: those who cannot afford a professional DSLR have to make do with low quality smartphone photos (even iPhone photo quality at best can be rated ‘poor’ compared to what a decent camera of today could do, if manufactured**). We are buying mobile phones that are being sold at prices several times the manufacturing cost. Yet, giving us low quality because the customer is not smart.
My suggestion to the smart buyer: rather than buying an expensive iPhone, buy a normal phone (costing around USD 300) and use the rest of the money to buy a mirrorless DSLR. You have nothing to loose but your mobility!
** some of the latest iPhone models do have larger sensors to improve quality.
Crux of the story: market for digital cameras got killed because of the greed of camera companies.
DCCI – a technical score based on simple parameters that indicate the quality of photos that can be expected. Here is my formula:
DCCI = (Sensor Diagonal Length in mm)^1.2 * (Max Zoom factor available) * ln(2^((Year Manufactured-1975)/1.5))/ln(10) / Const
Const is fixed at 559.7566738, calculated using a specific camera as “standard”.
For example, for the Canon Powershot A650 IS that I used to have:
DCCI = (9.3^1.2 x 6) x ln(2^((2007-1975)/1.5) / (ln(10)*const) = 1
Similarly for Panasonic Lumix LZ20 that I also have:
DCCI = 3.1762
For a modern cellphone camera, like the iPhone 14 Max Pro:
DCCI = (9.5^1.2 x 3) x ln(2^((2022-1975)/1.5) / (ln(10)*const) = 0.76534 (since it features 3X optical Zoom)
For Canon EOS 5D Mark II with 24-105mm kit lens:
DCCI = (43.27^1.2 x 4.375) x ln(2^((2008-1975)/1.5) / (ln(10)*const) = 4.7581
Though I do believe that DSLR technology has not seen the same level of improvement over the last decade as the mobile camera tech. This is version 2 of the index. Version 1 was:
DCCI = ((Mega Pixels ^ 0.8) * (Optical Zoom) * (Sensor Size ^ 1.2)) ^ 2.3
For detachable lens camera use the total zoom of all lenses you own.
Having hosted multiple WordPress blogs over the years, I have come to the following conclusion: static sites are best. My expectation is that you should be required to create the website and then forget it, while it works fine over the years. Doesn’t work with CMSs, they need to be updated, and PHP changes over time leaving a broken blog. In face there are ways to integrate user comments with static sites.
Wordpress itself has several issues – it should, in my expectation take care of making sites search engine friendly. Setting up the ‘viewport’, ‘gzipping’ content, social sharing should come out of the box. Strangely, doesn’t.
I then looked over at Drupal, and it does seem quite better: I did a pingdom test of:
WordPress.org
Drupal.org
to see the out of the box SEO optimisations of both products. Drupal got A where as WordPress got D. Pretty much matched my expectation after seeing google usability issues for my website for years.
Drupal may be tough to setup initially, but does an overall better job than WordPress in my opinion.
Big data can be explained by understanding the following key aspects:
Big Data
Volume. There is no specific quantification that says volume above these many terabytes will be called Big data. What volume one considers as threshold depends on the perspective and the year we are in (big data is a moving target). However, this large volume of data is mostly the cost-free byproduct of digital interaction such as consumers buying stuff off online shops.
Velocity. The speed at which data is generated and processed. Big data is often available in real time.
Variety. The type and nature of data. Big data draws from text, images, audio, video; plus it completes missing pieces through data fusion.
Data must be processed with advanced tools (analytics and algorithms) to reveal meaningful information. Big data is not about asking why, but about detecting patterns. Information generation algorithms must detect and address visible and invisible issues and factors.
Parallel computing tools are needed to handle data.
Often “inductive statistics” are used to infer laws (relationships, causal effects) from large sets of data to reveal relationships or dependencies or to perform predictions of outcomes and behaviours.
Artificial intelligence deals with mimicking the way the human brain works or evolution of life and other such natural phenomena. Here are some of the artificial intelligence techniques:
Artificial Neural Networks
Fuzzy logic
Genetic algorithms
Cellular automata
Artificial Neural Networks are inspired by the way the brain works. A neural network consists of a network of nodes. Each node is capable of making a simplistic decision or a simple calculation on the inputs, and providing an output. By interconnecting a large number of such nodes, it is possible to do data analysis and complex decision making. Each node has a threshold assigned and each connection between nodes is assigned a weight. A random NN is constructed to begin with. This is then “trained” by providing inputs, and matching given outputs against pre-calculated known outputs. When a mismatch is detected between current output and favoured output, the weights and thresholds are suitably modified.
Genetic algorithms are based on the process of evolution and natural selection. To begin with a pool of random “algorithms” is built. Each such algorithm is tested with given input and required output. Those algorithms that give results closest to the desired outcome are selected. Thereafter the next generation is built by combining pairs of algorithms from the previous generation and adding more steps (random mutation). This generation is again tested for fitness. This process is repeated as many times as needed. The algorithms keep increasing in complexity with each generation.
Please refer to Cellular automaton for more information on cellular automata and Fuzzy logic for more information on Fuzzy Logic.
Good quality English translations of Sri Guru Granth Sahib ji are very rare, if any. In any case, the words of Brahmgyanis (People who are in tune with the Celestial Formless Creator) can be understood completely only by Brahmgyanis. It is like asking someone who has never seen an elephant, but only read about it, to describe how an elephant looks like. However, your spiritual journey needs a starting point. For me, this has always been kathas (spoken discourse) of Giani Maskeen ji, or the Punjabi translation of Sri Guru Granth Sahib ji by Prof. Sahib Singh ji.
Please find attached interpretations of the Sukhmani Sahib (one of the many prayers withing Sri Guru Granth Sahib ji) in English. This commentary pulls out key thoughts from the Sukhmani Sahib and tries to explain. This is work in progress, only a short part completed so far.
Sikhs treat Sri Guru Granth Sahib as the Living Treasure of Knowledge, as the Guiding Master on the spiritual journey and embodiment of Word form of the God. The word Guru literally means a teacher in Hindi. The advice that comes from Sri Guru Granth Sahib ji is timeless and unchanging, rather than worldly knowledge which is ever changing.
What does the Guru say about the kind of teaching that needs to be practiced with the students? Read below:
ਪਾਧਾ ਪੜਿਆ ਆਖੀਐ ਬਿਦਿਆ ਬਿਚਰੈ ਸਹਜਿ ਸੁਭਾਇ ॥
We call person learned, if through the internalisation of his knowledge, he finds peace and his mind stays at rest.
ਬਿਦਿਆ ਸੋਧੈ ਤਤੁ ਲਹੈ ਰਾਮ ਨਾਮ ਲਿਵ ਲਾਇ ॥
He ventures inwards through the map of his knowledge, and by focusing attention on the True Name he attunes to Divine One.
ਮਨਮੁਖੁ ਬਿਦਿਆ ਬਿਕ੍ਰਦਾ ਬਿਖੁ ਖਟੇ ਬਿਖੁ ਖਾਇ ॥
The self willed teacher (who has not subdued his mind) is only a knowledge seller. Little does he know that this trade is a poison that finishes the spiritual purpose of his life.
ਮੂਰਖੁ ਸਬਦੁ ਨ ਚੀਨਈ ਸੂਝ ਬੂਝ ਨਹ ਕਾਇ ॥੫੩॥
Such people are fools, they have not understood the Eternal Word and have no intuitive knowledge.
ਪਾਧਾ ਗੁਰਮੁਖਿ ਆਖੀਐ ਚਾਟੜਿਆ ਮਤਿ ਦੇਇ ॥
A wise teacher follows precisely the teachings of God Guru and gives the same instruction to his disciples.
ਨਾਮੁ ਸਮਾਲਹੁ ਨਾਮੁ ਸੰਗਰਹੁ ਲਾਹਾ ਜਗ ਮਹਿ ਲੇਇ ॥
He tells his students to praise the Lord’s Name, the manifestation of God. To collect Naam which is the only profitable trade in this world.
ਸਚੀ ਪਟੀ ਸਚੁ ਮਨਿ ਪੜੀਐ ਸਬਦੁ ਸੁ ਸਾਰੁ ॥
His own heart becomes the slate on which he writes the word of the True Guru, and thus his own mind is cleansed of evil. This is the best learning.
ਨਾਨਕ ਸੋ ਪੜਿਆ ਸੋ ਪੰਡਿਤੁ ਬੀਨਾ ਜਿਸੁ ਰਾਮ ਨਾਮੁ ਗਲਿ ਹਾਰੁ ॥੫੪॥੧॥
Such a teacher is then called wise and learned who wears the garland of Lord’s Name
Guru Nanak Dev ji was the founder of Sikhism. Sikhs believe Him to be God in a Human form. His teachings are embodied in Scripture form: Guru Granth Sahib ji.
Traditionally, Guru Nanak Dev ji’s prakash purab (the day He spread forth His light on this earth) is celebrated on the full moon night of a specific lunar month. This year, this day coincided with the Supermoon. Here is a photo of the Golden Temple with the supermoon visible in the background:
Supermoon and the Golden Temple
My message sent out for this year’s Gurpurab greeting:
Kot karam karai hao dhare || Sram pavai sagle birthare || (278)
Hao vich maya, Hao vich chhaya || (466)
Kirpa kare je aapni, tan Gur ka Shabad kamahe || Nanak kahai sunho jano, eet sanjam dukh jai || (466)
By engaging in good deeds alone we cannot lose our egoistical pride. This pride causes to remain attached to Maya, and deprives us from appreciating Divine Bounties. Even millions of good deeds, done under the false influence of Maya – go waste. While we may have laboured, we do not receive Divine Respect. Reciting the Lord’s Name under the True Guru’s instructions, this veil of ego is removed and we are enraptured in Divine Love. Such a path is obtained by great fortune, and through the Lotus Feet of the Guru. Dhan Guru Nanak.
One of the central teachings of Guru Nanak was to see God as embodied in His Creation and recitation of His Greatness with loving devotion.
