IBM Buzz Equals Revenues: The Breakthrough Assumption
I am no wizard of finance. I have kept track of money for my Cub Scout troop. I do understand this chart from Google Finance:
The blue column shows that revenue is going nowhere, maybe even trending down. The red line shows IBM’s profit margin which is flat. And the gold bar presents IBM’s operating income. Notice that it is flat. The flat lines are achieved by cost cutting, selling off dead end businesses, and introducing innovations like offices an employee has to sign up to use.
I have focused on IBM Watson because I am interested in search and content processing. To eliminate confusion, I don’t work in this field. It is a hobby. This is a fact that perplexes the public relations professionals who want me to write about their client. Yep, that works really well. If you read my comments in this blog, you will know that I take a slightly more skeptical approach to the search and content processing saucisson that flows across my desk here in Harrod’s Creek, Kentucky. If you are a fan of ground up mystery meat, you can check out my most recent saucisson reveal here.
What caught my attention today was not a report about IBM landing a major deal. Nope. I did not notice a story about IBM’s Jeopardy champ smashing Autonomy’s single quarter revenues prior to the company’s sale to Hewlett Packard. Nope. I did not read about a billion dollar licensing deal for IBM’s semantic technology to a mobile phone giant. Nope.
What I learned about was an IBM chip that does not use Von Neumann architecture. Now this is good news. In my intelligence community lecture about the computational limitations of today’s content processing systems, the culprit is Von Neumann’s approach to computing. In a nutshell, some numerical recipes cannot be calculated because of pesky hurdles like Big O or P=NP.
IBM, if I believe the flood of remarkably similar articles, has kicked Von Neumann to the side of the road with SyNapse. I do like the quirky capitalization and the association of a neural synapse in a brain and IBM’s innovation.
Check out “IBM Chip Processes Data Similar to the Way Your Brain Does.” You can find almost the same story in the New York Times, the Wall Street Journal, and other “real” journalistic constructs. (IBM’s public relations firm certainly delivered some serious content marketing in my opinion.)
Here’s a quote I noted from the Technology Review article:
The new chip is not yet a product, but it is powerful enough to work on real-world problems. In a demonstration at IBM’s Almaden research center, MIT Technology Review saw one recognize cars, people, and bicycles in video of a road intersection. A nearby laptop that had been programmed to do the same task processed the footage 100 times slower than real time, and it consumed 100,000 times as much power as the IBM chip. IBM researchers are now experimenting with connecting multiple SyNapse chips together, and they hope to build a supercomputer using thousands.
There is a glimpse of the future in this passage and a reminder that quite a bit of work remains; for example, “they [IBM researchers] hope to build a supercomputer…”
Hope.
In addition to low power consumption, the “breakthrough” gives IBM an opportunity to “create a library of ready-made blocks of code to make the process easier.”
Who is fabricating the chip? According to IBM’s statement in “New IBM SyNapse Chip Could Open Era of Vast Neural Networks,” the 5.4 billion transistor chip is Samsung. The IBM statement says:
The chip was fabricated using Samsung’s 28nm process technology that has a dense on-chip memory and low-leakage transistors.
That seems like a great idea. I wonder if any of the Samsung engineers learned anything from the exercise. Probably not. The dust up between Samsung and some of its other “partners” are probably fictional. Since IBM seems to be all thumbs when it comes to fabbing chips, the Samsung step may be a “we had no options” action.
IBM’s breakthrough is not just a chip. Nope. It seems to be:
a component of a complete end-to-end vertically integrated ecosystem spanning a chip simulator, neuroscience data, supercomputing, neuron specification, programming paradigm, algorithms and applications, and prototype design models. The ecosystem supports all aspects of the programming cycle from design through development, debugging, and deployment.
To speed along understanding of what IBM has figured out:
IBM has designed a novel teaching curriculum for universities, customers, partners, and IBM employees.
I assume this part of IBM’s master plan for generating more revenue and profit.
Several thoughts crossed my mind as I worked through some of the “real” news outfits’ reports about the SyNapse:
- How long will it be before IBM’s customers, partners, and employees create a product that generates revenue?
- Will the SyNapse eliminate the lengthy training and configuration processes for IBM Watson?
- Will Samsung and other customers, partners, and RIFfed IBM employees stand on the shoulders of the giants in IBM’s research centers and make money before IBM can gets its aircraft carrier fleet turned in a new direction?
I don’t want to rain on the very noisy parade, but I think neurosynaptic technology will require considerable time, money, effort, and coding. But if it boosts IBM’s stock price and creates sales opportunities, SyNapse will have played its part in making the revenue line and the net profit line perform a Cobra and blast upward like an SU 35.
While I wait for Watson, I will use Bing, Google, and Yandex for search. Limited and old fashioned technology that sort of works. Watson running on SyNapse, an interesting lab project that has produced some massive content marketing zing.
Stephen E Arnold, August 8, 2014
