You are finite. Zathras is finite. This is wrong tool.
On the one hand I read this fascinating article on AI and the implications of how we think and discuss AI.
And on the other hand I see this:
Nude programmers or smart people thinking about hard problems – one is the field I joined the other — well — not so much.
In 1996, Len Widra, a Principal Engineer at SGI, and I got into a heated argument over the importance of software vs. hardware.
I was a kid out of school with an ego to match. Of course, I thought I knew everything. The crux of our debate was whether the software was a relevant technology or important technology.
Len’s observation was that software was irrelevant or something like that. Hardware, he observed, was the important technology.
As a software engineer, this was infuriating. As a computer scientist, this wasn’t very kind. How dare he say that a bunch of silicon was more important than my code?
It’s been almost 18 years, and I’ve learned more.
What I have learned is that new software rarely, if ever, displaces old software unless some new hardware shows up. New hardware shows up, and that new hardware makes the old software irrelevant or obsolete.
There is one interesting caveat. Some software applications are really dependent on the quality of the algorithms, and as the algorithms improve, the software gets obsoleted regardless of the underlying hardware changes. In many cases, the emergence of new algorithms creates new hardware that helps obsolete the old software.
For the vast majority of software systems, however, that’s not the case.
When you are looking for a new opportunity in the technology space, what you need to look for is where new hardware is emerging. If it is sufficiently different, that new hardware will obsolete the old software that was tied to the new hardware creating new opportunities for new software.
A mouthful.
A few examples:
(1) the emergence of x86 servers created the opening for Linux. Before x86 servers were a reality, the UNIX vendors owned the entire software and hardware stack. When x86 became good enough, a new software stack could win because the software used new hardware.
(2) Flash in the storage industry has truly created a massive disruption, enabling many different kinds of software stacks.
(3) Merchant (aka Broadcomm) Silicon is disrupting the networking space that reminds me of the x86 disruption.
(4) ARM processors made mobile computing plausible.
Maybe my favorite example is this picture from TIOBE Software that measures the popularity of programming languages. TIOBE measures popularity – not use or lines of code – and has been doing that analysis for many years:
You look at the chart, and you realize how slowly programming language popularity changes except for one programming language: Objective-C. The popularity of a single programming language changed dramatically not because it was good or bad but because of a single new hardware platform that enabled new software.
The hardware disrupts because it enables software that was impossible before. The carefully calibrated trade-offs that are baked into a system are tossed into the sea with new hardware. When you want to look for disruptions to your business, never look at software; software is irrelevant; look at the hardware …
In 2012 I argued with anyone who would listen that the tablet was a smaller lighter laptop and not a new computer. Because it was a lighter laptop Microsoft’s strategy of a unified OS strategy although poorly executed was the right one.
The reason this is important is if you believe tablets are a new growth platform.
The slow down in tablet sales makes my point.
Tablets are a replacement for laptops that are lighter weight. And as laptops get lighter and cell phones get bigger their advantages dissipate ….
The folks at Google wrote about their new toolkit for their new mail app. An app, by the way, that is actually great.
I was convinced – from using the app – that they had a lot of platform specific code. Instead, being great engineers, they cracked a hard nut – how do you build a UI rich application without writing most of the code twice that I didn’t think was going to get cracked anytime soon.
The challenge with UI rich products is that they must interact with the native software interface of the device. And the native interface is very different and is written in very different programming langues.
What Google has done is very interesting. My stock recommendation for UI rich applications is that you have a core that is in C++ and a bunch of platform specific code for each device, the approach Google has taken may indicate a new third way. The Prezi guys did this to great effect. And many of my former Zynga colleagues are doing the same.
I must dig in some more…
An old friend and his family came to stay at my sister’s house in Santorni
That you can stay at too and should!
What was really amazing was that my friend and his children only speak English and my cousins only speak Greek and some broken English. And yet they were able to communicate and become friends. Because when they couldn’t explain things to each other, when the limits of their shared understanding came to fore they relied on the 21st century universal translator:
The world is becoming a smaller place because some companies are trying to change the world…
Yesterday I wrote about how the failure of companies to respect the privacy and happiness of their customers posed an existential threat to the entirety of services that relied on big data.
Some folks on twitter remarked that my Data Scientist Hippocratic Oath is what their companies live and breathe.
@mattocko@kostadis_tech at LinkedIn statements like that oath were part of the company values, which were drilled into you every day.
— Peter Skomoroch (@peteskomoroch) November 20, 2014
And that’s great. I think that protecting user-data aligns with being a great company… And I think a great company sometimes may need to be explicit about how it thinks about user data.
Juliet asked how does this apply when the customer isn’t a person? I guess we need to refine the oath to be a little bit more specific – instead of customers we should talk about people.
And while I called out uber and facebook in my post, it’s only fair to share with folks that Facebook has been working to create a better code for it’s data science efforts described here and that the folks at Uber have hired an outside team to look at their approach to privacy.
I believe the self-interest of companies with vast amounts of data that we want to be kept private will ensure that the data is private because if it isn’t we will have encryption deployed everywhere. And I am delighted to see that happening.
And we’re seeing that. We, as users, need to demand that kind of data protection. The alternative is what happens in medicine where data is so regulated that our ability to fight diseases is being impaired.
Over the last two years, two troubling incidents from large companies have demonstrated the challenge facing modern companies that rely on large amounts of aggregated data to provide a compelling service.
The first was Facebook’s usage of data to test how people behaved when they were made upset.
The second was Uber’s threat to use information about what we are doing with the service for less than admirable reasons.
In both cases, customers had – unknowingly – handed over vast amounts of private information to a service provider that could use that data in ways that didn’t align with our best interests.
Although it’s easy to demonize Facebook and Uber, let’s not. Big Data is an industry that has exploded, and we are all collectively learning how to behave. Every industry has gone through a maturation phase. And my goal is to suggest a path for good because I believe in the value of these services.
The danger for service providers is twofold.
The first is that customers will begin to distrust the service providers and stop using the service. As a very private person about certain very personal topics, Facebook’s confusing and changing approach to privacy has made it difficult to use the service for topics where privacy matters. This switch from early on in my life with FB, where its commitment to my privacy was why I used the product.
The second is that customers will demand or gravitate to services that provide privacy. As a result, the ability to use the data to deliver better and more personalized services will be hurt. This is more likely. And what is more likely is that incumbents will provide that security. And almost as if to prove my point about this, WhatsApp now has a fully encrypted messaging channel. With fully encrypted messaging channels – SPAM becomes a much harder problem to solve, and ad-supported free mail services become much harder to monetize – this is not necessarily a better world for consumers…
What needs to be done?
I believe that people are decent. The world works not because we police it but because decent people know what they should do. We have morals and standards, and decent human beings gravitate to them.
With Big Data and the power to know more about your customers and manipulate your customers in ways that are not always aligned with their wants and desires, the danger for unintended evil is great.
Much like some medical experiments are not done because we think they are wrong, some data uses are wrong.
I don’t think regulation is necessary at this time. I think regulation will hurt the industry. What I do think is needed is a Hippocratic Oath for Data Scientists. If we agree on what is acceptable behavior, then most decent people will behave in the right way, and then the bad ones will be easily identified as bad actors.
More laws won’t protect us from bad people; decent people knowing what is right will protect us.
In that spirit, let me offer an oath.
I suspect if those three rules existed and we relied on the basic decency of human beings, the recent justifiable outrage would be significantly more muted because the things that did happen would not have.
We are a new industry, and as a new industry, we are figuring things out, and figuring things out means making mistakes.
Let’s take this opportunity where we made mistakes to make things better.
Read this really interesting performance analysis of various browser programming languages
Two things that come out of this.
The first is the power of meta-programming languages like Haxe. Using a better programming language and a typeless goop as your target machine-language can deliver great performance. Not entirely surprising – of course – because hardware is un-typed 🙂
I first encountered Haxe four years ago as an answer to my prayers around the mess of Php and Javascript inflicting typeless chaos on the world of web programming.
We actually used Haxe at Zynga to write a renderer if memory serves me write and got better performance than we could have if we had written it in entirely in Flash.
The second is how underwhelming the performance of emscrimpten is compared to Haxe when you don’t have asm.js. There was a time before the mobile web died that I though that C++ to JS would be important. Now that it’s clear that the mobile web is deader than a door knob, the value of Javascript as a front-end mobile programming language is trending to zero fast.
I had the good fortune of reading an article about how we’re getting better at getting better in the New Yorker. And it got me thinking about the pursuit of the 10x engineer and the lack of on-the-job training at most tech companies.
One of my beliefs is that as the size of a company expands the engineering population becomes average through sheer force of numbers. You can fight this problem indefinitely like Google and NetFlix do, or you can ask yourself – what the hell am I supposed do about this?
The general approach most companies take is to lather process on top of everything in attempt to prevent anything bad from happening. In effect, acknowledging that the average employee is no longer good enough to do their job, you rely on a small number of gatekeepers to act as fulcrums on your product quality. Hence the emergence of architecture reviews and design reviews and gatekeepers of quality.
We look at small high-talent density teams and wonder why can’t the entire company be like those teams? Heck we fantasize about the small high-quality teams and their productivity.
We rarely ask the question of how do we systematically improve our teams. We rarely approach making engineers better a core part of our core values. We make our value hire only the best, not make the best better.
The wasteful approach we take to talent, and to people will get disrupted by a company that realizes that it’s better to systematically train hundreds of engineers than to keep trying to find the best…
Our industry’s approach to talent is wasteful in the extreme – we discard 50% of the human race, we don’t train people, we love youth at the expense of the old, we think that insane hours that burn people out are okay and we’re able to do that because there is this almost endless supply of new kids coming in from every corner of the world dreaming of getting a piece of the action.
This approach reminds me of a company that never asks the question of what happened to the OLD users because of all of the NEW users that are joining every day.
I hate to leave a post with only a problem. What are some things that need to change?
Two things that need to happen:
This space feels like there is a lot of opportunity for innovation because of how little is currently being done. And if you believe that companies success is a function of the people, then a deep and sophisticated training program may be a strategic differentiator.
Something to ponder.
As I spend more time learning about Networking, I begin to realize that there are significant disruptions happening and they are not as obvious as “SDN” or “Open Flow”.
One of the most significant differences between a networking device and a server is that the data path stays entirely inside of a custom ASIC instead of running on a general purpose multi-processor.
Why is this important?
When a customer buys a device, what they are buying is the data path, the rest of the product is a second order purchasing decision. In a networking device, the data path is entirely in the hardware, and therefore – although software is important – it’s significantly less important than the ASIC that processes the packets.
A networking company – for all of the discussion about software – is a hardware company that builds an ASIC that processes packets. They live and die by the success of their hardware and by hardware I mean ASIC.
Historically a networking company built it’s chips and sold a device.
The disruption that is happening in the networking space is that – increasingly – a large chunk of the networking ASIC’s are being built for increasingly important segments by vendors that sell to multiple networking companies.
This is very similar to what happened in the late 90’s when Intel started killing off all of the custom microprocessors in the server market.
A simplistic and silly view is that as a result of this disruption is that everyone is going to go and build white-box switches and routers all of a sudden. For some customers wh have the depth of skill and expertise to build their own networking gear this will happen but for the same reasons I am bullish on storage I am bearish on this happening broadly. The majority of the market will continue to buy gear from networking companies.
The disruption that Intel created in the 1990’s was that companies like SGI that built everything soup-to-nuts had to suddenly go from hardware companies that had software to a systems company.
Customers used to buy SGI hardware to get access to the massive number of processors or the high end graphics engines and they didn’t really care about the software running on them too much. The selling point was the hardware.
As the number of vendors that could deliver the hardware that SGI produced customers went from buying whatever hardware SGI produced running whatever software SGI put on the hardware, to thinking about the whole system and that created more options for the customers.
In effect, the decision criteria went from being what SPECint or SPECfp a MIPS processor had to what is your TPC-C and TPC-D number and whether you were a key partner’s of Oracle.
So what is a systems company then?
A systems company delivers a device that is balanced between hardware, software and packaging. The balance of the three components creates a unique selling proposition that the customer and market is willing to put a premium on.
Systems companies emerge in markets where the hardware is supplied by a small number of vendors and differentiation is created in how you combine the hardware and use the hardware in software and create a package that the customer can buy.
The challenge for systems companies is that sophisticated customers can build the same product from the same components and this creates a pressure to innovate in lots of areas outside of the core components.
The challenge for a hardware company as it makes the shift to a systems company is that the mindset of how you build a product has to change. Whereas in the hardware centric world – the hardware is built and the software guys have to figure out how to make it work, in a systems world there is a fine balancing act between the two. And whereas in a pure hardware world the hardware performance was the be-all of your differentiation, the systems company has a combination of attributes in software, packaging and hardware that create the unique differentiation.
In fact, perversely, how you build software and the easiest way to build software becomes more important over time than any specific hardware platform. And the choice of components becomes more important than any specific component.
The challenge for networking companies is that system design is not where their core focus has been over the last 20 year.s
This change in how you build networking devices from – here’s an ASIC with software to here’s a complete balanced and well integrated system is going to be disruptive to how companies do business.
Now that I said all of that, let me observe, I don’t think my employer, Juniper, or Cisco are in danger of getting disrupted per-se. I just think that the way systems will get built is going to be very different and that that change is going to be very interesting.
And that in my mind is where the real disruption in networking is happening, everything else may just be noise.