IBM’s five qubit processor
Quantum computing has the potential to revolutionise many aspects of computing. While it might not make the graphics on your smartphones games better or handle most of the tasks your laptop’s CPU currently does, it is especially effective at computing work which requires finding optimisations. In fact, in many data-heavy tasks which require such logic, such as scientific analysis, financial systems, logistics or weather predictions, these computers could be several orders of magnitude faster than today’s fastest chips.
The problem is that the technology is so young that neither the hardware, software, logic or human skills have yet matured to the level of being useful. The hardware itself is still fighting against the laws of quantum mechanics to exist. So it was a surprise when IBM, one of the leading researchers in the Quantum computing field, announced an online service that lets anyone use the five-qubit quantum computer in its research lab in Yorktown Heights, New York. You can access the machine via the Internet through a simple software interface (or at least it’s simple if you understand the basics of quantum computing).
Deep Learning and Artificial Intelligence: Google, Facebook, Amazon, Microsoft, Elon Musk…
I’m going to have to combine all of these companies together, because it seems like this battlefield is a full-on open-source brawl. Artificial Intelligence and Deep Learning, some of the most valuable and cutting-edge technology in existence right now, has top tech companies recruiting AI researchers for higher salaries than the world’s top sports stars.
Yet at the same time, all of them are also making some of their core technology available to the public, which almost appears completely counterintuitive.
Just take a look at some of these headlines, all from the past 6 months:
These are not just side projects that these tech companies have thrown together to please the open source communities. Google’s Tensorflow is what it uses for image searches and automated email replies. Microsoft’s technology (called CNTK) has enabled it to translate Skype conversations in real time, and Facebook uses it to find friends in photos and figure out which stories should end up in your news feed.
Perhaps most ambitious of all is Elon Musk’s new company OpenAI. This company will allow its researchers to work on pushing the underlying technology as far as it can go and then releasing toolkits to the world to use the improved, cutting edge technology. This is instead of researchers trying to use the AI to meet specific product requirements (e.g. facial recognition for Facebook’s photos). Recently OpenAI released its first batch of AI software, a toolkit for building artificially intelligent systems by way of a technology called “reinforcement learning” (which we covered in more detail when talking about Google Deepmind’s victory in the Go Championship).
Super-efficient hardware designs: Facebook & others
When you think about the biggest computer hardware makers in the world, who springs to mind? HP? Dell? Lenovo?
In reality, while these companies may be the public faces of selling servers, they outsource the actual manufacturing of the machines to OEM subcontractors in companies like China and Taiwan.
The biggest buyers are the tech giants who need huge numbers of servers to feed the demand for their ever-growing user base, and the biggest two at the moment are Google and Facebook. When they both started, most of them bought their servers from the big sellers, like the ones we listed above. But as their companies grew and they reached industrial scale, they began to see how much more efficient they could become if they cut out the middleman and started contracting directly with the OEMs to get a cheaper deal. Not only that, they began to cut out unnecessary components and steel to improve airflow and access to components, reducing maintenance requirements and power consumption (which can save millions of dollars for companies that use this many machines).
While Google has always kept its exact technology a company secret, Facebook has taken the opposite route, releasing the design for many of its best hardware components for anyone to use.
In fact, this strategy has proven to be so successful that it started a group called the Open Compute Project, the non-profit that oversees Facebook’s effort to share hardware across the tech industry. Other companies which have joined the OCP include Microsoft, Apple, cloud computing giant Rackspace, and several of the country’s biggest financial companies, including Goldman Sachs, Fidelity, and Bank of America.
But why are companies doing this?
The question remains, why would successful and highly profitable companies release some of their most important technology to the general public, and thereby lose a strategic advantage? And even help their competitors innovate!
Well, the answer is that it helps them innovate in the long run.
Here are several ways it is beneficial for these companies to share their secrets:
- Accessing a larger talent pool: No matter how large you are, you have a limited number of employees with a limited amount of time to research this technology and produce products. If you make it available to thousands of other developers, they might just make improvements which you hadn’t thought about, and which help improve your own products
- Training a new generation for your future needs: Many of these technologies are still at the beginning of their lifecycle, especially quantum computing and AI. It is going to take many years for the underlying tech to improve and mature. But by making it accessible now, this increases the number of people who will be improving their skills and knowledge in it. In 5-10 years time when you are then looking to recruit people to turn this technology into products, there will be a larger talent pool available.
- Economies of scale: This applies especially to the customised hardware. The more companies which use Facebook’s custom hardware designs, or at least components of them, means that the manufacturers in China can produce them in a higher volume, thereby making bulk deals and bringing down the cost for each unit, which benefits everyone (especially Facebook who would be buying a large quantity).
- Reduces the risk of being disrupted by a competitor: The simple fact is that while all of these companies may be behaving similarly, they are competing amongst themselves. Google was the first to open source their Tensorflow AI technology. At this point, Facebook and Microsoft needed to figure out a way to respond to this news. If they did nothing, then there was a risk that the open source community, and the many startups which rely on this technology and developers, would quickly put their efforts behind working with Google’s technology, leaving Facebook and Microsoft behind. Therefore, by following each others’ strategy, it reduces the risk of getting disrupted and left behind.
- Cross-selling services: All of this underlying technology may be available, but in order to run it you still need access to servers (especially multiple servers when it comes to deep learning). And while some larger companies may have this hardware, many startups have grown up by using on-demand cloud servers like Amazon Web Services, Microsoft Azure or Google’s Servers. If their experiments with the open-source technology turn into something they’d like to turn into a larger-scale application or new company, then the company who’s technology is being used could benefit by selling them the necessary services to run it. This is how AWS became a nearly $10 billion a year cash cow.
- Outsider perspectives: Sometimes it takes an outsider to see something which you and your company cannot. Especially in the ultra-technical world of cutting edge research, it is very easy to develop tunnel vision in your field based on your own knowledge and that of the people around you. Often, someone with a completely different upbringing and skill set may find the solution to a challenge which experts have been struggling with, leading to big jumps in the rate of innovation. By opening up technology to everyone, you make this more likely to happen.
- Some secrets remain: It is important to remember, these companies are only making a small amount of their technology available. They still have control over the rest of their business and their R&D, and often the bit that is released is even just a part of the full picture which the company has developed. So these companies have not lost all of their advantages.
- “It is the right thing to do”: This may be me being naive, but in at least some cases you get the sense that the companies releasing their technologies believe that by doing it, they will benefit the wider world more than by keeping it secret. Many of the leaders of these technology companies are still the founders and are still relatively young, and have talked publicly about the need to do work which improves the future. Mark Zuckerberg for instance wants to bring the internet to remote parts of Africa. And Elon Musk has stated that the Tesla Roadster was important to show the world that electric cars could be not just practical but desirable, because fossil fuels would eventually no longer be sustainable. Equally, you get the ethos that by sharing aspects of technology like this, they do firmly feel like it’s the right thing to do.
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