Close interaction with the customer is one of our cornerstones and has been a significant factor in our success. Our customers are welcome during the entire flow of product development: we allow some customers to directly influence our overall product backlog, we demonstrate existing and new features per customer demand, and customers are invited to join the test labs within the development process. Any feedback given by customers at demos or test labs flows into the development: this way we can identify early on whether the developed functionality will lead to true customer value. Our product-deployment support provides support to any customer; a kanban team composed of dedicated deployment managers and team members from the development teams drives this initiative.
What deep learning will allow us to do is to bridge the semantic gap between the fuzzy thing that is the real world, and the symbolic world computer programs operate in. Simply put, machines will soon have much more understanding of the world than they currently do. A few years from now, you’ll take a picture of your friend Sarah eating an ice cream cone, and some machine in the cloud will recognize Sarah in the said picture. It will know that she’s eating ice cream, probably chocolate flavored by the color of it. Facial expression recognition will make it possible to see that she looks excited with a hint of insecurity. Combining information from multiple third party data providers, it won’t be too difficult to infer that you and Sarah are on your third date together.
In spite of these promises, the actual use of consumer wearables within a clinical population remains limited. The potential applications described above are still in the early stages of development, have not been approved for medical use, and have so far been explored predominantly within an academic research rather than a real-world context. Clinical studies to date that have a closer resemblance to consumer wearables involve (1) pedometers and smartphone apps to tackle a sedentary lifestyle and obesity and (2) home telemonitoring solutions for patients with pulmonary conditions, diabetes, hypertension, and cardiovascular diseases.
The financial services sector, starting with insurance, capital markets and actuarial information, has always led the way in the collection, analysis and monetisation of personal data. The very concept of KYC (Know Your Customer) regulation revolves around the bank's ability to detect and prevent identity theft, fraud, money laundering and terrorist financing by identifying unusual behaviour patterns from the customer. Away from regulation and compliance requirements, this enhanced customer insight is helping to change and improve the way financial institutions interact with customers. When IoT crosses with finance, we suddenly get an explosion of data, which will bring even greater opportunities to obtain data and build even more accurate profiles of customers.
When you take a look at the transition from server software to Azure, what's going on in terms of cloud infrastructure, the company is absolutely the No. 1 company serving enterprise backbone needs, which is fantastic. It's making the migration to cloud. We started a good thing with Azure, and the company has made well more than two years of progress in terms of being able to compete with the right cost profile, margin structure, and innovation versus Amazon. There's still a lot to do on that. It's not like the company rides the same momentum. I think the company in terms of the investments it's making in evangelizing those products, supporting those products technically, I think it's really doing a good job.
Besides cyber intelligence, companies and government agencies will begin using Blockchain encryption to protect against cyberthreats. Blockchain is the public ledger of Bitcoin transactions, which is updated by a network of several computers solving complex algorithms for verification. As such, it is considered a secure way to record data, as tampering with the records would require taking over majority of the computers in the network - a nearly impossible feat. MIT has tapped Blockchain technology to build Enigma, which could potentially allow databases to retain sensitive information and process it without risking exposure to malicious parties.
"If you want to solve consciousness you're not going to solve it using the sorts of algorithms they're using," he said. "We all want to get to the moon. They've managed to get somewhere up this stepladder, ahead of us, but we're only going to get there by building a rocket in the long term. "They will certainly develop useful algorithms with various applications but there will be a whole range of applications that we're really interested in that they will not succeed at by going down that route." In the case of DeepMind, Stringer says the reinforcement learning approach used to teach systems to play classic arcade games and Go has limitations compared to how animals and human acquire knowledge about the world.
IAP addresses many of the use cases that HTTP 1.1 ignores. While HTTP2 and WebSockets definitely address several problems not addressed by HTTP 1.1, we believe that more is still required, as we describe in our blog: Why HTTP2 and Websockets are not Enough. IAP is a free flow message based protocol. The communicating nodes exchange messages, just like HTTP requests and responses. However, IAP does not require that each message have a response. Being a free flow protocol, IAP specifies only that nodes exchange messages. Messages can flow freely in both directions of a network connection as the communicating nodes see fit for the purpose of the communication. We have described some of the core message flows in more detail in our tutorial IAP Message Flows.
Blockchain technology is going to enable disintermediation in a great many fields that until this point have largely not been digitally disrupted. Blockchain technology ... could take an enormous amount of friction [out of] legal processes and legal costs. One person's friction is another person's profit. I also think thatbanking and financial services could be significantly changed by the integration of blockchain technology. One thing that I predicted in the book, which is now happening: Goldman Sachs recently filed a patent for creating its own digital currency, which is really sort of a walled-garden use of blockchain technology, to settle foreign transactions and asset settlements, from stock sales to wire transfers and the like. Goldman Sachs is quintessential Wall Street. To see Goldman Sachs move in this direction I think portends a lot of what is to come.
It’s important to note that as companies build out their IoT ecosystems, whether for the consumer or business market, connectivity and security standards are almost nonexistent. Most of these projects involve customization and add to this the fact that there isn’t one dominant technology service provider in the IoT space and the approach to standards is at best fractured. And of course all of this has implications for security. In fact, during 2016 we’re set to witness more examples of security vulnerabilities related to IoT. This is inevitable. The lack of standardization means IoT is an incredibly fragmented space and one in which network security has not been a priority for device manufacturers.
Quote for the day:
"I have no special talents. I am only passionately curious." -- Albert Einstein