Blockchain has been a term that has been thrown around for a while, even though many people do not completely understand what it is. Essentially, it is a potentially revolutionary piece of technology that top companies are currently using to track shipments and store big data. Going back to the original question of what it is, blockchain is a public digital ledger. So here is how it works:
- One person wants to pay another person
- That payment is logged and entered into a “block” with other transactions
- The data from that “block” is sent to every entity in that network
- The entities in the network verify that “block”
- The “block” is then added to a chain, where it cannot be changed
- The transaction is complete
One of the major advantages of blockchain technology is the high level of security it offers. Once the “block” is added to a chain, that information cannot be changed so it is almost impossible to hack since the ledger is held by so many entities and there is a permanent public record of the ledger as well. Additionally, when the entries are being logged in, they are usually logged using pseudonyms so that provides even more security.
So why is this so important? In light of the recent breach of security with Facebook and Google, it is crucial to look for technology that provides tighter security online, especially when it comes to sensitive information such as financial transactions. In today’s age, almost every company is heavily dependent on technology when it comes to their customers’ data and it is imperative to ensure that their information is being protected. It raises a lot of concern from a consumer’s perspective when two of the biggest tech companies are unable to provide the high level of security they expect. That is why we should be exploring new technologies that have some form of a public record while being almost impossible to hack.
According to recent reports, we could soon see fully self-driving on U.S. roads. The Trump administration has been saying that it is considering allowing real-world testing for thousands of fully self-driving cars to allow for companies to start gathering more accurate real-world data for when the real push for self-driving cars occurs. Cars used in the program are said to need technology that monitors speed and sensor functionality as well as the ability to fully disable the car if it needed according to the National Highway Traffic Safety Administration. The NHTSA is also working on figuring out if it wants to make data available to the public that could contain sensitive information such as near misses. The Trump administration is also looking to revise safety rules to allow different types of cars to be allowed so automakers can design cars that don’t have pieces like a steering wheel or mirrors as the cars will be handling everything.
If this program goes through, it will open up a huge job market for people looking to work as a technical employee. With relatively low amounts of data and experience, this field would surely be an interesting one to get into especially as someone coming out of college. While there are still barriers in place including the senate as well as local and state government approval, the future is bright for self-driving cars.
The Real Estate industry is not the first thought of when it comes to technological advancements. However, that has changed over the last years. Real Estate tech investments have ballooned from $33M to $5B since 2010, mainly focusing in the property management. Perhaps this has been the topic for many Real Estate agents as they are fearing that it would replace high-value and negatively impact face-to-face interaction, technology and automation, when used thoughtfully, humanize the customer experience.
There are different ways we could look at the benefits of this market-industry integration. For example, real estate tech investments may provide solutions that systematize how properties and tenants are managed, while others contribute to the data insights that is being provided to landlords and tenants. From a data visualization perspective, the amount of information retrieved can be overwhelming, but it also led firms to focus on how to best visualize all kinds of constant streams of information. Leverton, in one hand, applies AI / Deep Learning technology to extract data from real estate firms and create data visualizations and analytics from unstructured data and converted into meaningful insights. Another emerging product that promises help visualize data is called Matterport, which allows people to virtually walk around the interior of an existing space using 3-D renderings.
Justin Rowlatt of the BBC looks at various valuation metrics related to Uber’s entrance into the driverless electric car market. Rowlatt postulates that Uber is in an advantageous position to reduce transportation costs and gain a positive net present value from their investments. He cites the driverless format as having the potential to cut transportation costs by 50%. Additionally, Rowlatt points out that electric engines extend the life of the vehicle and cost less to maintain because they have fewer parts. He believes electric engines will reduce costs by another 40%.
He notes that profits from this investment depend on regulatory approval from government entities. By assigning a probability of reaching this approval over the three years, we can find the net present value of investments Uber would make. Using the industry standard as an example, the investment for driverless car technology costs $1.1 billion. Add another $500 million for an electric car fleet, and the total investment is $1.6 billion. With a 90% reduction in costs, Uber would have 1.7 billion in savings per year assuming the U.S. government provides regulatory approval. If we put the odds of approval at 0% in year 1, 50% in year two, and 100% in year three with a discount rate of 12%, the net present value equals $420 million, making this a good investment for Uber.
Major OEMs (original equipment managers) such as Dell, Hewett-Packard, and Lenovo are exploring the world of subscription based services. With DaaS, these major companies will offer a monthly (or yearly) subscription service that will allow businesses to offload the responsibilities of purchasing and maintaining equipment to third party vendors. This is similar to businesses outsourcing data storage to third party cloud storage providers, such as Amazon Web Services or Office 365. These services would include distributing and managing devices as well as retiring them once they’ve reached the end of a predetermined lifespan. Set, monthly payments would provide businesses with an operational expense and eliminate the headache of working capital expenditures into a budget.
Companies that offer these services are able to take processes that normally require maintenance and effort and make them non-factors for businesses. The popularity of the recent shift to subscription-based services is intriguing and reflects of the evolution of technology and its ubiquitous nature. The state of the subscription economy is headed in different directions and it is interesting to see how this culture will be reflected in the future.
Hone Capital is the Silicon Valley-based arm of a large venture-capital and private-equity firms in China, CSC Group. In order to gain a competitive advantage, in 2015 Hone invested heavily into the development of a machine learning model to aid in investing decisions. In order to build the model they used a database of 30,000 deals from the past decade and tracked 400 different characteristics, and from that found 20 factors that were predictive of success. The insights gained from this analysis allowed the fund to identify deals they would have normally overlooked and readjust tactics to make success a more likely outcome. After the implementation of machine learning analytic models, Hone Capital’s deal success rate has risen to over twice than the industry average (average success rate was 16% Hone had a 40%). This use case demonstrates the vast value of insights gained from AI analysis and how it can be used to optimize instead of replacing business processes.
Amazon Go has been open to the public since January of 2018, and the foundation of the business is to make things simpler and quicker for the customer. While using machine learning, artificial intelligence and other technologies, the store allows the customer to go in, grab what they want, and walk out. With everything connected, from the Amazon Go App to the hundreds of cameras inside of the store, to the sensors and RFID readers, it shows how intricately related everything is. The system detects when the shopper picks up and item and adds the item to the shopper’s virtual cart.
If companies get on the Amazon Go wave, it could possibly change retail forever. It is collecting an enormous amount of information and using it to its advantage. There are other companies looking to battle Amazon, specifically Microsoft, who is developing technology for cashierless point of sale systems. If Microsoft were to create and patent this technology, they would be able to sell it to different retailers. A venture capital firm believe this market could be worth about $50 billion, so it is a matter of time before this becomes the future of retail and grocery stores.
Its interesting to think about how this store is set up behind the scenes. We learn a lot about processes and the different kind of systems a business would use, but Amazon Go is taking it to a different level. As time goes by and Amazon fixes some of the problems they might have, there can be entirely new systems coming into the market that a tech company similar to Amazon will use.
The project known as the Joint Enterprise Defense Infrastructure cloud or JEDI, is a developing project of the pentagon in which massive amounts of government data are to be moved to cloud based. The Pentagon has elected partner with US-Based companies for obvious reason. Previously, Google had put their name in to be considered but recently removed that submission.
Google has said that its main reason for leaving is because the project conflicts with its principles for ethical use of AI. Google has also stated that components of the contract are out of scope of current government certifications. Employees at the company have protested it’s involvement in yet another US government project. After backing out of “Project Maven” in which google was using AI to build military grade drones for the US military, Google has taken a step back (for now).
Where do we draw the line between government & public tech companies? There are more than a few companies working on artificial intelligence and account massive amount of data into those projects. How can we trust companies to use government information in the right way? What classifies the “right” way and what happens when unintended outcomes take a wrong turn?
In our course, we study how information technology systems are integrated and implemented into a working business or organization. I am pressing further into the discussion and moving past the development of systems. I am posing the question of ethics in a system. This problem is becoming increasingly important as we consider our personal and physical safety.
Facebook had a breach and roughly 50 million users’ information was hacked. Facebook made the public aware of the breach as soon as they discovered it. It appears that hackers “exploited a feature in Facebook’s code to gain access” (Isaac and Frenkel). Facebook being such a vital company to today’s world economy puts even more stress on this hack. The security and infrastructure should be on Facebook is world class, but breaches such as this should almost never occur with such sensitive data.
Another compounding factor that stresses Facebook’s security is this use in elections. Recent highlights such as the 2016 United States Presidential elections is commonly highlighted; supposedly Russians manipulated the platform to boost voter turn out. The aftermath of our election redirects attention to Facebook for future elections specifically in Mexico and Brazil.
The security apparatus developed within Facebook should be thoroughly evaluated to prevent future breaches; especially considering there is data on roughly 2.2 billion people. Mark Zuckerberg has stated publicly that the breach point was located and they will work to thwart future attacks.
When people think of Google as a company, they don’t always think of their social network platform Google+. However, Google+ has recently brought itself into the headlines by compromising the personal data of over a half million users from 2015 till the present. Google first learned about the incident in March as part of an audit process called “Project Strobe.” During this process, Google took a closer look at the interfaces between 3rd party applications and Google+ and found that data marked private by the user could still be accessed by the software developer. The API bug was not disclosed to the public at the time it was discovered because Google did not want to introduce more regulatory demands onto the social media industry.
In our course, we study the integration of systems into a business and how they could either be a source of cash or a tax. In the case of Google, where IT is the business itself, the integrity and controls of their IT framework must be high priority and highly sound to continue to run their business efficiently. Though when Google allows their IT framework to compromise personal information to other untrusted companies, it becomes not only a source of capital but a source of ethical responsibility. Should Google have released the bug information as soon as it was discovered to increase user confidence? Probably, but they should also make the IT process of securing data more highly weighted in their organization if they continue to profit off user engagement. Google+ has been shut down permanently because of the problem, but this solution may be too late for those with their information given up.