The federal Communication Commission is looking to auction US licenses that will allow 5G services. 5G will allow speeds to be about 100 times faster than the current cellular speeds we experience now. There are a few more benefits as well. It can increase the responsiveness and allow more people being on the same network without any delay or lagging. Having less delay and response time can help other technology improve dramatically such as VR, drones, self driving vehicles, and social media apps. Self Driving vehicles can allow accelerated information such as finding out the location and speeds more effectively. VR devices would be able to display a much more advanced experience that consumers would enjoy. Social media apps, such as Facebook Live would be able to have more clear live videos of everyone. Drones are similar to the self driving vehicles that would give us more data and footage needed. 5G is coming soon and will impact all of our lives dramatically. What features are you looking for most that will be impacted by 5G networks?
Lockheed Martin, the world’s largest defense contractor, has steadily been targeted with cyber attacks by malevolent parties (particularly nation-state actors from Russia, China, and North Korea) since 2003. As an enterprise that “interacts with the internet 20 billion times a day” in carrying out its roughly 8,500 programs, there is vast opportunity for attackers to exploit weaknesses in Lockheed Martin’s systems and extract classified information. In an effort to combat these threats, the company has combined its intelligence function with its ability to track big data and invested in creating its Threat Intelligence Platform (TIP) called “Palisade”: a “centralized platform” which integrates their Security Information & Event Management (SIEM) systems “to provide enterprise wide alerting capability and manage all threat
intelligence.” Palisade is aligned with Lockheed’s trademarked “Cyber Kill Chain” framework of threat analysis; this framework applies the military terminology of “kill chain” – an outline of all events from reconnaissance activities to battle damage assessments that need to take place in order to execute a mission – to the analysis of attempted cyber attacks.
Understanding that cyber attacks are constantly evolving to better breach targeted entities, Lockheed Martin reasons that the “seven distinct steps” to a cyber attack’s kill chain are an excellent way to determine patterns in attacks and mitigate future ones. This is because adversaries, while likely aware of the need to change their techniques, are unlikely to change all seven of these techniques at once simply due to time/cost constraints. What this means is that even minor elements of past attacks, such as “a scrap of code”, can be tracked and stored into a database that Palisade can then assess in terms of the Cyber Kill Chain framework. Lockheed’s intent here is for Palisade to improve its overall network defense posture, incorporate big data into cyber security (a field that is still largely reliant on human driven analysis), empower analysts with a more comprehensive view of threats using historical data, and identify and respond to threats in a proactive, rather than reactive, manner.
I find this incredibly intriguing as it is the combination of my top two professional interests: big data and intelligence analysis. This initiative certainly innovates the company’s cyber security operations, placing less of a burden on analysts and providing new tools for Lockheed’s defense teams, but I have concerns about its efficacy. What happens if the platform inappropriately raises a red flag on an interaction between internal and external actors because it matched one element of that interaction to a previous attack’s kill chain? What happens when an attack is attempted and Lockheed’s framework fails to identify that breach because of Palisade’s algorithm? Obviously the need for human-level analysis is still very much needed even with this platform, so how much business value is Lockheed Martin actually enjoying from this development? Could this platform be marketed to outside clients to transform Palisade from being a cost center to a profit center? If they could market it as a solution, what impact would it have on the project’s Net Present Value – negative or positive? There is much to consider here for the company, but this development of “Intelligence Driven” cyber security is nonetheless thought-provoking and offers new potential to organizations in protecting their information.
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.