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 Alan Turing and the Turing Test

Alan Turing was a British computer scientist, among other roles, who made great strides in the field of artificial intelligence in the 1930s, 40s, and 50s. He published “On Computable Numbers, with an Application to the Entscheidungsproblem,” which dealt with decision methods, and developed the Church-Turing thesis, essentially stating that all human computation can be achieved by the Turing machine, or a model of a machine which could perform computations on an infinitely long tape. For our purposes, this is interesting because it outlines the limits of human computation. This comes into play in the Turing Test, which then determines whether a computer can think like a human, or exhibit artificial intelligence, under certain conditions. This test consists of three terminals, one operated by a computer respondent, one operated by a human respondent, and one operated by a human questioner. The human questioner, after completing a set of questions on a specific topic, must decide which respondent is human and which is the computer. A computer has passed the test if they are indistinguishable from a human, demonstrating that the computer possesses artificial intelligence. While this test has fallen out of favor as computer science has advanced, this was an incredible advent when it was published in 1950. We can use this framework to conceptualize today’s technology, as one can describe Microsoft Excel as a Turing machine, or imagine that Chat GPT might pass a Turing Test.

Network Effects and Examples

I was instantly drawn to this question because finding a network effect, in the VC world, is classically regarded as the first step to finding a “unicorn,” or billion-dollar company. Network effects, speaking simply, is the effect of growing user bases generating value specifically because they are growing. Facebook is probably the most ubiquitous example of this effect. Facebook only became valuable because the number of members kept growing. New users were encouraged to join to access their friends on the website, but were no one on Facebook, no one would want to join. Therefore, as more friends joined, the value proposition was even stronger, because users could interact with growing numbers of people. This effect allowed Facebook to blossom into a social media giant. Many businesses seek to generate a network effect, but it is easiest to achieve in the software and tech space, in my opinion. For example, there are few opportunities for network effects in the consumer space. If I buy Pepsi, for example, your decision to buy Pepsi is not influenced. I have not generated more value to you from my purchase. Network effects allow exponential growth for a business, but, as illustrated above, are difficult to come by. Network effects generate value not only in terms of revenue and profit, but a stronger value proposition, which is the core of the exponential growth that they enable.

Descriptive vs. Predictive Analytics

Generally, data analysis can be seen as the process of asking and answering complex questions to better understand data sets. This process can be useful in business, as it allows greater insights into the operations of the business, especially in analyzing trends and effectiveness of initiatives. Descriptive analytics, specifically, allows a business to see outcomes of events, and visualize trends in data. Descriptive analytics works well for the present or past time frame. One example from Google Analytics of descriptive analytics is data regarding the number of sessions per user on a website in a given month. Predictive analytics, on the other hand, refers to data which can be used to make predictions about what may happen in the future. Predictive analytics work in tandem with descriptive analytics, which form a basis for these predictions. One example of predictive analytics would be an inference of how many sessions per user a website might experience in the next month based on previous months’ data. As seen in the picture above, the four levels of analytics work together as they increase in complexity. While one could employ descriptive analytics without predictive analytics, the reverse would not be true.

Who uses CRMs?

One thing that makes Customer Relationship Management software, or a CRM, so ubiquitous, is precisely because of their wide range of applications. A CRM is an invaluable resource for any business, big or small, to help automate sales, marketing, billing, and customer outreach. CRMs help speed up tedious processes, thus generating efficiencies and aiding in company-wide growth. Specific core functions which might spend the most time with a CRM are those who work in sales and marketing, but the platforms are designed such that anyone from an intern to a C-level operator can check in and monitor company sales and growth. I could envision myself using such software in my future roles as a VC, reaching out to founders and LPs, tracking our communications, and visualizing where each of our interactions left off. For anyone using a CRM, one key advantage is to be able to visualize and synthesize large amounts of data, especially in communications, which are typically not clear-cut or easy to understand. Large firms that have many employees running outreach operations would benefit from the birds-eye view that CRMs can provide of marketing and sales operations, while small startups would appreciate the addition of efficiency and clarity that CRMs provide.

Your digital identity is a representation of yourself that is portrayed online. This information is readily available to the public with the use of online resources. Your digital Identity allows you to create a professional online reputation and that is why it is very important to make sure that what you post stays professional. Future employers or business partners have access to your digital identity and may take that as their first impression of you. You want this first impression to be taken seriously and looked at professionally. That is why you want to avoid sharing any sort of inappropriate content including photos and private information on any online platform that is connected to your name. You really only want to share what you believe positively adds to your digital identity. When it comes to managing your digital identity, you must keep updating/editing your profiles. While you are adding to your digital identity you want to keep in mind to stay consistent with the information you are adding. You have to make sure people know it is you and that you portray the same person across all online platforms. It is also very important to tune in to who your audience is or who you want your audience to be. I believe that the greatest impact one has to their digital identity is making sure they are setting a barrier between their personal life and their professional life and understanding what they feel benefits them from both categories. Growing up in a world with rapidly evolving technology meant we had to be careful with what we posted online as it does not ever fully disappear and could impact us later on. Many role models in my life did a great job of reminding me of that, that I needed to watch what I posted on the internet and also what was posted about me.  

An e-portfolio is the profile that comes up with any google search tied to your name. This platform states contact information, educational background along with your work history. These portfolios should include professional information about yourself and include a profile photoso that your photo can be placed to a name. Again, this platform is strictly to benefit you in the professional realm and allows other professionals to gain some information about you, without having to contact you directly.