Students: Get an internship in Open Source with GitHub Octernships

Hello students! If you are looking for a paid internship and mentorship by industry experts, GitHub has recently announced the Octernships program which gives you the opportunity to contribute to real world open-source projects all while getting paid and mentored. The program is initially starting for students in 10 countries, including India, Singapore, Indonesia, Malaysia, Vietnam, Philippines, Thailand, Mexico, Nigeria, and Colombia, and will gradually expand to more regions over time. In the coming months, the team will be scaling, expanding, and launching new programming to further DEI within open source communities.

Check out these resources to learn more about the programs, and some tips to apply.

– Video by GitHub:
– Video by Kunal Bhaia:
– Blog post by GitHub:
– Link to GitHub Octernships:
– Learn more about GitHub’s social impact programs and how we’re skilling for the future here:

Industry: Media & Entertainment

Microsoft | Africa’s Media and Entertainment Industry

Moderating the Media and Entertainment industry discussion at Microsoft with Audu Maikori, Executive Vice Chairman of Chocolate City Group has been a highlight of my career. Maikori is a visionary and industry leader behind one of the largest entertainment companies in Africa. The impact and reach of the event exceeded expectations, with much positive feedback.


US20200134878A1: Multimodal data visualization using bandwidth profiles and optional environmental compensation. United States.

I am pretty excited about hitting this milestone: a published patent application with IBM, where I have had the privilege of building a career and being part of an amazing community. The invention is a multimodal data visualization technology that will adjust in real time to fit the needs of individuals with varying levels of sensory acuity: #Accessibility #Technology #Inventor #Data #DataVisualization #Enugu #Firsts.

Should your business be on blockchain?

It depends.

Blockchain has evolved from the concept of a platform for trading cryptocurrencies to one that exchanges all kinds of digital assets, from flowers and luxury goods to medical records and supply chain documents (smart contracts). When considering adopting a private blockchain model for your business transactions, you should ask yourself these four questions:

What are my transactions?

A first step is identifying the assets that you will be exchanging on a blockchain network. A transaction is simply an exchange, trade or transfer of an asset, a digital one in this case, between two or more parties. If your asset will change hands, then you will need to keep a chain of records documenting the activities of the exchange. This is the essence of a blockchain, to manage and secure digital transactions as part of an open, transparent and decentralized system of record. And don’t worry, your blockchain data is confidential and private.

A blockchain is a shared ledger of key-value hash chains, representing transactions, that is distributed amongst approved parties. It records data from member transactions and updates the ledger securely and efficiently, in a way that is both verifiable and permanent. This system of record is publicly visible to each approved member of the network, and when written to blockchain, each new transaction record is linked to the record before it, making the system auditable and immutable, the latter meaning it cannot be altered, as long as the encryption on the blockchain remains intact. Computational algorithms and approaches are deployed to guarantee that the transaction recording on the database is permanent, chronologically ordered, and available to all members of the network.

Will I leverage network effect?

A network effect is the effect, described in economics and business, that one user of a good or service has on the value of that good or service to others. When a network effect is present, the value of a good or service is dependent on the number of others using it.[1] A greater number of users increases the value to each.

The strength of a blockchain network is in its numbers, and this is where the concept of consensus comes in. In his lucid blogpost for Evergreen, @EricJorgenson explains the nuances between virality, network effects, and economies of scale. The network of users acts as a consensus mechanism. Having more users or nodes on the network generally means more distributed operators will review and agree on all addenda before the data is permanently committed to the blockchain. This means that each member is creating the same shared system of record simultaneously. Because the database is distributed, each party has access to the entire database and its complete history, making data manipulation very difficult, if not near impossible. This also eliminated the potential of having Single Points of Failure (SPOF) in any one part of the system, leading to a more robust system overall than a traditional centralized database could offer.

Can I pool resources?

For the purpose of pooling resources to achieve a common goal, business networks can come together to form a consortium that benefits from sharing reference data. A consortium blockchain platform is essentially a private blockchain model that will allow its members to retain privacy and control, while reducing their transaction speed and cost. This model might be appealing to parties spread across industrial, geographical or regulatory boundaries.

Each member of a consortium blockchain platform plays a different role in meeting their common goal, with a visionary who will be responsible for leading the pack. Hyperledger Fabric, for example, obviates the need for having a visionary to build the code, therefore a potential barrier to easy adoption.

What is the business use case?

Beyond building a minimum viable product that will be deployed on the blockchain, what is the overarching vision?

  1. Faster payment settlements – no reliance on centralized servers to do all of the work.
  2. Increased security – virtually impossible to reproduce (or tamper with) the entire blockchain, and to get member nodes to accept the hijacked version.
  3. More open and transparent – with permission, members are able to view the entire history of transactions, increasing auditability and general trust amongst participants.
  4. Lower cost – expensive infrastructure of transaction processing, reviews and approvals by intermediaries is eliminated.

In summary, businesses today should be on blockchain, but not all businesses qualify. Blockchains are well-suited for certain functions, while for others, they are not.



[1] – Network effect (n.d). In Wikipedia. Retrieved November 5, 2017, from


Curated list of blockchain services and exchanges – Imbaniac, Github


New York State: Tomorrow Starts Today (#MamaWeMadeIt)

This month, I am featured in a series of TV commercials for the New York state, themed Tomorrow Starts Today. The commercials are currently airing on prime time TV nationwide (United States and Canada).


See more on Youtube:

New York State: Rust Belt to Brain Belt
“Millennials are heading to Upstate New York for rapidly expanding job markets in fields like technology, engineering, and even gaming.”

New York State The Millennial Effect
“Millennials are reshaping Upstate New York by creating vibrant communities full of diverse restaurants and nightlife.”

New York State:  The New American Dream
“New York is evolving into a hub for Millennials to chase the new American Dream with an array of career opportunities and a high quality of life.”

LinkedIn Analytics: Another Person You May Know

This past Labor Day, my college friend was in town for a month and had invited me to hang out with friends over grilled food and games. It was a a good time. I got to meet new people, enjoy their company and all of us – guests and the host couple – ended up having a blast. A couple days later, I logged into LinkedIn (via web), and a picture of the host popped up in the bottom right corner of the webpage as Another Person You May Know.

I was curious. Certainly, there’s a lot to keep up with as a ton of changes have occurred over time in LinkedIn’s algorithms which when I joined, categorized and recommended potential contacts based on existing network, work and school history. linkpinHowever, this was not the case. The host and I had had this one mutual friend whom we had both been on and offline friends with for years, and I wanted to figure out what suddenly roused this latent connection that resulted in a social recommendation. So I started to mentally retrace my steps:

  • My friend Peter mentions he has a friend he wants me to meet, Joyce. While he’s talking about the impressive work that Joyce has been involved with, I google her name on my phone’s browser. Cookies, page browsing tracking.

This setting was automatically set to Yes by default.

  • Couple hours later, Joyce and her husband show up to pick Peter from my place, and right there and then, all four of us are at the same location. Our phones which have IP addresses are oozing geo-spatial data. The three go off to spend some time together, and later return to drop Peter off at mine. Again, another geo-spatial count.
  • This time around, we talk for a bit and Joyce and I exchange numbers before they leave. Phone numbers/Contacts. By the way, I don’t have my contacts synced to my LinkedIn account. Maybe she does, I didn’t ask. A couple days to the party, we trade texts and a phone call.

    What my default Data privacy settings look like


  • Peter posts a picture on Instagram, tags me in it and Joyce leaves a comment. I check her profile, ‘like’ some of her pictures and follow her. She does the same. Social media data.
  • Finally it’s party time! I visit her home, sharing geo-spatial data again. And a couple days later, she’s in my LinkedIn feed.


Without knowing whether or how heavily involved LinkedIn is with using a 360 view of its users, my best bet is to solve by elimination. I check the default privacy settings on their site and it appears the glaring culprit is the phone number (exchange). I reckon if it were geo-spatial data, Joyce’s husband’s profile (that’s if he has one) would also pop up in my feed, since I had met both her and her husband at the same time and place. However, I only exchanged numbers with her. The same goes for the interaction on Instagram. Plus the next time we would all regroup at the party, there were more people – none of which have popped up in my feed. At least not yet. There was no number swapping (or Instagram following), but then again, what if they do not have LinkedIn accounts?

It gets more interesting to break this up into chunks and identify the underlying technologies that enable this interaction.