My daughter is particular about manners. If you don’t say please or thank you when you’re supposed, it’s a serious problem. This is starting to extend to the Alexa device she uses to listen to audiobooks. She says please and thank you after the device follows her instructions. Numerous times she has corrected me for not using similar pleasantries.
The world in which my daughter and children her age are growing up in is full or artificial intelligence. Communicating with a smart device, recommended searches, GPS directions, and more capabilities we have involving artificial intelligence are normal parts of life for them.
So, how do we ensure our children have an awareness of artificial intelligence rather than thinking Alexa just automagically talks to them?
I recently ran across the AI for K-12 Initiative, an effort to map out a curriculum for primary and secondary school-age children to learn about artificial intelligence. The site has a ton of resources that I think will be helpful for parents and educators to take a look through.
Imagining the world my daughter will be living in 30 years from now is pretty overwhelming at times. Resources like this help me do what I can now to help ensure she’s at the table shaping that future. I’d love for your kids to be at that table as well.
I’m working through The Quest for Artificial Intelligence by the late Nils Nilsson, a pioneer in the development of the field. He charts out the foundation for artificial intelligence beginning with Aristotle’s syllogisms and makes his way through various European mathematicians who made various contributions to mechanizing logic.
A couple of years ago, Chris Dixon, a venture capitalist at Andreessen Horowitz, wrote a piece on how Aristotle laid the foundation for the creation of the computer. Is that the whole story? I think there’s more to it than that. I tweeted about this early last year.
It’s critical that black folks and other groups currently underrepresented in the development of artificial intelligence carve out a space for ourselves. I wrote a bit about why here.
Perhaps a good example of the impact carving out a space can have is in the news that Robert Smith committed to pay off the loans for the entire 2019 class of Morehouse graduates.
Smith has built Vista Equity Partners into a machine of a private equity firm that has outpaced its competitors investing in enterprise software businesses by executing a precise operations playbook in each of its portfolio companies before flipping them for real nice returns. Pitchbook estimates that as of 2017, Vista’s internal rate of return has averaged 22%. Compare that an industry average of nearly 10%, according to AQR Capital Management research. Smith has done quite nicely for himself as a result, generating the resources to be able to clean up $40 million in debt.
A key engine behind the playbook Vista Equity Partners deploys across its portfolio companies is Vista Intelligence Group. The group uses artificial intelligence to scan data across Vista’s portfolio companies to surface opportunities and stand up new businesses around them. In a fireside chat at Goldman Sachs, Smith talked about how Vista is navigating the fourth industrial revolution by trying to get the firm to a leadership position in the various ecosystems it invests in rather than just placing capital in particular narrow verticals. I venture that Vista Intelligence Group is the lever they’re turning to make that happen. Artificial intelligence is the magic sauce. Here’s that fireside chat.
Imagine it’s true that artificial intelligence is the new electricity as Andrew Ng claims. Now consider that Robert Smith has leveraged AI to generate $4.47B worth of resources personally while managing $46B. Imagine the possibilities of some of the 2019 Morehouse graduates going on to tap into their genius and reimagine AI and how it will shape the global economy.
What do these graduates need to tap into their genius? The lightened financial burden courtesy of Mr. Smith definitely helps. Another component is these graduates seeing beyond the narrative that the arc of technological development cuts through Europe. I’ve written about this narrative issue here. While Aristotle was developing syllogisms, equally brilliant philosophers and mathematicians were working on their own ideas across Africa. Drawing confidence and inspiration from that kind of foundation makes these graduates unstoppable in my mind and positioned to reshape the trajectory of this world.
TikTok Is the New Music Kingmaker, and Labels Want to Get Paid (Bloomberg)
I wonder what it is about the music industry that has it looking at itself on the wrong side of a deal once again. Decades ago, Napster and file sharing put a massive dent in the industry, then Apple came along and dictated the price it was going to pay for music. Now, it finds itself trying to figure out how to get value out of the virality that TikTok is driving among artists.
What’s more interesting to me is the engine behind TikTok. The app is one of the products of Bytedance, the most valuable startup in the world at $75B. Bytedance owns a number of mobile-first products that are all powered by machine learning. There’s a news app Toutiao that is powered by artificial intelligence technology that can write 400 words in a couple seconds. There are 140 million monthly users spending around an hour a day on that app in China. Incredible.
I wonder what the quality is of the news the app is developing. To what extent is Bytedance in coordination with the Chinese government? What sort of unintended insights is the company getting as a result of having its finger on the pulse of people’s music and news consumption? How much more room for growth is there in its valuation before it goes public?
Breaking down Alibaba’s global ambitions (Digiday)
I’m yet to buy anything through Alibaba, but it seems like those days are more and more numbered as the company expands its footprint globally. The amount of handholding that its various subsidiaries engage in to ensure the success of brands is pretty remarkable.
The Fundraising Environment in 2019 – Three Major Shifts (Tomasz Tunguz)
Tom Tonguz argues that the fundraising environment for startups is very sophisticated in three ways – the types of funding founders can pursue, the sophistication of the pricing, and the speed with which money can be raised.
I agree with his takes on the first and third point, but wonder whether the pricing is really all that sophisticated. Investors are using enterprise value to forward revenue to value companies. Are startups hitting their forward revenue targets? If they aren’t, what adjustments are investors making to their valuations? How are late stage investors remaining disciplined in the face of Softbank dropping $1B in a startup’s bank account?
Ozwald Boateng put on an incredible fashion show today at the Apollo Theatre. I loved that he called the show AI for artistic intelligence. Africa flows through his designs and the combination with the title struck me as a strong statement of the confidence with which black folks must carve out our role in shaping the future.
Boateng’s designs were full of complex simplicity and boldness – two characteristics that I believe are core to black design – chicken and waffles, kente cloth, and hip hop sampling are just a few examples. We can bring the same design ethos to the shaping of artificial intelligence. I’m sure in a lot of ways we already are.
Kunle Olukotun through his development of Afara Websystems, changed the game for server rooms back in the late 1990s and early 2000s, increasing their ability to avoid power outages. Over the past couple years, he has been building a new company developing a platform on which artificial intelligence applications can run.
The thing that bothers me about this example is that the intellectual property Olukotun and his team is developing is in the U.S. The use of mobile phones across Africa is still pointed to as the primary example of leapfrogging. I think the next wave of leapfrogging has to take place at a foundational level – African countries figuring out how to remix how commercialization of advanced research takes place.
In order to accomplish this, what education looks like across Africa needs to be a primary focus. How do we make sure students are getting all the exposure and resources they need to maximize their curiosity from elementary school through college and that there are resources that can support them even if they do decide to study at a Stanford, CalTech or Harvard. How do we create an environment where an incredible researcher like Olukotun feels like he could be really productive in Nigeria. Even if it doesn’t make sense to conduct research on the continent, researchers should be confident they can look to countries across Africa for support.
My thinking here is still pretty rough and I’m writing this with very sleepy eyes. I’d love to engage with folks who have a point of view on this.
What do you think is key to Africa participating in the development of artificial intelligence?
This is a fascinating conversation between Fei Fei Li, a computer science professor at Stanford and co-director of their new Human Centered AI Institute, and Yuval Noah Hariri, a historian and author of the widely popular book Sapiens. The two have a respectful go at one another on what the future looks in an AI world.
Machine learning is much better at doing certain things than people, just as a dog is much better at finding drugs than people, but you wouldn’t convict someone on a dog’s evidence. And dogs are much more intelligent than any machine learning.
The problem with this statement is that we have convicted people on a dog’s evidence and later found that evidence to be faulty.
Outside of this issue, Benedict Evans provides a simple definition of artificial intelligence bias, scenarios of the potential bad effects of AI bias, and how we can mitigate those effects. Evans’ central point is a good one to keep in mind:
ML finds patterns in data – what patterns depends on the data, and the data is up to us, and what we do with it is up to us.
This is an interesting partnership probably arising from both startups being Y-Combinator alums. Paystack has gotten quite a lot of traction in Nigeria providing a payment platform similar to Stripe. Lambda provides software development training free of charge until folks get a job making at least $50k. After this, they’ll have to pay 17% of their salary for tuition over two years.
I’ve seen a lot of VCs pointing to Lambda as the chosen one to lead us into a new model for education based on this model. First – their not the only education business doing this, African Leadership University uses a similar model. Second, I worry that folks could still find themselves stuck with collectors hands in their pockets. I’d be curious to see what the income threshold will be for this Paystack partnership.
Russia’s State Atomic Energy Corporation has been aggressive about pushing nuclear development across Africa. Over the past five years, the company has been at various stages of talks with South Africa, Kenya, Zambia, and Ethiopia. It’ll be at least a decade before we see how all this plays out but it’s quite interesting.