Posts from machine learning

I wrote last week that I have started coding again. And I have been amazed at how much easier it is now that I can code and deploy in the cloud without having to spin up anything myself.

But the other massive improvement in programming is the “AI assist.”

I am working in a Javascript library called jQuery and I don’t really understand its commands and syntax very well.

So I turned to ChatGPT last week and got back this:

That is like having every line of code commented out so you know exactly what it is doing. Once I understood what the code was doing, it was pretty simple to edit it to do something different.

GitHub also has a service called CoPilot that I have just set up so I haven’t used it yet. They call it “your AI pair programmer” which sounds like exactly what I need. I hope to get it working this week and that will help me even more.

Like all things AI, some will say that machines will replace humans in writing code. I think that could happen, but what certainly is happening is machines are making humans more productive in writing code. AND AI is allowing humans who aren’t very good at writing code to be able to do it much more easily.

The machines replacing humans narrative is powerful. But the narrative I prefer is that AI is making things available that have been expensive and unobtainable for so many. And that is not limited to programming. It is true of so many things.

I read last week that the NYC Department of Education has banned ChatGPT from its networks and devices. I understand that reaction and mentioned the issues that AI/ML create for educators in a post a few weeks ago.

I attended a dinner this past week with USV portfolio founders and one who works in education told us that ChatGPT has effectively ended the essay as a way for teachers to assess student progress. It will be easier for a student to prompt ChatGPT to write the essay than to write it themselves.

However, I would like to suggest that educators embrace these new tools rather than block them.

We are entering an era when AIs will be available to everyone to use to do work, entertain ourselves, and many other things. We cannot put this genie back in the bottle. We need to embrace it.

I think a better approach would be to require students to use ChatGPT to write an essay or at least help write an essay and then have the students compete to see who can leverage this technology to create the best essay. That would teach the students to use these tools rather than pretend they don’t exist.

I own a slide rule that my dad gave me. He used it for many years until calculators emerged. He told me when calculators first showed up, many educators wanted their students to continue to use slide rules. But eventually, they realized that calculators were better and embraced them.

I think the same thing will happen with AIs. So we might as well get busy integrating them into education instead of banning them.

The advances in AI over the last year are mind-boggling. I attended a dinner this past week with USV portfolio founders and one who works in education told us that ChatGPT has effectively ended the essay as a way for teachers to assess student progress. It will be easier for a student to prompt ChatGPT to write the essay than to write it themselves.

It is not just language models that are making huge advances. AIs can produce incredible audio and video as well. I am certain that an AI can produce a podcast or video of me saying something I did not say and would not say. I haven’t seen it yet, but it is inevitable.

So what do we do about this world we are living in where content can be created by machines and ascribed to us?

I think we will need to sign everything to signify its validity. When I say sign, I am thinking cryptographically signed, like you sign a transaction in your web3 wallet.

I post my blogs at AVC.com and also at AVC.Mirror.xyz which is a web3 blogging platform that allows me to sign my posts and store them on-chain. This is an attestation at the end of last week’s blog post.

You can see that “author address” and click on it to see that it is one of the various web3 addresses I own/control. That signifies that it was me who posted the blog. It is also stored on-chain on the Arweave blockchain so that the content exists independently of the blogging platform. That is also important to me.

I think AI and Web3 are two sides of the same coin. As machines increasingly do the work that humans used to do, we will need tools to manage our identity and our humanity. Web3 is producing those tools and some of us are already using them to write, tweet/cast, make and collect art, and do a host of other things that machines can also do. Web3 will be the human place to do these things when machines start corrupting the traditional places we do/did these things.

My friend Steve Kane suggested I take a longer view in my pair of year end posts this year:

What, no decade end/decade ahead posts? 😕

— Steven Kane (@stevenkane) December 26, 2019

And so I will.

Here are the big things that happened in tech, startups, business, and more in the decade that is ending today, in no particular order of importance.

1/ The emergence of the big four web/mobile monopolies; Apple, Google, Amazon, and Facebook. A decade ago, Google dominated search, Apple had a mega hit on their hand with the iPhone, Amazon was way ahead of everyone in e-commerce, and Facebook was emerging as the dominant social media platform. Today, these four companies own monopolies or duopolies in their core markets and are using the power of those market positions to extend their reach into tangential markets and beyond. Google continues to own a monopoly position in search in many parts of the world, has a duopoly position in mobile operating systems, and controls a number of other market leading assets (email, video, etc). Apple owns the other duopoly position in mobile operating systems. Amazon has amassed a dominant position in e-commerce in many parts of the world and has used that position to extend its reach into private label products, logistics, and cloud infrastructure. Facebook built and acquired its way into owning four of the most strategic social media properties in the world; Facebook, Instagram, Messenger, and WhatsApp. Most importantly, outside of China, these four companies own more data about what we do online and also control many of the important channels to reach us in the digital world. What society does about this situation stands as the most important issue in tech at the start of the 2020s.

2/ The massive experiment in using capital as a moat to build startups into sustainable businesses has now played out and we can call it a failure for the most part. Uber popularized this strategy and got very far with it, but sitting here at the end of the 2010s, Uber has not yet proven that it can build a profitable business, is struggling as a public company, and will need something more than capital to sustain its business. WeWork was a fast follower with this strategy and failed to get to the public markets and is undergoing a massive restructuring that will determine the fate of that business. Many other experiments with this model have failed or are failing right now. When I look back at the 2010s, I see a decade during which massive capital flowed into startups and much of it was wasted chasing the “capital as a moat” model.

3/ Machine learning finally came of age in the 2010s and is now table stakes for every tech company, large and small. Accumulating a data asset around your product and service and using sophisticated machine learning models to personalize and improve your product is not a nice to have. It is a must have. This ultimately benefits the three large cloud providers (Amazon, Google, Microsoft) who are providing much of the infrastructure to the tech industry to do this work at scale, which is how you must do it if you want to be competitive.

4/ Subscriptions became the second scaled business model for web and mobile businesses, following advertising which emerged at scale in the previous decade. Startups that developed the skills to execute a subscription business model with positive unit economics delivered fantastic returns to investors and capital flowed into this sector as a result. This was a very positive development as subscriptions better align the interests of the users and the developers of mobile and web applications and avoid many of the negative aspects of the free/ad supported business model. However, as we end the decade, a subscription overload backlash is emerging as many consumers have signed up for more subscriptions than they need and in some cases can afford.

5/ Silicon Valley’s position as mecca for tech and startups started to show signs of weakening in the 2010s, largely because of its massive successes this decade. It is incredibly expensive to live and work in the bay area and the quality of life/cost of life equation is not moving in the right direction. The physical infrastructure (transit, housing, etc) has not kept up with the needs of the region and there is no sign that it will change any time soon. This does not mean “Silicon Valley is over” but it does mean that other tech sectors will find an easier time recruiting talent to their regions and away from Silicon Valley. And talent is really the only thing that matters these days.

6/ Cryptography emerged in the 2010s as a powerful technology that can solve some of the web and mobile’s most vexing issues. Cryptography and encryption have been around for a very long time, well before the computer. Modern computer cryptography came of age in the 1970s. But the emergence of the internet, web, and mobile computing largely did not integrate many of the central ideas of cryptography natively into the protocols that these platforms were built on. The emergence of Bitcoin and decentralized money this decade has shown the way and set the stage for cryptography to be built natively into web and mobile applications and deliver control back to users. Credit to Muneeb Ali for framing this issue for me in a way that makes a lot of sense.

7/ Technology inserted itself right in the middle of society this decade. Our President wakes up and fires off dozens of tweets, possibly while still in bed. We are all hostage to our phones and the services that we rely on. Our elections are conducted using machine learning technology to segment and micro-target important voting groups. And bad actors can and do use the same technologies to interfere in our elections and our public discourse. There is no putting the genie back in the bottle in this regard, but the fact that the tech sector has such a powerful role means that it will be highly regulated by society. And there is no putting the genie back in the bottle in that regard either.

8/ The rich got richer this decade. Axios wrote in a recent email that:

“The rich in already rich countries plus an increasing number of superrich in the developing world … captured an astounding 27% of global growth.”

But the very poor also had a great decade as Axios also reported:

The rate of extreme poverty around the world was cut in half over the past decade (15.7% in 2010 to 7.7% now), and all but eradicated in China.

The losers in the 2010s were lower middle class and middle class people in the developed world whose incomes stagnated or fell.

Technology played a role in all of this. Many of the superrich obtained their wealth through technology business interests. Some of the eradication of extreme poverty is the result of technology as well. And the stagnation of earning power in the lower and middle class is absolutely the result of technology automation, a trend that will only accelerate in coming years.

9/ This a post publish addition. A huge miss in my original post is the emergence of China as a tech superpower and a global superpower. There are many areas (digital money for example) where China is light years ahead of the western world in technology and that will likely accelerate in the coming years. Being a tech superpower is a necessary condition to being a global superpower and China is already that and getting more powerful by the day.

I will end there. These are the big mega-trends I think about when I think about the 2010s. There is no doubt that I left out many important ones. You can and will add them in the comments (wordpress for now), emails to me, and on Twitter and beyond. And that is what I hope you will do.

My friend Fraser took a large number of AVC blog posts over the years and trained an AI model on them.

The result is a blog written by a machine.

You can see it here.

One one hand, it is kind of amazing that you can train a machine to write like someone.

On the other hand, I don’t think I will be out of a job anytime soon.

If you are in or around the Brooklyn Navy Yard and want to get to the East River Ferry, you can have a self driving car take you there.

I did that yesterday:

It’s sort of like a van. There are six passenger seats in the vehicle rand I saw four of them lined up waiting for passengers next to the main gate off Flushing and Cumberland.

There is a driver in the front seat but the van drives itself. That takes some of the excitement factor down a notch. But it increases the comfort factor. I assume the driver can take control of the vehicle and drive it manually if necessary.

It makes a ton of sense that autonomous vehicles would start out in places like the Navy Yard where there is not a lot of vehicle traffic and the map is fairly simple.

If you want a taste of the future go over to the Navy Yard and get a ride. It’s free.

And while you are there check out the amazing new Dock 72 building next to the East River Ferry stop. They are leasing it up now and there are some great office spaces still available there. They have smaller offices for startups. Link here.

This is a talk my partner Albert gave at an AI conference in Berlin last month. Although he gave it to an AI conference, it is really about where we are in our society and what we need to do about it. It is about 20mins long.

I would like to start this post with a disclosure. USV portfolio company Clarifai has one of the best facial recognition models on the market and is very active in the facial recognition market. Now that I have disclosed that, we can move on.

Facial recognition has come of age. Machines can figure out who we are and more.

One of the most popular booths with students at The Annual CS Fair this year was the Microsoft booth where they were showing some of their facial recognition technology.

The delight and amazement on the students’ faces was infectious.

But of course, not everyone is excited about facial recognition technology being deployed in the market.

woooooow pic.twitter.com/qWvGQeSjLb

— Laurie Charles (@TheStuffOfMemes) April 20, 2019

I particularly like that question in the embedded image in that tweet:

How does Jet Blue know what I look like?

The answer turns out that there are many ways to know what we look like and you can start with the federal government and go from there.

Like all technologies, facial recognition can be used for good and bad. And it will be.

I like what my partner Albert wrote on this topic recently:

And then some things are incredibly hard. Such as face and object recognition. There are tons of amazing positive applications for such technology. And yet they could also be used to bring about a dystopian future of autonomous killer weapons chasing citizens in the streets. Does that mean we should not develop these capabilities? Should we restrict who has access to them? Is it OK for corporations to have them but not the military? What about the police? What about citizens themselves? Those are hard questions and anyone who thinks they have obvious answers I submit hasn’t thought long enough about them.
So what is to be done? A good start is personal responsibility. 

We used to have to stop at toll booths and wait in long lines to get across bridges and tunnels. Now we drive past the tolls at 60mph and the machines detect our license plates and debit our accounts.

The same is going to happen with our faces and that will be great for many things. But, of course, it will also freak us out on a regular basis and add to the “technology is turning everything into a surveillance state” narrative that has more truth than we would like to admit.

So what is my point? Well for one, the technology is here and we had better get used to finding it deployed in the wild. And second, that it will bring a lot of good. So we should not over react. But we should be mindful of the downsides and those of us who are working on this technology, those of us who are financing the development of it, and those of us who are deploying it, need to take great care with it.

Earlier this week, Kara Swisher interviewed Kate Crawford and Meredith Whittaker, who run NYU’s AI Now Institute.

It is an interesting and thought provoking discussion. I don’t personally love Kate and Meredith’s answers on how society should be thinking about these issues. They feel very “20th century” to me.

But regardless of what you think about their particular take on the issues, I do think we all ought to be paying a lot of attention to AI and its impact on and role in our society. It is important.