Think tanks and block chains

June 30th, 2014

Anil Dash:

I teamed up with Kevin McCoy to create monegraph. It’s a system that uses the block chain technology which underpins Bitcoin, but puts it to work in service of artists, so that they can verify that a digital work is an original, with a verifiable provenance. I describe the context of the work in A Bitcoin for Digital Art, my first piece for Medium’s “The Message” collection, and we also showed it off with a demo at the most improbable of venues, TechCrunch‘s Disrupt conference. The response overall has been great, as you can tell from the monegraph tumblr.

This is exciting, an eye-opener, and the type of work you’d expect FAT to produce. Nevertheless, it is clear now that the block chain concept can be put to use onto diverse domains and redefine them.

From Anil’s post I also found out about Data & Society; an NYC-based think/do tank focused on social, cultural, and ethical issues arising from data-centric technological development. Data & Society also contributed to The White House’s Big Data and Privacy Working Group’s review.

Snapchat’s future

June 18th, 2014

Our most basic need right after survival and concurrently a key quality of the human condition is the need to connect and communicate. I’m an avid Snapchat user for almost a year now and sold thenceforth on its ephemeral premise. A friend from the States dragged me into it long before it went huge in Europe as well1 — a great idea in retrospect, since it eliminated a lot of communication friction, both formal and informal. It connects.

Snapchat’s “[…] pure sharing, the ‘lowest-commitment form of communication.’”.

I’m also a Casey Neistat fan. And today Casey posted this:

Casey Neistat x Snapchat

I followed suit and within seconds I was watching random segments from Casey’s Cannes trip for the Lions. This experience was new; unique; social (despite being “one way;”) direct; creative; raw.

Since Neistat doesn’t have me in his contacts (read: “follow”) it reminded me of Twitter; everybody can follow you but you choose whom you’ll follow. Only this time it isn’t about fragments of one’s life set apart by brevity and 140 characters (sometimes) rather than visuals — photos and video.

A new way to connect with people by living the latest highlights of their lives as if you were there; not reading about them or have them stored in your messages feed forever. You don’t need this anymore. “This is me, this is what I do now, pay attention by not paying attention and connect with me.”

My argument regarding Snapchat’s future, though, is not related with the consumer facet of this feature. It’s about Snapchat’s business. Bubble or not there’s a rich background to Snapchat both in and of itself as a new medium and as a startup.

This novel new way of sharing and most importantly connecting whether it’s friends with friends or fans with artists — provided being executed well — can drive extraordinary growth for the service with much higher engagement ROIs and better KPIs overall. The Stories feature did exist for some months but only now does Snapchat start to capitalize it. Its upgrade, “Our Story,” is an even better opportunity for big brands, artists, celebrities, et al. $3 billion isn’t crazy anymore.

In the meantime, Kanye West shared some relevant thoughts about branding, design, and communication at the Lions. “People ask, where’s our future? Where’s our flying cars? That is the world that’s floating above us right now.” That’s the Internet and that’s what it’s all about: connecting us.

Update: Hate to say it but: I told you so.

Update 2: Told you so.


  1. Ephemeral hipster. 

On which a computer passes the Turing Test for the first time

June 9th, 2014

Yesterday, a computer simulating a 13-year-old boy named Eugene passed the Turing Test at an event organized by University of Reading at London’s Royal Society. This is a huge and remarkable breakthrough in the AI front.

The Turing Test is a test of a machine’s ability to exhibit intelligent behaviour equivalent to, or indistinguishable from, that of a human. It is, essentially, a conversation between three parties—Player A (human,) Player B (machine,) and Player C (human)—which are separated from one another. If the judge (Player A) cannot reliably tell the machine (more than 30% of the time) from the human, the machine is said to have passed the test. Until yesterday it had never been achieved. The Turing Test doesn’t check the correctness of the answers, rather how closely the answer resembles typical human ones.

Quoting Alan Turing:

I believe that in about fifty years’ time it will be possible, to programme [sic] computers, with a storage capacity of about 109, to make them play the imitation game so well that an average interrogator will not have more than 70 per cent chance of making the right identification after five minutes of questioning.

Yesterday also marked 60 years since Turing’s death.

This marks a very important step forward for the AI (and the general Computer Science) community. We’ve made—for the first time—a machine that is capable of being so smart and fluent with human language and cognition, one can’t tell it’s not a human. Such an event paves the road for superintelligent machines, better NLP, artificial neural networks, along with better answers to philosophical questions such as “can a machine have a mind, consciousness and mental states?,” “can a machine have emotions?,” and “can a machine be self-aware?”1

 The rabbit hole goes deeper

The philosophy of artificial intelligence is a broad field and currently one of the most intellectually stimulating ones. Intelligent machines are closely related to questions about the deterministic nature of our universe; if it’s completely describable programmatically or even a simulation, if there are multiple (perhaps infinite; containing all logical possibilities) other universes (or universe simulations), if the simulation is written by another species or a sapient machine or if it’s a simulation within another simulation.

Some (like Price and Hamilton) argue that humans are self-replicating machines themselves. I briefly touched this topic at the end of my Google Glass review last year:

In 1967 George R. Price went to London after reading Hamilton’s little known papers about the selfish gene theory and discovering that he was already familiar with the equations; that they were the equations of computers. He was able to show that the equations explained murder, warfare, suicide, goodness, spite, since these behaviors could help the genes. John Von Neumann, after all, had invented self-reproducing machines, but Price was able to show that the self-reproducing machines were already in existence, that humans were the machines.

Juergen Schmidhuber famously said at his TEDx talk (which I can’t stress properly how much of a “must-see” it is; arguing about this universe and our own lives being just by-products of a very simple and fast program computing all logically possible universes) that “to the man with a computer, everything looks computable.”

Now, if our reality is indeed deterministic, then it’s also completely describable (and thus, predictable) by a computer. Hence, a superintelligent computer will have much more executive and cognitive power over this very domain. Moreover in this case it’s also easier to describe the world itself to this machine. Once I argued that, perhaps, “if our universe were to be a computer simulation then Deterministic Finite Automata would be to it what particles are to physics models” but my friend Panagiotis counter-argued my hypothesis with an even better, interesting, and in our case, extremely relevant to the Turing Test, one:

That’s very interesting topic and I keep thinking about it constantly.

Let me first give you a proof why particles are not the equivalent to DFAs. Your computer is the equivalent of a turing machine and it’s built by particles. So assuming particles are equivalent to DFAs, a model emerged from a DFA can’t be more powerful than a DFA. But, by definition Turing Machines are more powerful than DFAs, thus particles can’t be equivalent to DFAs.

What is more, a human beeing might be more like a turing machine. That comes from the fact that DNA/RNA itself seem to be a turing machine and models emerging from it can’t be more powerfull than a turing machine. Thus, a brain probably is equivalent to a turing machine, capable of running other turing machines as well.

So, here comes my point. Given that the brain is a turing machine, that means it can be simulated and for me that means that also the perception or the “soul” can be simulated as well. Free will is just a perception. For me and you, there will always be a machine that can simulate us. Laplace in a similar fashion introduced the thought experiment of a demon being able to predict the future given it has full knowledge of the current state. Determinism comes from the fact that someone knows the exact current state. Let me give you another example. For a computer there is no random thing. It can always know what’s the next number so for a computer there is only determinism. However, for the human perception, which might not have access to the current internal state of it, does this actually matter? Will you feel less lucky if you win the lottery from numbers generated by a computer?

I believe having full knowledge is impossible and thus determinism is well hidden under this constraint. In game theory that’s the equivalent of incomplete information. Thus, the free will is just ability of organisms to create strategies to cope with that incomplete information. Determinism doesn’t contradict free. It just emerges from our limited capacity of predicting the future.

Let’s not forget that a deterministic universe means that we lose our free will. As Panagiotis said above “Free will is just a perception.” Don Knuth said also something apt to me last year when I asked him about a related topic:

[…] and if our universe is a computer simulation, which means we’re simply mathematical representations and everything is deterministic and, as a result, we lose our free will, then there’s nothing we can do about it and we cannot answer it, thus we shouldn’t bother thinking about it.

It is obvious now that the Turing Test is relevant not only to abstract sapient-or-not machines for “conversation games” but also to physical and biological systems like the DNA. The implications of computability (and especially, intelligent computing) are enormous. Yesterday we went one step closer to intelligent computing; something we couldn’t fathom even a few years ago. What an exciting time to live in.


  1. A new avant-garde field in bioethics is “theoretical bioethics” which argues whether software can suffer. And if so, what are the ethics of creating, modifying and deleting it from our hard drives. 

Hello, Yosemite

June 4th, 2014

I wrote my thoughts about Monday’s WWDC elsewhere.1 Today I installed OS X Yosemite on a new partition in my 15″ MacBook Pro Retina (2.3 Ghz i7, 16GB RAM)2 and I only have one word: wow.

Yosemite

I’ll briefly elaborate on two of Yosemite’s aspects as of this beta 1.

Interface

It is gorgeous. Amazing. Beautiful. Helvetica Neue is a great fit. The new dock is lovely. Even the vivid blue of folders is ok.3 Transparency—although often buggy or ommited due to being beta 1—felt natural and appealing. Safari looks stunning. Other Apple apps which got a face-lift (like, Mail, Calendar, iMessages) are a perfect fit with the new semi-transparent window chrome. Using Mavericks now feels almost like what iOS 6 felt after using iOS 7.

Performance

Time for the bad stuff. Well, even for my computer Yosemite’s quite slow and it’s not only the UI. Definitely not a fit yet for a primary machine. But hold your pitchforks right there before start going mental against Cupertino: it’s only beta 1. Which, for Apple means something like early post-alpha for the rest of the world. Things will get better, faster; and I expect this to happen around beta 3 or 4.

All in all, OS X Yosemite—even now—is stunning.

And never forget what John Siracusa wrote on April 2, 2001:

I’ve said it before and I’ll say it again: the “X” is pronounced “ten”, like the roman number, not “ex” like the letter. Don’t make me come over there.

Update: I’ve deployed Yosemite in my late-2009 iMac and I’m happy to report it works smoothly. I’ve made it my primary boot partition. Exciting (and weird since on the Retina MacBook it lagged. I guess, post hoc, the choppy performance had to do with the retina UI.)

Update 2: Mac OS X Yosemite under the magnifying glass. A very nice round-up of all the visual changes in Yosemite.


  1. Seven Twenty Three isn’t exactly ‘elsewhere’ per se; it’s a new blog I co-started with my friend Konstantinos

  2. This is relevant to Yosemite’s performance; see Performance section. 

  3. I bet, though, the exact color will change until the Fall release.