Today’s paper of the week from Fermat’s Library is about Eliza by J. Weizenbaum. Eliza is a very early natural language processing system, that can mimic a Rogerian pshychologist‘s tactics and thus feel like a very sentient program within its context. Like many of my age, I was first introduced to Eliza via a game: a friend had an Amiga and a copy of it and we played around trying to make it tell us stuff based on information we were feeding it. It looked really amazing at the time.

Also like many others, I come across Eliza every few years and have toyed with an implementation. This is why this podcast on Eliza’s lineage is very interesting, because it shows from where you most likely learned to implement Eliza. Do listen to it. It contains a very interesting observation from a person who has actually read Weizenbaum’s paper:

Its name was chosen to emphasize that it nmy be incrementally improved by its users, since its language abilities may be continually improved by a “teacher”.

ELIZA A Computer Program For the Study of Natural Language Communication Between Man And Machine

So what most people overlook is that the original Eliza included a training mode, much like (in an abstract way at least) current chatbots that are all the craze do.

Weizenbaum himself was disturbed by the acceptance of Eliza and the anthropomorphic effect it had on people. He wrote Computer Power and Human Reason (a book that I need to skim through sometime given that I’ve read McCarthy’s refutation) to point out the issues he thought were important and was a fierce critic of AI in his later life, to the point of being marginalized in conferences where he appeared to preach his warnings. 99 Percent Invisible has an episode on him which you may also find interesting.

One goal for an augmented ELIZA program is thus a system which
already has access to a store of information about some aspect of the
real world and which, by means of conversational interaction with
people, can reveal both what it knows, i.e. behave as an information
retrieval system, and where its knowledge ends and needs to be
augmented. Hopefully the augmentation of its knowledge will also be
a direct consequence of its conversational experience. It is precisely
the prospect that such a program will converse with many people and
learn something from each of them which leads to the hope that it
will prove an interesting and even useful conversational partner.

ELIZA A Computer Program For the Study of Natural Language Communication Between Man And Machine

Too bad he didn’t successfully pursue this goal; no one else has. I think
success would have required a better understanding of formalization than
is exhibited in the book.

Defending AI Research

Things that returned to my mind as I sat today in front of the screen:

• The Datacenter as a Computer, book. A PDF can be found here.
• AWS, Azure, Google Cloud, Alibaba, Digital Ocean
• Thomas Watson saying “I think there is a world market for maybe five computers”
• Ken Thompson saying “The future of OS is just a stream to the cloud. Doesn’t see “universal cloud computer” Companies will try to dominate.” Cloud Drives, your music from a streaming service, even your Office documents, etc.
  
  Right now I am subscribed to two cloud drives and am battling migrating from one to the other. It took about a year for one client to not crash when downloading the whole content locally.
• An old post of mine that I never expanded on, just like this one.

This is what a friend whom I’d not seen for some time asked me yesterday. Well these days not much.

In the past I’ve used it for running OpenELEC, but these days a FireTV and whatever Android box the ISP gives you do the job fine.

I’m currently using it for two things:

• Running a mailing list
• Running pihole
• Using a blinkstick to know the state of my ISP connection
• RIPE Atlas software probe

Next project, with no actual ETA because I’m interested in other stuff more: run these in k3s.

I’m sure other people have more exciting stuff to do with it, but what little time I have for spare computing right now, I’m using it on Groovy and J.

This must be the most annoying question for many people during an interview process. An interview is a stressful situation, even for the most experienced performer, and yet you’re asked to predict the future, your future, just like that, without any other factors in. To be honest, I do not know what HR people want or think when they ask this, and I’m not sure they also do; I bet most are asking it because it is in their checklist.

Parenthesis on prediction: Five years is a long time. Often I am asked by friends and acquaintances on the (business) value of certain Engineering studies. I have learned to not answer this question, because it carries a lot of my biases, but also because I tell them this: If someone told you in 2007 that they began studying Civil Engineering in Greece, you’d assume -and tell them- that if they like the field, they won’t be out of work. Now Civil Engineering is 5 years of study (add one more for an MSc, a normal tradition in Greece) and you’re now in 2013, right in the middle of the Greek economic crisis, competing with thousands of other Civil Engineers, both old and new for virtually no work offered and for pennies.

That is why I hate these questions. But I’ve learned why certain people ask them. And this may provide a guideline how to think about these without hating the question or the interviewer. I am copying the relevant parts from an interview Brian Krzanich gave a few years ago:

I give the same advice to women and men about that. I tell them that there are three mistakes that people make in their careers, and that those three mistakes limit their potential growth.

The first mistake is not having a five-year plan. I meet so many people who say: I just want to contribute. But that doesn’t necessarily drive you to where you want to go in your career. You have to know: Where do you want to be? What do you want to accomplish? Who do you want to be in five years?

The second mistake is not telling somebody. If you don’t go talk to your boss, if you don’t go talk to your mentors, if you don’t go talk to people who can influence where you want to be, then they don’t know. And they’re not mind readers.

The third thing is you have to have a mentor. You have to have someone who’s watching out, helping you navigate the decision-making processes, how things get done, how you’re perceived from a third-party view.

After that you can now have a discussion. When you want a raise you’re not only going in saying: I want more money. You’re going in and saying: Here’s what I want out of my career. Here’s what I accomplished. Here’s what I said I was going to do. Here’s what I’ve done. Not only do I deserve more money but I want to get to here on my career.

Because what you really want is to build a career, not just get the raise. And if you do those things, whether you’re a man or a woman, you’ll be a lot better off.

If you’d asked me in 2013 where would I see myself in 5 years, there is no way I would have predicted that I would have worked for three startups, a brief stint at Intel and the software house of the biggest lottery on the planet. I was working in the Public Sector and doing relatively OK. But I know I needed two things: A pay raise and to sharpen my skills. And mind you, I was not telling anybody nor had a mentor. I did not even know how to interview. You do not have to wait to have coffee with someone to get your push like I did.

Plan ahead.

I make it no secret that one of the most impactful essays on me the last 20 years has been Bob Lucky‘s essay about the last electrical engineer. And I have seen other computer scientists taking it into account too.

Ever since cloud computing caught on, it comes more and more frequently to mind, because I see that the abundance of computing power makes people think that they can get away without really thinking about the problem. After all, computing has become cheap, right? The prototype you’ve just rigged up costs $10 / month to host. Well scale on the other hand does not come cheap and it will bite you.

Now that “cloud” has become a commodity word, “serverless” is coming to dominate. Because you really do not need to buy your infrastructure since, you know, you can have a data center as a tab in your browser for half the cost. And you really now do not need old-school sysadmins, since you make people all work together and deploy stuff n-times a day (DevOps).  But hey, even that is complex, because you just want to write the damn stuff and not think on where it runs, or how the hell it is supposed to run on scale. You only want profit on scale.

So let’s go serverless. And in the process, let’s make the prophecy about the world needing 5 computers true. Only they are cloud / serverless providers (just count the big players) where for some engineers, paraphrasing a bit Bob Lucky, life will be:

Projecting the current trends, future applications will be serverless.  No one will have the foggiest idea what is on that cloud.  Somewhere in the basement of the serverless provider or its successor will be a huge computer file with the listing of that infrastructure.  The last engineer will sit beside the file, handcuffed to the disk drive like a scene out of “Ben Hur.”  That engineer will be extremely well paid, and his or her every demand will be immediately satisfied.  That engineer will be the last keeper of the secret of the universe: E = IR.

Bootcamps and other vocational training institutions will turn out lots of serverless programmers, so prepare at least to be able to tick the Steinmetz chalk mark.

I cannot even remember how many disks Windows 95 was, fourteen, fifteen? Something like that. And how many hours installing it to machines around the lab.

That was the day I said goodbye to FTP software’s PC/TCP and Trumpet Winsock.