Move over Eliza and expert systems. ChatGPT belongs to a family of artificial intelligence (AI) know as large language models (LLMs). The ChatGPT service lets you hold conversations with a computer ranging from astronomy to Zoroastrianism. This AI has some Kepler paid for my first month’s subscription of the ChatGPT service in December which gave me the opportunity to have more conversations with the AI. While it has its quirks, I can definitely see it becoming something that can assist with productivity when used correctly. In fact, I found it so useful, I got myself a subscription. In this blog post, I talk more about my experiences and where I think this technology might be headed.
Continue reading “ChatGPT: Dawn of ubiquitous AI”An almost-blog post
A few months ago, Steve suggested I write a paper for a particular conference. He even gave me a topic. Brat that I am, I thought about for a few minutes and then flat out said no to that topic but thought of another one suitable for the conference. I decided to write on the ethics and legality of reCAPTCHA. While outside the scope of my academic oeuvre, I figured that even if my paper got rejected, it would still make for an interesting “Random musings” blog post. But it hasn’t come to that. Instead, you can look for it at PST 2012 in a couple of months. At seven pages (and possibly eight after further additions), this is longer than my typical blog post. You might want to get your favourite hot beverage ready before diving in.
In defence of climate change deniers
I’ve heard some people say they don’t understand how people can hold the view that climate change is not anthropogenic yet claim that climate change can be countered cheaply using geo-engineering, e.g., by injecting sulfur ((Why, IUPAC, why?)) into the atmosphere. The reason for their concern is that they think it’s logically inconsistent since the effects of geo-engineering techniques and anthropogenic climate change are predicted by the same computer models. However, (anthropogenic) climate change deniers are being perfectly reasonable as far as thinking about temperature goes. Let me explain.
Really, Mister Mayor?
Toronto Mayor Doug Ford has been quoted as saying that congestion in Toronto can be reduced through “driving efficiencies”. He suggests that some of these could be realized by drivers were faster to drive off when the signal turns green “or didn’t stop at a crosswalk when a pedestrian is still five feet from the road […]. You can’t blame everything on the car, you know.”
Populating Inflo with data
One can fairly simply write a module to dump data into Inflo. The first thing I populated the database with was with some population data and then surface area data. I’m currently thinking of adding GDP data. Any ideas as to what other easily mineable data I ought to include?
Hello, Inflo
And now for something completely different: the post that I’ve alluded to for a few weeks (and as far back as last year)…
Census draft
I started this blog post shortly after writing Let’s scrap the long-form census!, but have only recently finished it. No, this is not about “drafting” or conscripting people to fill out long-form versions of the census. It’s about the draft form of a census; that is, how a long-form census is born and its future relevance.
More about Professor Mor Harchol-Balter's talk
Last week, I highlighted some points from Professor Mor Harchol-Balter’s talk. This week, I would like to focus on a different point she made related to the academia-industry divide.
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Professor Mor Harchol-Balter talk & Consolidating load in data centres
Last week, Professor Mor Harchol-Balter visited us at the University of Toronto to deliver a talk as part of the Department of Computer Science’s Distinguished Lecture Series. During her excellent talk, she showed how intuition often fails us when scaling systems to meet a given load, even with perfect information of load patterns, whereby the amount of computers is over-estimated (thereby increasing energy use due to over-provisioning) and presented some results that will be appearing in conferences soon with experimental results related to power saving policies in data centres. One of the examples she gave of intuition breaking down is, given n computers serving r requests per unit time, load l, and a response time of t per request, how many computers are required to maintain response time t and load l if r increases by, say, a factor of one hundred?
During her talk, Professor Harchol-Balter mentioned that banks refuse to share computing power with anyone else. This seemed like a missed opportunity for energy savings in the form of virtualization, although, in the short term economic analysis, millions of dollars of power saved is chump change for these institutions. I later asked her about this and she conceded that they’d be willing to share their servers with other instances of their own software, given certain constraints. Which brings us to a continuation of my previous depth paper excerpt blog post Energy-proportional computing.
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Identifying gaps in wireless network infrastructure
About a month ago, I switched cellular service providers from Rogers to WIND Mobile. Aside from the abysmal quality of the phone or more precisely, the Android operating system, I purchased for use on the new network, the cellular network infrastructure requires some work. Indeed, WIND Mobile is well aware of this problem and has a page called Network Builder to report coverage issues. It might be better if this process could be automated.
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