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It has been generally known for some time that quantum computers can in principle solve problems that are intractable on classical computers — like factoring large numbers to break public-key encryption (companies like Google have already increased the key lengths they use, as a precaution against early breakthroughs). With multiple corporations demonstrating working prototype quantum computers, can we look forward to using these amazing machines to accelerate machine learning? Perhaps a Quantum ML accelerator card to compete with GPUs/FPGAs/ASICs?

Quantum computers have other-worldly computational abilities (still mostly theoretical), but also other-worldly limitations. Take something as basic as RAM on a…


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Oloid and anti-oloid, it created them both!

I’ve wanted a 3D printer more or less ever since I heard that they existed outside sci-fi. I’ve watched early kit versions emerge, and seen the print quality gradually improve; I even got an after-hours tour of Autodesk’s fabulous office in San Francisco, basically a shrine to the miracle of computer-controlled manufacturing.

There are two main kinds of consumer-friendly 3D printer: one melts a spool of plastic to build up a model line by line, while the other projects ultraviolet light into a tub of liquid resin, flashing one entire layer into existence at once. This second kind has really…


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“Iterations” (Seema Gaur, Emil “GAN” Barbuta)

“Materials science” doesn’t have quite the pulse-raising associations as, say, “aerospace” or “robotics”. This is a shame! Stone tools — with wooden shafts — were key to the elevation of an ape with rather underdeveloped teeth and claws to the top of the food chain. Metallurgy gave us copper, bronze and iron — and corresponding waves of conquest and settlement (for at least 10,000 years, there has been strong selection pressure in favour of societies that let at least a few nerds tinker with ore and fire).

An extra pinch of carbon and a stubborn commitment to process improvement gave…


Google is the prototypical machine learning company. As a young and hungry startup, they first used “statistical modelling” to correct the spelling of search terms, and they’ve never looked back. These days, they even use machine learning to invent the new the machine learning, mechanising the invention of new deep neural network topologies that achieve state-of-the-art results in terms of accuracy, while often reducing total model size. If you’ve trained any deep neural networks at all, you’ve likely used Google’s Tensorflow framework — not bad for an advertising firm!

So, when such a legendary force in machine learning announced a…


If you’ve read much about the history of Tesla, you’ll know they’ve got a history of making in-house what other car companies buy from OEMs — not because they are driven by some corporate self-sufficiency dogma, but because for many key components, they fail to find a supplier who can meet their very, very high standards and do it a price they think is reasonable.

This has led Tesla to invent or co-invent components from drive shafts to the monster 17-inch touchscreen that they decided their first car just had to have. …


The computer on your desk is very nearly useless. You can use it the way I, as a hilariously over-engineered typewriter-with-integrated-postal-service, or as a television set, or to store all the photographs you took so carefully and never remember to look at again.

Photo of an ironing board by Filip Mroz on Unsplash
Photo of an ironing board by Filip Mroz on Unsplash

Your computer and its more powerful siblings are confined to desktops and server closets because, despite the exquisite refinement of all the sensors we connect to them, they understand almost nothing of the world around them. …


A sequel to “Career advice for techies”

The enquiry is usually something like…

“I’ll be graduating with a Masters in Data Science from the University of X this summer, and would love to get an internship with your team. I’m super passionate about machine learning! Can I give you my CV?”

Honestly, just having enough initiative to find someone that might appreciate your skills is already a really strong positive. However, I usually find myself giving the same few pieces of advice.

Show, don’t tell!

Like Eliza in “My Fair Lady”, I don’t want you to declare your undying love for machine learning…


After waste, the great money sin is idleness - so best then to keep your money working? Lots of reading, validated by good and (expensive!) bad experiences, led me — and lots of other people — to my current thinking:

  • Having some cash around is an excellent idea — you need that immediately-available buffer. You should never need to worry about unexpected expenses.
  • …but too much cash is really a waste of money! There you go, off to work every day, while your cash yawns, rolls over, and goes back to sleep, inflation steadily atrophying its purchasing power.

How exactly…


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Late October is dark and cold, bare branches framing a blackening sky. The season of decay seems to suit the churchyard, thick with drifts of rotting leaves. Even the headstones are decrepit, once crisply-carved lettering now almost erased by centuries of rain and frost. The church itself seems as dead as its surrounding congregation, windows and doors boarded up, slates coming loose. A bright plastic “For Sale” sign is nailed to the grey stone of a structure that has, in one form or another, stood for eight centuries. …


Immensely flattered by a series of requests for career advice (all from terrifyingly bright, effective, hard-working young folk who don’t seem to need it at all!), I decided to take my own advice (“find the long-term lazy solution”) and write it all down so I could just share a link.

I work in a technical role myself; I write some code, train some machine learning models, and try to help and advise others on these things. I’m one of those irritating people who look forward to Monday mornings and reluctantly fold up my laptop of an evening. I get to…

Edward Dixon

Intel Data Scientist. Interest in #machinelearning stems from hope that someday a robot will iron my shirts, co-author of ‘Demystifying AI for the Enterprise’.

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