This week I am listening to “Complicated Game” by James McMurtry
This week I am listening to “Complicated Game” by James McMurtry
Today I finished reading “The Power Laws: The Science Of Success” by Richard Koch
Today I finished reading “Breaking Stephan: A Pearls Before Swine Collection” by Stephan Pastis
Today I finished reading “Your New Job Title is “Accomplice”” by Scott Adams
Today I read a paper titled “Crowdsourcing Gaze Data Collection”
The abstract is:
Knowing where people look is a useful tool in many various image and video applications. However, traditional gaze tracking hardware is expensive and requires local study participants, so acquiring gaze location data from a large number of participants is very problematic. In this work we propose a crowdsourced method for acquisition of gaze direction data from a virtually unlimited number of participants, using a robust self-reporting mechanism (see Figure 1). Our system collects temporally sparse but spatially dense points-of-attention in any visual information. We apply our approach to an existing video data set and demonstrate that we obtain results similar to traditional gaze tracking. We also explore the parameter ranges of our method, and collect gaze tracking data for a large set of YouTube videos.
Today I read a paper titled “Enhancing Genetic Algorithms using Multi Mutations”
The abstract is:
Mutation is one of the most important stages of the genetic algorithm because of its impact on the exploration of global optima, and to overcome premature convergence. There are many types of mutation, and the problem lies in selection of the appropriate type, where the decision becomes more difficult and needs more trial and error. This paper investigates the use of more than one mutation operator to enhance the performance of genetic algorithms. Novel mutation operators are proposed, in addition to two selection strategies for the mutation operators, one of which is based on selecting the best mutation operator and the other randomly selects any operator. Several experiments on some Travelling Salesman Problems (TSP) were conducted to evaluate the proposed methods, and these were compared to the well-known exchange mutation and rearrangement mutation. The results show the importance of some of the proposed methods, in addition to the significant enhancement of the genetic algorithm’s performance, particularly when using more than one mutation operator.
Today I finished reading “Fundamentals of Action and Arcade Game Design” by Ernest Adams
Today I finished reading “After the King: Stories in Honor of J.R.R. Tolkien” by Martin H. Greenberg
There is no greater sin in this life than selling me a tall, cold glass of Blackthorn cider but in actuality serving me a glass of Wyder’s Pear cider that is flat and then trying to convince me that I do not know what Blackthorn cider tastes like and that the cider is not flat.
There is a special circle of Hell reserved for people like that.
I know. I checked. It’s in the Bible.
“When you bring an offering to the Lloyd it shouldn’t be burnt… something… something.”
Look it up.
Leviticus I think.
He was all about punishing people for cheating and lying.
This week I am listening to “Untethered Moon” by Built To Spill
Today I finished reading “Frozen Assets” by P.G. Wodehouse
It’s a shame I never had a child.
I would have named him Abraham Lincoln.
I would ensure he had a generous weekly allowance that would sustain him throughout his entire life.
The requirement of receiving the allowance would come with the stipulation my son writes random, nonsensical quotes at regular intervals and posts them publicly, dated, on the Internet.
“It must be true, it was on the Internet.” – Abraham Lincoln, 2016.
Today I finished reading “Intron Depot 5: Battalion” by Masamune Shirow
Today I read a paper titled “Machine olfaction using time scattering of sensor multiresolution graphs”
The abstract is:
In this paper we construct a learning architecture for high dimensional time series sampled by sensor arrangements. Using a redundant wavelet decomposition on a graph constructed over the sensor locations, our algorithm is able to construct discriminative features that exploit the mutual information between the sensors. The algorithm then applies scattering networks to the time series graphs to create the feature space. We demonstrate our method on a machine olfaction problem, where one needs to classify the gas type and the location where it originates from data sampled by an array of sensors. Our experimental results clearly demonstrate that our method outperforms classical machine learning techniques used in previous studies.
Today I read a paper titled “Fast and Robust Hand Tracking Using Detection-Guided Optimization”
The abstract is:
Markerless tracking of hands and fingers is a promising enabler for human-computer interaction. However, adoption has been limited because of tracking inaccuracies, incomplete coverage of motions, low framerate, complex camera setups, and high computational requirements. In this paper, we present a fast method for accurately tracking rapid and complex articulations of the hand using a single depth camera. Our algorithm uses a novel detection-guided optimization strategy that increases the robustness and speed of pose estimation. In the detection step, a randomized decision forest classifies pixels into parts of the hand. In the optimization step, a novel objective function combines the detected part labels and a Gaussian mixture representation of the depth to estimate a pose that best fits the depth. Our approach needs comparably less computational resources which makes it extremely fast (50 fps without GPU support). The approach also supports varying static, or moving, camera-to-scene arrangements. We show the benefits of our method by evaluating on public datasets and comparing against previous work.
Today I read a paper titled “A Dataset of Naturally Occurring, Whole-Body Background Activity to Reduce Gesture Conflicts”
The abstract is:
In real settings, natural body movements can be erroneously recognized by whole-body input systems as explicit input actions. We call body activity not intended as input actions “background activity.” We argue that understanding background activity is crucial to the success of always-available whole-body input in the real world. To operationalize this argument, we contribute a reusable study methodology and software tools to generate standardized background activity datasets composed of data from multiple Kinect cameras, a Vicon tracker, and two high-definition video cameras. Using our methodology, we create an example background activity dataset for a television-oriented living room setting. We use this dataset to demonstrate how it can be used to redesign a gestural interaction vocabulary to minimize conflicts with the real world. The software tools and initial living room dataset are publicly available (this http URL).
Long-ish personal anecdote.
Went to help my brother collect his new RV yesterday.
The drive wasn’t any longer than an SF to LA or SF to Portland run, which I’ve done quite literally hundreds of times, but oh boy, do I hurt today.
I feel like I have been hauling sheet goods back and forth in the workshop all day.
I don’t get that at all.
On the way home I stopped at Woodcraft and picked up some Freud router bits for some custom cabinetry I am building.
Which got me to thinking about intellectual property.
The packaging is obviously covered by copyright laws.
The user manual is covered by copyright laws.
How the packaging works is covered by patent law.
The Freud logo is covered by trademark law.
The router bits themselves are covered by no less…
than patent law for how they cut
than trademark law for their distinctive Freud red colour
than copyright law for the shape of the router profile.
Which is crazy!
Once you throw away the accoutrement of the product, i.e. the manual, the storage carton, the sticky warning labels, what you are left with is a chunk of metal that were I to recklessly melt it down in the workshop would be worth just a few cents.
At what point does a lump of metal start to be protected by law once it has been shaped?
This week I am listening to “Fading Frontier” by Deerhunter
Today I finished reading “Jeeves and the Old School Chum” by P.G. Wodehouse
Today I finished reading “Startup Communities: Building an Entrepreneurial Ecosystem in Your City” by Brad Feld
From 15 systems running Windows 7 (and a few 8’s) and 1 Linux box and 1 OS X laptop.
To 9 systems running Windows and 7 Linux boxes and 1 OS X laptop by July.
To a planned 2 systems running Windows (because we cannot change the OS) to everything else OS X and Linux by end-of-the-year.
Because Windows 10 happened.
Or rather, because Microsoft decided that I should upgrade because they said so.
Imagine purchasing a loaf of bread and then being told by the baker whether you can make toast or not.
Today I read a paper titled “Tracking of Fingertips and Centres of Palm using KINECT”
The abstract is:
Hand Gesture is a popular way to interact or control machines and it has been implemented in many applications. The geometry of hand is such that it is hard to construct in virtual environment and control the joints but the functionality and DOF encourage researchers to make a hand like instrument. This paper presents a novel method for fingertips detection and centres of palms detection distinctly for both hands using MS KINECT in 3D from the input image. KINECT facilitates us by providing the depth information of foreground objects. The hands were segmented using the depth vector and centres of palms were detected using distance transformation on inverse image. This result would be used to feed the inputs to the robotic hands to emulate human hands operation.
Today I read a paper titled “Toward Game Level Generation from Gameplay Videos”
The abstract is:
Algorithms that generate computer game content require game design knowledge. We present an approach to automatically learn game design knowledge for level design from gameplay videos. We further demonstrate how the acquired design knowledge can be used to generate sections of game levels. Our approach involves parsing video of people playing a game to detect the appearance of patterns of sprites and utilizing machine learning to build a probabilistic model of sprite placement. We show how rich game design information can be automatically parsed from gameplay videos and represented as a set of generative probabilistic models. We use Super Mario Bros. as a proof of concept. We evaluate our approach on a measure of playability and stylistic similarity to the original levels as represented in the gameplay videos.
This month I am studying “Baking mastery” concentrating on desserts.
This is my 28th month of study, 19th month of actual time. I like being able to race through those parts of the course that are easy.
How many different desserts can you possibly need to create in one lifetime?!?
This week I am listening to “The Most Lamentable Tragedy” by Titus Andronicus
Today I finished reading “Sprint: How to Solve Big Problems and Test New Ideas in Just Five Days” by Jake Knapp
Today I finished reading “The Axemaker’s Gift” by James Burke
It is interesting to observe that throughout human history society has tried to engender gender into everyday things.
Girls and boys clothing
Girls and boys colours (pink and blue in the latter half of the 20th century in the west)
Girls and boys toys (cars and dolls)
Girls and boys words and speech patterns
Girls and boys cars (automobiles)
Girls and boys careers
Girls and boys sports
Girls and boys hobbies
Girls and boys room décor
Girls and boys technology (to a degree)
The only thing we have not yet separated, but have taken a darn few good stabs at, is food.
Probably because girls and boys, to a man, have universally said “Fuck your salad, stay the fuck away from my rare steak.”
I do not understand why Microsoft Windows 8 & 10 and Ubuntu need to include web based search results as part of the standard, local desktop search.
“Hey, you searched for something in your documents, so here’s some results from Wikipedia, Facebook, Twitter, Tumbler, eBay, Amazon, an online music store, Netflix, another video streaming store, and a few other sources that we think might be relevant.”
Frankly I think we should also, by default, include results from Tinder, PornHub, KickAss Torrents, Match.com, and whatever child porn, fetish porn, gay porn and shock image websites anybody might be interested in, as a default, and let people turn off (but not completely remove) the ones they don’t need.
Then turn them all back on again in another software update for all users on the system.
I don’t think I need to be “sold too” in my desktop operating system.
I don’t need to be told “that’s an integral part of the operating system” when it clearly isn’t.
If we are going to allow one online service to show results I believe all online services, websites and companies should have an equal opportunity to shove shit you don’t need down your throat 24/7 in the privacy of your own home.
Or am I just stuck in my ways and this is the new economy?
Today I finished reading “Pandora in the Crimson Shell: Ghost Urn Vol 3” by Masamune Shirow
This week I am listening to “Divers” by Joanna Newsom
“I’d like to invite you to coffee. I’ll pay. I want to pick your brains about my start-up idea and I’m looking for a CTO. But I have to insist you don’t write about any of this on your blog. How does this afternoon sound?” said the unannounced inviter for coffee from New York City who found me through LinkedIn.
“I can only promise that if you promise not to say anything any reasonable person would regard as foolish.” I replied in an email from San Francisco.
I never did hear back.
Signed up to ownDrive.com.
Got this response immediately after clicking submit.
Oh yeah! This instills confidence in storing my valuable data with you:
Every day I wake up and I find myself to be rich.
I didn’t wake up to an alarm clock (unless a client needed me on the phone).
I woke up, lounged in bed for a bit, and got up when I felt like it.
That was a choice.
I decide what I will work on next.
Or whether I will take the day off.
I decide what I will eat for lunch and dinner.
Whether I will eat out or cook a meal from scratch.
I decide when to walk my dog.
Whether around the block or over at the dog park.
I decide to spend an hour in the workshop making some sawdust.
Whether that is for a book case or just practice cuts.
I decide to read a book for an hour.
Whether for pleasure or for business.
I decide when I will go to bed.
And in which city I will go to bed.
Every decision I made was made by me without the pressure of having to show up to a job, please someone else, or fulfill an obligation I never wanted.
I’ve stuck to this idea for several decades, if you have a lot of choices, you are very rich indeed.
Making a choice isn’t “making a decision.”
A decision is the metaphorical equivalent of whether you want burger or pizza for lunch.
Choice is deciding when to lave lunch, where to have lunch, what to have for lunch, who to have lunch with, and what you will talk about at lunch.
Every day, I am presented with choice.
And that makes me rich.
I’m richer than most everyone I know.
If you enjoy Pokemon Go, and I cannot fault you for that, here’s a useful tip for prolonging the battery life of your phone.
Put your fucking phone in your fucking pocket when you come in to the meeting.
Today I finished reading “Unified Behavior Framework for Discrete Event Simulation Systems” by Air Force Institute of Technology
Today I finished reading “Press Start to Play” by Daniel H. Wilson
Today I watched “Chaplin”
There have been serious but non-fatal crashes directly connected to Pokemon Go.
In early 2007 I wrote a rather prophetic piece.
This was just prior to Apple’s iPhone announcement if I recall correctly. Though don’t hold me to that.
People said that it was ridiculous… “Well that will never happen. You need to give people more credit.”
I think I was far too conservative in my outlook. I wish now I had thrown in some forward looking statements about Augmented Reality.
Today I watched “Life of Pi”
I know they are CGI and I know it’s only a film, but I cried for the poor animals on the boat.
“What about the humans Justin?”
There were humans?
This week I am listening to “Harmlessness” by The World Is A Beautiful Place And I Am No Longer Afraid To Die
Today I watched John Carter.
Swashbuckling tale sort of tangentially related to the book.
Not quite a “Do androids dream of electric sheep?” re-write but enough to confuse the hell out of me after a 30 year span from when I first read the novel.
Read that lengthy Atlantic article. I’ll wait. Read it? Good. Let’s proceed.
“That is insane.” was a common complaint.
Watch the documentary of “The Land” by Erin Davis and read the article.
At the end, my wife and I turned to each other and chorused.
“No! That is fucking awesome!”
I strongly believe we are heading to a crisis within American (and UK) industry, science and technology due to the over-protective parenting style.
We want better for our kids, and “better” equates as safer in a lot of our culture when it comes to our future.
But “safer” isn’t “better” when the outcome 40 years later is worse because we no longer have children who are now adults who are willing to take risks and “figure it out on their own.”
And then we lose.
We lose because future industry leaders in other cultures won’t have that risk averse nature.
We lose because future industry leaders in other cultures will be willing to figure it out on their own.
We lose because future industry leaders in other cultures are willing to experiment.
We lose because future industry leaders in other cultures are willing to set fire to things.
And we lose because future industry leaders understand that there isn’t anybody ready to swoop in and save them from themselves.
Today I read a paper titled “BioSpaun: A large-scale behaving brain model with complex neurons”
The abstract is:
We describe a large-scale functional brain model that includes detailed, conductance-based, compartmental models of individual neurons. We call the model BioSpaun, to indicate the increased biological plausibility of these neurons, and because it is a direct extension of the Spaun model. We demonstrate that including these detailed compartmental models does not adversely affect performance across a variety of tasks, including digit recognition, serial working memory, and counting. We then explore the effects of applying TTX, a sodium channel blocking drug, to the model. We characterize the behavioral changes that result from this molecular level intervention. We believe this is the first demonstration of a large-scale brain model that clearly links low-level molecular interventions and high-level behavior.
I do not know why we need five different conditioners, three shampoos and four types of bubble bath.
Is this like a “wine” thing where people pontificate on nose, mouth feel, regions and varietals?
Is there such a thing as a soap sommelier?
Today I read a paper titled “Progressive Gaussian Filtering”
Fuck me! Nice feedback filtering and sampling system!
The abstract is:
In this paper, we propose a progressive Bayesian procedure, where the measurement information is continuously included into the given prior estimate (although we perform observations at discrete time steps). The key idea is to derive a system of ordinary first-order differential equations (ODE) by employing a new coupled density representation comprising a Gaussian density and its Dirac Mixture approximation. The ODE is used for continuously tracking the true non-Gaussian posterior by its best matching Gaussian approximation. The performance of the new filter is evaluated in comparison with state-of-the-art filters by means of a canonical benchmark example, the discrete-time cubic sensor problem.
Today I finished reading “The Art of Startup Fundraising” by Alejandro Cremades
This week I studied “Developing Ideas and Design Concepts”
This is an online class from Lynda.com.
The class consists of just a hair under two hours of video.
I logged a total of 2 hours of “class time” and an additional 8 hours of sketching, laying out concepts, brainstorming, and working on sample project briefs.
Was at a tech mixer/meet-up/networking thingy in Silicon Valley area just before July 4th holiday.
“And we have a lot of machine learning in here” said the entrepreneur, indicating his app.
“It’s classifying product categories automatically based on the description and the manufacturer?” I ask.
The entrepreneur nods.
“A Naïve Bayes classifier then.” I add.
The technical cofounder, silent until now, eagerly starts to explain how he implemented it in NodeJS with an off-the-shelf gem.
“No, no, far more than that. We have a lot of machine learning in our app. This is Deep A.I.” said the business co-founder using air quotes.
I swear you could see the italics.
I looked at the technical co-founder without saying a word. He continued to babble about Naive Bayes and gems and NodeJS.
I asked about scaling the P values and if he was using a logarithmic function.
The run-on-sentences stopped. The response was slow and thoughtful. “I think that’s how I stop the values always trending to near zero. I don’t really understand that part.”
I nod politely. “Nothing wrong with that. Use whatever works, even if you aren’t sure you fully understand how it works.” I say encouragingly.
“Dude, shut up, you’re talking about stuff we’re trying to patent.” said the business co-founder impatiently.
“It’s just a Bayes classifier” opined the technical co-founder.
The business co-founder looked pained. “He doesn’t really mean that. It’s more complicated.”
I nod again, just as politely.
“Did you try a Laplacian smoothing algorithm? Or additive smoothing?” I asked knowing full well that Laplacian applies to polygonal meshes and that additive smoothing and Laplace smoothing are one and the same.
“Yes” said the business co-founder.
“I don’t know what those are.” said the technical co-founder the merest fraction of a second behind.
“Have you solved the overfitting to data problem?” I asked the business co-founder. A Naive Bayes classifier generally doesn’t suffer that problem.
“Of course. I won’t deny we had some trouble, but we overcame the overfitting issue.”
I nod again.
The technical co-founder looks like a deer caught in headlights.
“This is a very nice looking app” I said to the business co-founder. “But I will give you one piece of advice.” I didn’t look up from his phone that I was holding on to. I was still swiping through the screens of the app. “When you talk to potential investors, do not bullshit them about your technology. It’s no fun to lose out on an investment during the due diligence phase. The tech guys working for VCs are a lot sharper than I am.”
Now I had two deer caught in the headlights.
This week I am listening to “What A Terrible World, What A Beautiful World” by The Decemberists