I’ve been a little engaged in a run for Council of Nashville’s 16th District and neglecting writing for Pocketables as I’ve been talking to people pretty much nonstop for a month.
I have no intention of abandoning Pocketables, but getting a team up and running for a campaign that was started absolutely last minute against two well-connected opponents has been somewhat time consuming.
This and every sit down turning into people telling me their stories for a couple of hours, kind of rude to write a review on a MyCharge Hub while talking to them (we’ll get that published later).
Voting Day’s is August 1st, so presumably I can stop campaigning then.
One of the things I’ve come to realize is that for many, this is life. Things like zoning of a house as a single family or a duplex can have effects on the entire neighborhood (duplex, owner dies, two tall and skinnies pop up, then developers can point and say “see, it’s that way over there” and get zoning changed).
It’s also life to some who just want the other group to fail. Politics man, it’s… man.
On the road I’m using my phone constantly now. I wish I’d had better charge rates with the SunnyBag, as that would have been an ideal representation of it, but it’s primarily charging a portable battery now and it’s not angled enough to reach full potential walking from door to door. Luckily most portable batteries have enough to keep me going through a day.
Using Google Sheets to track donations as well as leveraging Facebook for meet and greets, Google Docs for position statements, FB Messenger, texting, etc etc etc to communicate with people and about to throw in some Instagram videos, pulling up codes and history of the district pretty much constantly.
Unfortunately at this point it looks like a messy hodgepodge as I’m working on other things and most people have a team in place at this point.
My goal at the moment is to find a way to get a real message to people as opposed to a 30 second sound bite. Even if I don’t win, that message is there and hopefully whoever is elected will be forced to work with it.
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I’m holding the Depstech WiFi Endoscope while wearing a lab coat and I just can’t stop making rectal jokes. It’s not a gadget that I would usually review, but fret not, I will get to the bottom of something and tell you if the Depstech Endoscope WF010 is worth your peek!
Is Depstech Endoscope WF010 what doctors recommend?
A long time ago, I remember I had a use case for it. It was way too long ago to remember, but having a camera attached to a 3.5m long lead that can penetrate dark cavities could be of use to a small but highly adventurous part of the population.
What you get is a long stiff wire with a camera on one end and WiFi box wrapped around a battery. There are some LED lights to guide you in the dark and 3 attachments to perform difficult operations (a hook, magnet and a mirror). You won’t be performing endo-surgeries any time soon with it, but you could fish out a set of keys from a gutter for sure.
How Depstech Endoscope WF010 works?
Download this app, open it up and connect to the AP generated by the Depstech Endoscope WF010. You will have to set a correct video resolution for your phone to avoid the distortion but soon enough, you will see what’s on the other end of the endoscope. The recorded video comes as 640×480.
I have to say, that Depstech WiFi Endoscope can take you places you would not imagine. Especially, that for the safety reasons you can leave your phone connected via WiFi in a safe place.
The LEDs are bright enough and the camera performs ok in the dark places. It’s also watertight, so you can dip the camera into liquids of your choice! The bottom line is: you won’t get lost. There isn’t any significant latency. I was able to manipulate accurately while looking at the phone screen only.
The companion app is very bare bone. The video mode should be detected automatically really at this point. It’s nice to see that you can change the WiFi’s SSID and password but the overall all design is stuck in the mid 00’s.
The app comes with picture and video recording modes which handy if you want to review the footage later.
Depstech Endoscope WF010 is a niche product. You won’t need one until you do. It’s a question of what’s more valuable for you, a lost item in a drain or the money spent on an endoscope ($35./£30) you are likely to use 2-3 times a year. If you are the person who can justify the purchase with the much frequent use, the WiFi freedom, separate battery and 3.5m of wire could be a tempting proposal. I only wish the associated app was a little better.
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- Energy and Policy Considerations for Deep Learning in NLP — training Transformer NLP model w/ neural architecture search is 626,155 lbs of CO2. Compare to Car, avg incl. fuel, 1 lifetime: 126,000 lbs. (via MIT TR)
- Open Source Game Clones — This site tries to gather open source remakes of great old games in one place.
- A Glass Battery That Keeps Getting Better (IEEE Spectrum) — grunty batteries without the fire would be a great thing, indeed, never mind one that got better. Goodenough and collaborators claimed they’d developed a non-flammable lithium battery (whose electrolyte was based on a glass powder) that had twice the energy density of traditional lithium-ion batteries. They also published a graph that showed an increase in capacity over more than 300 charge-discharge cycles. (This increase, however, pales in comparison to the cell’s at least 23,000-cycle lifespan.)
- Text-Based Editing — We propose a novel method to edit talking-head video based on its transcript to produce a realistic output video in which the dialogue of the speaker has been modified, while maintaining a seamless audio-visual flow (i.e., no jump cuts). You edit the script and the software edits the video so the person says what’s in the script. (via Stanford)
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In this episode of the Data Show, I spoke with Dhruba Borthakur (co-founder and CTO) and Shruti Bhat (SVP of Product) of Rockset, a startup focused on building solutions for interactive data science and live applications. Borthakur was the founding engineer of HDFS and creator of RocksDB, while Bhat is an experienced product and marketing executive focused on enterprise software and data products. Their new startup is focused on a few trends I’ve recently been thinking about, including the re-emergence of real-time analytics, and the hunger for simpler data architectures and tools. Borthakur exemplifies the need for companies to continually evaluate new technologies: while he was the founding engineer for HDFS, these days he mostly works with object stores like S3.
We had a great conversation spanning many topics, including:
The importance of having solutions for real-time analytics, particularly now with the renewed interest in IoT applications and rollout of 5G technologies.
Use cases for Rockset’s technologies—and more generally, applications of real-time analytics.
The Aggregator Leaf Tailer architecture as an alternative to the Lambda architecture.
Building data infrastructure in the cloud.
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- Software Engineering for Machine Learning (Microsoft Research) — We collected some best practices from Microsoft teams to address [several essential engineering challenges that organizations may face in creating large-scale AI solutions for the marketplace]. In addition, we have identified three aspects of the AI domain that make it fundamentally different from prior software application domains: 1) discovering, managing, and versioning the data needed for machine learning applications is much more complex and difficult than other types of software engineering, 2) model customization and model reuse require very different skills than are typically found in software teams, and 3) AI components are more difficult to handle as distinct modules than traditional software components—models may be “entangled” in complex ways and experience non-monotonic error behavior.
- Open Long-Tailed Recognition (Berkeley) — A practical system shall be able to classify among a few common and many rare categories, to generalize the concept of a single category from only a few known instances, and to acknowledge novelty upon an instance of a never seen category. We define OLTR as learning from long-tail and open-end distributed data and evaluating the classification accuracy over a balanced test set which includes head, tail, and open classes in a continuous spectrum.
- Hype Cycle: Machine Learning (Vimeo) — dance being changed by computers.
- Past the Tipping Point: The Persistence of Firefighting in Product Development — In this paper, we try to answer three questions: (1) why does firefighting exist, (2) why does firefighting persist, and (3) what can managers do about it? The most important result of our studies is that product development systems have a tipping point. In models of infectious diseases, the tipping point represents the threshold of infectivity and susceptibility beyond which a disease becomes an epidemic. Similarly, in product development systems there exists a threshold for problem-solving activity that, when crossed, causes firefighting to spread rapidly from a few isolated projects to the entire development system. Our analysis also shows that the location of the tipping point, and therefore the susceptibility of the system to the firefighting phenomenon, is determined by resource utilization in steady state.
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