Category Archives: Innovation

“Low code” app development surges amongst pandemic

The shift to remote work has led some companies to come up with quick digital solutions for tasks that have become hard to tackle during the coronavirus pandemic.

Source: Emptying Offices Prompt Adoption of Low-Code to Build Work Apps


“Low code” means using “drag and drop” tools to create software applications. These systems make the creation of user interfaces easy, and provide functionality through similar drag and drop interfaces. We used to call this “Rapid Application Development” or RAD.

I have long though future software would be created with advanced tools that simplify the development process, particularly for straight forward applications of modest size. MIT App Inventor, and Scratch, are examples of drag and drop programming interfaces. Scratch is for teaching programming concepts to children. App Inventor leverages the Scratch concept into developing mobile apps for Android. You can learn about Microsoft’s Power Apps feature here.

Energy: Why throwing money at climate solutions leads to no solutions

When a political leader has a choice, such as am I going to inaugurate a new solar park or wind farm, or something, and show how I care? Or am I going to spend money on some eggheads [R&D] that don’t make for good picture? The problem is the extra solar panel park is not going to do very much, but these eggheads could make a huge difference

Source: We are throwing money at the wrong solutions to climate change

I began looking at solar PV and EVs as ways to take personal action. Read my other posts about what I learned – basically, adding solar PV for some homes will reduce CO2-emissions while for others it will have not only no impact but will have spent money that will then not be available for actual CO2-emission reductions. Similarly, in some situations, purchasing an EV just transfers your CO2-emissions to the utility company and has little or no impact. And at present prices, buying an EV uses up resources that might better be spent on say, home insulation.

Longer term, we need to invest in R&D and invent new technologies. Unfortunately, we invest little in R&D while politicians are pursuing actions that have little impact. Because they do not understand what they are doing.

Disaster tech: Should California require fire proof construction methods in wildland fire areas?

California has more wild fires, in large part, because its expanding population is wealthier and has migrated into outlying areas in historically fire prone wild land areas. As homes move in, so to do more power lines which are subject to start fires when wind blown trees contact power lines. The state is also historically prone to intense droughts that dry out forests.

Standard wood sided homes with a shake roof are easily burned by wild fires. Homes can, however, be built to be highly fire resistant through the use of non-flammable roofing and non-flammable siding and deck material. This is in addition to keeping clear the area around the home, and using detached garages and shops (a frequent source of accidental fire starts).

When wildfire swept through Bob Heath’s neighborhood in Napa, Calif., a lot of other homes in the fire’s path burned to the ground. In recent years, as many as 2,000 homes (annually) have been destroyed by wildfire, a loss inflated by drought conditions in both eastern and western states, along with steady encroachment of development onto “frontier” lands.Jim Smalley, manager of wildland fire protection for the National Fire Protection Association (NFPA), notes that some home builders have taken an active role in fire prevention–often getting some perks in the process.

Source: How to Build Fire-Proof Homes | Builder Magazine

A major reason that wild land fires seem worse is the same reason hurricane damages seem worse – as documented by researchers and the insurance industry, more people are living in more expensive structures in locations that are historically prone to “natural disasters”. Damages are up because we are wealthier and build more, nicer buildings in these zones, not because of an increasing incidence of events.

There are solutions. In hurricane prone areas near the ocean, new homes are built on risers with the bottom floor being a garage, storage and recreational area with “break away” walls to accommodate a storm surge.

In tornado prone areas, new construction uses steel fastening straps – or even steel stud construction – to create buildings that can survive the high winds of severe thunderstorms and tornadoes.

Logically, fire prone zones should be using fire resistant construction techniques.

Update – a day after writing this, the SF Chronicle had a report saying much the same, and adding that roof vents are an important weakness in fire resistance as wind blown sparks get sucked into attics.

The problems with models versus the real world

Model-land is a hypothetical world in which our simulations are perfect, an attractive fairy-tale state of mind in which optimising a simulation invariably reflects desirable pathways in the real world. Decision-support in model-land implies taking the output of model simulations at face value (perhaps using some form of statistical post-processing to account for blatant inconsistencies), and then interpreting frequencies in model-land to represent probabilities in the real-world.

The following is something I see nearly every day in the media – where the model output is presented as the real world (even when the real world is different):

As a trivial example, when writing about forecasts of household consumption, energy prices, or global average surface temperature, many authors will use the same name and the same phrasing to refer to effects seen in the simulation as those used for the real world. It may not be the case that these authors are actually confused about which is which, the point is that readers of conclusions would benefit from a clear distinction being made, especially where such results are presented as if they have relevance to real-world phenomena and decision-making.

For what we term “climate-like” models, the realms of sophisticated statistical processing which variously “identify the best model”, “calibrate the parameters of the model”, “form a probability distribution from the ensemble”, “calculate the size of the discrepancy” etc., are castles in the air built on a single assumption which is known to be incorrect: that the model is perfect.


It is not clear why multi-model ensembles are taken to represent a probability distribution at all; the distributions from each imperfect model in the ensemble will differ from the desired perfect model probability distribution (if such a thing exists); it is not clear how combining them might lead to a relevant, much less precise, distribution for the real-world target of interest.

Source: 1662970102.pdf

The last paragraph quoted above is something that has long bothered me about model ensembles.

This paper is a good read. Click on the link above to read the full paper.

Thompson, Erica L.; Smith, Leonard A. (2019) : Escape from model-land, Economics Discussion Papers, No. 2019-23, Kiel Institute for the World Economy (IfW), Kiel. Retrieved from:

Private sector R&D spending rising at fastest pace in 12 years

R&D spending is up +33% year over year. But this could be due, in part, to Federal tax cuts which change how R&D expenses are accounted for, starting in 2022. Most of the growth is within the leading edge “high tech” and “bio tech” sectors, and not by those in established industries such as automobiles.

Big tech and pharmaceutical companies have been pouring billions of dollars into research and development this year, driving up private-sector investments in intellectual property at the fastest pace in 12 years.

Source: The 15 U.S. companies that are investing the most in tomorrow’s big ideas – MarketWatch

Ham radio emergency communications influenced Jack Kilby, inventor of the integrated circuit

When a blizzard knocked out lines and plunged his father’s customers into darkness in 1937, young Jack watched as his dad enlisted local hams to coordinate repairs. That so much could be accomplished so quickly by the amateur radio operators left an impression on Jack, and electronics became another passion for him.

Source: Profiles in Science: Jack Kilby and the Integrated Circuit | Hackaday

Study finds VCs would get better returns investing in startups with age 45-50 year old entreprenuers 

A new study found the average founder of the fastest growing tech startups was about 45-years-old — and 50-year-old entrepreneurs were about twice as likely to have a runaway business success as their 30-year-old counterparts.

The findings have implications for both older and younger entrepreneurs, who may gauge future success on industry biases, as well as for venture capitalists, whose propensity to invest younger may be having adverse affects on their returns.”

Young people are just smarter,” Facebook CEO Mark Zuckerberg once said.

Zuckerberg’s bias is not uncommon in Silicon Valley. Young people are digital natives, thought to be cognitively sharper, less distracted by family and less beholden to current industry paradigms, according to the study.

Source: Research shows older entrepreneurs are likely to be more successful 

The bias to youth is, in part, because media stories frequently focus on the unusual (versus the important), and a young, successful entrepreneur met the unusual criteria.

VCs invest almost exclusively in firms started by very young entrepreneurs.

High school #Drones #Quadcopters racing as part of #STEM curriculum

A group of high schools in Hawaii have spent the past year studying physics, aerodynamics and learning how to build quad copters, culminating in a multi-high school competitive quadcopter racing program. Very cool!

Students participate in first interscholastic drone race

In some ways, this is similar to FIRST Robotics, also an awesome program for students interested in learning more about engineering, planning, fabrication and organizing complex projects. There are now many similar programs – nice!

Governments set to regulate and issue their own cryptocurrencies

Why the Bitcoin bubble may explode when it pops:

One reason for regulating blockchain-based cryptocurrencies, also known as digital tokens, is the growing concern that the virtual money they represent could be used for nefarious activities, such as money laundering. Cryptocurrencies could also be a threat to the current financial system because they have at times encouraged unbridled speculation and unsecured borrowing by consumers looking for a piece of the crypot action.

Source: Governments eye their own blockchain cryptocurrencies | Computerworld

Government or central bank issued, blockchained-based cryptocurrencies could be far more useful for legal transactions than the underground currencies like Bitcoin. Bitcoin is great for secret or questionable transactions that do not want to be tracked, of course, but most transactions are not in the camp.

(Note “blockchain” is an important bit of technology that has numerous applications other than cryptocurrencies.)