Automakers Are Rethinking the Timetable for Fully Autonomous Cars

Automakers Are Rethinking the Timetable for Fully Autonomous Cars

The popular notion of the go-anywhere, go-anytime, sleep-in-the-back autonomous car crumbled a bit in the last few weeks, as automakers admitted that the development of full self-driving technology is more difficult than expected. Krafcik went on to say that the auto industry might never produce a car capable of driving at any time of year, in any weather, under any conditions. Most such problems need to be dealt with through test – either by driving physical miles or performing software simulations.

Source: www.designnews.com

Optimizing a PostgreSQL query from 24 mins down to 2 seconds

Optimizing a PostgreSQL query from 24 mins down to 2 seconds

Using the platform, you can make arbitrarily complex queries on large data sets. The clause in the original query is:

Which means that we do pattern matching on our URLs, then take an intersection with all the urls common with the recordings. Simple check was to simple do a on both the slow and fast queries on many different sets of data.

Source: parallelthoughts.xyz

Wisconsin bar owner uncovers 134-year-old circus poster

Wisconsin bar owner uncovers 134-year-old circus poster

By the time Berger was done excavating and researching, he had unearthed a 9-foot-high by 55-foot-long, multi-sheet, full-color paper lithograph circus poster advertising the Great Anglo-American Circus and Menagerie performing in Durand on Aug. 17, 1885, according to the Eau Claire Leader-Telegram. Schrake said the Durand poster is a relic from the golden age of circus, when the shows toured via railroad and advance teams would paper the towns on the schedule with posters and handbills promoting their acts. In another stroke of luck, though the building’s basement fills with water nearly every year, Berger noted that the only time Durand’s annual Chippewa River flooding would have been high enough for the above-ground artwork to be underwater was in 1884 — the year before the circus stopped in the city.

Source: www.chicagotribune.com

What Game of Thrones Got Wrong About Firebombing

What Game of Thrones Got Wrong About Firebombing

Since dragons represent air power, we should understand the historical analogy for the firebombing of King’s Landing not as the sack of medieval cities in a feudal era, but rather the saturation bombings of World War II, where undefended cities were systematically incinerated from the air. To be fair, audiences were permitted to see the aftermath of death by fire: charred bodies appropriately reminiscent of images from the aftermath of Dresden, Tokyo and the countless other Asian and European cities targeted from the air in that period. Strategic bombing proponents in World War II believed terrorizing civilians from the air would induce surrender.

Source: www.lawyersgunsmoneyblog.com

Kong raises $43M Series C for its API Gateway

Kong raises $43M Series C for its API Gateway

Kong, the open core API management and life cycle management company previously known as Mashape, today announced that it has raised a $43 million Series C round led by Index Ventures. One area the company plans to especially focus on is security, in addition to its existing management tools, where Kong plans to add more machine learning capabilities over time, too. It’s worth noting that while this is officially a Series C investment, Marietti is thinking of it more like a Series B round, given that the company went through a major pivot when it moved from being Mashape to its focus on Kong, which was already its most popular open-source tool.

Source: techcrunch.com

Programming Language Reminiscence: R-Technology

Programming Language Reminiscence: R-Technology

Nodes are program states and directed edges (arcs) are state transitions. The C code also has a more interesting R-program: building a full binary tree iteratively, without using stack — in constant memory, if we do not count the allocated tree nodes. I should also say that the tree builder (written for the sake of running the example and was not present in the original Algol-68 code) did take some thought: how many R-states I need, what is the point of each state, how much mutable state is enough.

Source: okmij.org

What makes ramen noodles so special?

What makes ramen noodles so special?

Photo: C_Sombutpinyo (iStock)
The science
Kansui does two critical things to wheat doughs like those that make ramen noodles:
Improves the rigidity of gluten. Manufacturers in Japan have identified specific ratios of these two salts, along with those mentioned other salts or buffers, to give ramen noodles their characteristic texture and flavor. There are some rules of thumb for using each salt:

For thinner, more brittle noodles, increase the ratio of potassium carbonate
For thicker, more chewy noodles, increase the ratio of sodium carbonate

Now, that said… I don’t think you should make noodles at home if you can help it.

Source: thetakeout.com

AMD Ryzen Mini-STX: ASRock’s DeskMini A300

AMD Ryzen Mini-STX: ASRock’s DeskMini A300

The front panel ports are the usual DeskMini affair, being a microphone input, headphone output, USB3.1 Gen 1 Type-A and USB3.1 Gen 1 Type-C. To the right, the standard STX form factor front I/O, embedded into the board, and to the top, the VRM section powering the CPU/GPU combination in the AMD APU. On the rear of the board, a giant AMD backplate, the CMOS battery,  the twin SATA power/data plugs, another NVMe-only Ultra M.2 slot, and a bunch of supporting circuitry, including a Realtek ALC233 chip for the front audio.

Source: smallformfactor.net

CodeGen: LLVM wrapper for just-in-time code generation and compilation

CodeGen: LLVM wrapper for just-in-time code generation and compilation

The general template that for CodeGen use looks as follows:

The code above compiles a function that returns an integer that was passed to it as an argument incremented by one. The human-readable source code that CodeGen generates looks like this:

Since CodeGen takes care of emitting all necessary debugging information, and informing GDB about the JIT-ed functions, the debugging experience shouldn’t be too bad:

A more complicated example would be if one of the tuple elements was an ASCII string. For example, if for a value and arrays and we wanted to compute it could be achieved by the code like this:

CodeGen configures LLVM so that it takes advantage of the features available on the CPU it executes on.

Source: github.com

Modern SAT solvers: fast, neat and underused

Modern SAT solvers: fast, neat and underused

Modern SAT solvers fall into one of two groups: local search based solvers and

Conflict Driven Clause Learning (CDCL) based solvers. Some of the data structures are generic, and well-known outside solvers, such as custom memory managers that batch allocations and keep data laid out in a cache-friendly manner, other are pretty much specific to CDCL SAT solvers, such as the (2) watched literals scheme. The naive implementation is simple, you can create a mapping between a variable and each clause that contains its literal when you are loading the problem, and then just iterate through all clauses relevant to a variable, either marking them as solved or shortening them.

Source: codingnest.com