Hiring Sucks.

The other day I came across this story by Guy Shachar, in which he shares his experience with hiring people and the lack of candidates.

The struggle is real. All the different startups are competing over the same human resource and let me tell you, the list of proficient talent isn’t as long as you might think. Or as someone once told me, the problem with going after the top 1% of talent, is that there is only 1% of top talent. In fact the only thing that’s harder than finding top talent employees, is finding top talent employees that are interested in working in your startup.

This reminded me of a long rant I wrote about ten years ago – Where did all the PHP programmers go? And I wasn’t even looking for the top 1% of talent at the time.  I have been continuously involved in hiring for a number of companies since that blog post.  I’ve tried a variety of different approaches with varying success.  But the problem is real and it’s getting worse.  There’s huge demand, insufficient supply, and the quality of the supply seems to be dropping as well, with many educational institutions falling behind the progress.

And it’s even tougher for the startups, as they don’t have much to throw into the competition with the larger established companies.

Caire – content aware image resize library

Caire is content aware image resize library.

How does it works

  • An energy map (edge detection) is generated from the provided image.
  • The algorithm tries to find the least important parts of the image taking into account the lowest energy values.
  • Using a dynamic programming approach the algorithm will generate individual seams accrossing the image from top to down, or from left to right (depending on the horizontal or vertical resizing) and will allocate for each seam a custom value, the least important pixels having the lowest energy cost and the most important ones having the highest cost.
  • Traverse the image from the second row to the last row and compute the cumulative minimum energy for all possible connected seams for each entry.
  • The minimum energy level is calculated by summing up the current pixel with the lowest value of the neighboring pixels from the previous row.
  • Traverse the image from top to bottom and compute the minimum energy level. For each pixel in a row we compute the energy of the current pixel plus the energy of one of the three possible pixels above it.
  • Find the lowest cost seam from the energy matrix starting from the last row and remove it.
  • Repeat the process.

AutoMapper – Declarative data mapper for PHP 7

AutoMapper can map data from array/object to existing array/object or marshal a new one.

Mapping rules specified in declarative way using three simple definitions:

  • From definition (From::create or via short function from) — maps single field from source to target. Supports chainable functions:
    • ->convert(callable $callable) — converts input value to another one via any callable;
    • ->trim() — trims value to eliminate whitespaces (suitable for strings);
    • ->default($defaultValue) — returns default value if source field is missing;
    • ->ignoreMissing() — ignores target field if source field is missing;
    • ->ignoreEmpty() — ignores target field if source field is empty.
  • Aggregate definition (Aggregate::create or via short function aggregate) — maps multiple fields from source to single target field. Supports chainable functions:
    • ->trim() — trims aggregated value
    • ->ignoreEmpty() — ignores target field if aggregated value is empty.
  • Value definition (Value::create or via short function value) — maps constant value to target field. Supports chainable functions:
    • ->trim()
    • ->ignoreEmpty()

All missing source fields can be ignored via AutoMapper::create(...)->ignoreAllMissing() modifier.