The Poor Man’s AI

Sometimes I have fun with checking the logs of my website. Over the years I’ve changed domains, hosting providers, and technologies, but certain script attacks keep coming in the exact same style. If I’m looking up a couple of IP numbers they are originating from, most of the time I’m finding them reported by admins. 

A few weeks ago I’ve discovered a new phenomenon: an IP reported and blacklisted by a bot. In other words a webmaster with passion for coding, and pissed off by WordPress hackers has invested some time and effort to automate filtering the access logs for common WP attack patterns, and blacklisting the originating IP numbers.

Taking into account that various hosting providers are scanning sites for discovering WP vulnerabilities, and the script kiddies might use IP rotator, it’s hard to tell that blacklisting a particular IP number is always a good idea.

For me the remarkable thing is that people are starting to teach their scripts to identify an unknown script  (bot, crawler, you name it) after its behavior. The first intelligent antiviruses adopting behavior analysis have lifted the software security to a new level, and in my opinion the main utility of AI is offering new possibilities as a tool.

Since the advent of online shopping, travel tickets, sports betting, trading, and property listing there are countless crawlers sent day by day, hour by hour or even more frequently to gather data. While the high-end and middle-market companies are already hiding their data sources behind paid APIs, and using refined AI solutions for blocking the undesired bots, the low-end markets are dependent on the cheaper and less sophisticated software automations.

A small family shop or local business are not losing money by serving a hundred of bot visits per day via a classic hosting package, but a regional online business hosted in the cloud usually has a big database and it's  paying a quantifiable price for the outgoing traffic generated by bots, and the slower response time of their servers might be noticed by their clients.

Many times the velocity of getting the latest data sets, or a specific projection of a big amount of data are the keys of the success of a business. Ultimately knowledge is power, thus for a commercial entity at some point it becomes profitable to erect a fence against bots. 

In a hi-tech country you can buy whatever data you need. In a non-hi-tech country it depends on the local culture, how much is the price-quality ratio of the data you can collect. In the grey area of partially digitized data AI may be used eventually to analyze sound tracks and videos in order to rate the protagonist's objectivity.

Hiring Ceremonies

 The hiring strategies are culture and industry-dependent, even if the final decisions appear to be dominated by the daily mood or delusion of a manager.

According to unofficial estimates in Spain 60% - 80% of the jobs are taken by family members, friends, or their recommended acquaintances. Based on the discussions I've followed over the years in various social networks I believe that the estimate is representative to the neo-Latin communities - I mean more hundred millions of people living in a Romance-language speaking country, city or neighborhood.

People belonging to communities with English-Saxon origins seem to have more appetite for experimentation, and for instance in the USA or Germany a bigger proportion of the work opportunities are taken by newcomers (outsiders, new faces) than in a neo-Latin country. 

In fact the whole telecommuting movement and the specific PM methodologies are based on the Yankee approach of handling multicultural teams and organizations. Their respect of diversity is manifested in the multitude of project types thriving in virtual spaces. 

As a freelancer I've seen both small software boutiques and companies with siloed departments; team leaders making hiring choices based on textual answers to a couple of questions, and CEOs hiring HR experts, or running automated video interviews.

Many hi-tech companies are using multistep pre-screening interviews for hiring. Even if the records of those conversations are analyzed with AI tools, the entire process reminds me of an age-old movie scene, where a mature lady was interviewing jobless youngsters, and selecting the right candidates in minutes.

25 years ago I told my manager of that time that I was not afraid of the future, because the tendencies can be calculated, but I was afraid of the individuals who are unpredictable. Since then  I've learned to deal with the uncertainty, and to appreciate people for the good things they've done so far, not for the mistakes they might make in the future.

Free Source with Upselling?

It has never worked as a business model. Although you can find many companies using free source tools, none of them has made years in a row at least zero profit from selling paid add-ons targeted to enhance free source packages.

From a marketing point of view it sounds promising to label a service offer as based off of a community driven tool, which is meant to focus on the user’s real needs as opposed to an abstract enterprise leader board’s considerations. 

Presenting a business entity with employees making a living from and contributing to the free source ecosystem sounds like declaring the company as part of the sharing economy, and it may attract talent from the Z-generation, there’s nothing wrong with that.

The real problem is with those guys confusing the marketing tactics with a business strategy, and funding startups insisting on such a strategy. It’s never a pleasure to work for a service condemned to fail - it’s a high-stress environment, where the initial success moments are followed by an endless loop of “whatever I do it’s the wrong thing to do” moments.

The history of long and respectively short-lived free source projects demonstrates that the need for paid software add-ons is scarce and/or random, and the revenues collected from selling would eventually cover the spending with hardware and hosting for upkeeping such activities.

This happens because most people and companies using free tools don’t have sufficient resources to pay for the commercial alternatives of those tools, or cannot keep their offers competitive on their markets in the eventuality of using commercial software tools, consequently they are focused on avoiding operative spending as much as possible.

The long-lived free source projects are backed by strategic users, or are funded as side projects by financially stable organizations.