Day: February 28, 2018

If many of your clients don’t understand the difference between artificial intelligence (AI) and intelligent systems, you’re not alone. There’s a deeply rooted misconception about AI that isn’t going to clear up anytime soon.

AI has become a marketing buzzword and is being used interchangeably with computer algorithms that analyze data and produce a solution. For the majority of the population, this misunderstanding isn’t a problem.

However, when entrepreneurs and corporations start to pursue the development of their own intelligent projects, the lack of understanding can drive data scientists – and programmers – crazy.

Since AI seems to be what everyone wants, it appears that marketing messages are being constructed that tell people everything is AI when in fact, it’s not.

Instead of getting frustrated, here’s how you can help your clients understand what AI really is when they ask for an AI solution.

1. Explain that AI is marketed just like any other product

The most effective way to help your client understand when the solution they want isn’t actually AI is to explain that AI is marketed just like any other product. Everyone wants AI, so marketing messages tell people that everything they do is AI.

To a non-data scientist, it seems logical that if a computer predicts anything, it must be artificial intelligence. This isn’t true, and you’ll need to use familiar examples to override your clients’ beliefs.

2. Explain artificial intelligence to clients using familiar examples

Long before AI existed, machine learning was used to optimize actions based on patterns in data. Only when deep neural networks and reinforcement learning were applied did true AI emerge. It’s these two tools that gave rise to real AI like self-driving cars and machines that can read MRIs to determine if cancer is present.

Explain to your client that self-driving cars would never be allowed on the road if it weren’t for reinforcement learning and deep neural networks, and that each time a self-driving car encounters a new experience, it learns more, and that learning can be added to every other self-driving car’s programming. That’s how they were developed.

3. Distinguish intelligent systems from AI

According to Forbes.com, “artificial intelligence is the broader concept of machines being able to carry out tasks in a way that we would consider “smart.” Computers that are authentically utilizing AI technology are taught to think and learn for themselves, just like humans. This is in contrast to programming a computer with information and an algorithm to make decisions.

Explain to your client that intelligent systems work with patterns just like AI, except intelligent systems don’t have the deep neural networks that support self-learning. In today’s tech world, intelligent systems are being used by nearly everyone on a daily basis. Chances are, your client is familiar with at least one you can use as an example.

For instance, context-aware intrusion prevention systems (IPS) are now being used to increase security by scanning WAN and internet traffic. Cato Networks, for example, provides this context-aware protection  with no capacity constraints. This is unusual for the industry but made possible by intelligent systems.

Cato’s intelligent system can detect suspicious traffic patterns and stop traffic from specific countries. It can use Active Directory to recognize user identity and perform true filetype inspection to prevent attacks.

4. Use the analogy: “a square is a rectangle, but a rectangle isn’t a square”

In school, you might remember learning that a square is a rectangle, but a rectangle isn’t a square. A rectangle is a quadrilateral with four right angles, and a square is a quadrilateral with four right angles and four sides of the same length. By this definition, a square is most definitely a rectangle.

By this same kind of logic, it can be explained that AI is being applied by using machine learning, but machine learning alone doesn’t constitute artificial intelligence. Machine learning is when computers can train themselves and adapt their own programming to the task. This is part of AI, but not AI itself.

Be careful if clients still don’t understand

Sometimes you need to let go of trying to educate a client on the technicalities they don’t understand. However, if you choose to proceed with a project for a client who insists on calling your intelligent solution AI, you need to be careful.

Avoid using the terms AI or artificial intelligence in your contracts to avoid being sued for not delivering on the project. Consult with your lawyer to create a clause that explains why your solution isn’t technically AI, and have the client initial that specific paragraph to indicate full understanding. https://goo.gl/q35Cua #DataScience #Cloud

What is Raspberry Pi?

Raspberry Pi is a small computer that costs between $5 and $35 but can function as a desktop computer or be used for additional functions, such as building smart devices. Originally, the Pi was intended for usage in schools as a method of increasing interest in computers among children and as a tool to teach them basic coding.

The Raspberry Pi Foundation was founded in 2008 by a group of technicians Eben Upton, Rob Mullins, Jack Lang, Alan Mycroft, Pete Lomas, and David Braben. Since the inception, the Pi has grown into one of the most popular technology items in the world, with over eight million units sold as of 2016.

“The idea was that these tiny computers would allow for easy basic programming. Its low power usage and cost were expected to make Pis more easily available in classrooms.” The ‘Pi’ derives from the original idea to make a small computer to run only the Python programming language.

Many have seen the microcomputer’s potential, extending its capabilities by adding a camera or touchscreen module.

What are the different models?

Model A (Pi 1) of the Raspberry Pi was launched commercially on February 19, 2012. It could run Linux-based desktop operating systems, featured 256MB of RAM and a USB port, but no Ethernet port.

Since then, Pi 2 (2015) and Pi 3 (2016) were released, with Pi 3 being the best of the models. You can find detailed information regarding their features and capabilities online. The best model for your needs depends on what it will be used for.

What is it used for?

You may be surprised to know that there are two Raspberry Pi’s currently in space on the International Space Station as a part of the Astro Pi project. This project, run by British astronaut Tim Peake challenges students to write code for experiments he can perform in space.

This is just one of many examples of the extensive capabilities of Raspberry Pi, not to mention its use as a supercomputer and underwater drone.

Why is Pi useful?

With Pi, you can complete a variety of tasks that do not require much processing power and can enhance the small device with modules. It can help you save on space and cut costs while learning new skills and adding capabilities.

How can I use it?

* Learn how to code
* Use it as a desktop PC
* Make a media center
* Use it as a gaming console
* Build a camera attachment
* Make a clock or FM radio

What do others say?

It’s impressive how (relatively) potent the $35 Raspberry Pi 3 can be, but the board won’t work by itself. You’ll need to connect it to a monitor or TV via HDMI; connect it to power via a 5-volt micro-USB cord capable of drawing 2.5 amps from the wall (I used a Kindle Fire charger; my Moto X’s charger wasn’t sufficient); and connect yourself via a USB or Bluetooth keyboard and mouse, though you’ll need to set it up using USB peripherals before you can activate Bluetooth pairing. Grabbing a case or at least a box to house the Pi is a swell idea too, because the board is fully exposed in its default state.

To Summarize

Raspberry Pi is an affordable way of learning basic coding and grasping fundamental computer components. Working hands-on with Pi can help individuals develop their practical skills and provide the potential for a wide range of capabilities with this device. Start experimenting, see what you can learn, and better yet, create! https://goo.gl/3ExY2c #DataScience #Cloud