Article | February 26, 2020
Technology professionals and the companies that employ them all have their own unique needs, goals, and challenges. Workers often face the question of whether they should stay with their current employer or explore opportunities elsewhere. And companies are often in need of skilled and qualified workers that they may not be able to find. Two new reports from LaSalle Network shed some light on what tech pros and employers both want in the year ahead.
Article | December 21, 2020
Machine learning — a branch of artificial intelligence that gives computer systems the ability to automatically improve and learn from experience — has been making serious waves for the last few years. More recently, though, the applications for smartphones and other small screen experiences have started to take shape, driving the way millions interact with their mobile devices.
Yes, Your Mobile Devices are Becoming Smarter
So what do these innovations means for your business? Machine learning can, essentially, make your smartphone “smarter” by improving a host of functions and processes instantly. In fact, most smartphones are already using some type of machine learning or intelligent automation application that aids mobile devices in becoming more efficient and effective. Predictive text messaging, for example, is one such application that’s already become part of the mobile vernacular — chances are, you use it daily without thinking twice.
As a whole, businesses are ramping up their machine learning investment, meaning we’ll be seeing more of this technology — and more accessible versions of this technology — in the coming months and years. For each generation, there’s an added level of intuitiveness when it comes to mobile technology — your current smartphone is smarter than the computers that helped bring man to the moon, in many ways. From that end, how advanced will our mobile devices be in another 10 or 20 years? Smartphones could be paving the way for Robotic Process Automation (RPA) and evolving the very way many industries work.
What’s Next for Mobile Machine Learning
Historically, machine learning requires a tremendous amount of power — power mobile devices simply didn’t have. However, businesses can now install special chips in drones, automobiles and smartphones enabling them to consume 90 percent less power. As a result, mobile devices — even without an internet connection — can perform a variety of once-complex tasks, including:
Virtual / Augmented Reality
Smarter Camera Functionalities
Improved Device Security
Going forward, envelope-pushers are driving towards even bigger, better, more sophisticated applications — think motion control and navigation, diagnosing and analyzing sensory data and more. Interactivity or perceptual interfaces are also capabilities that the new applications are expected to be equipped with, giving mobile devices seemingly endless capabilities.
Due to these unique benefits, machine learning on small devices is clearly becoming a priority for businesses.
Article | March 15, 2021
A few weeks ago, I created a Tensorflow model that would take an image of a street, break it down into regions, and - using a convolutional neural network - highlight areas of the image that contained vehicles, like cars and trucks.
I called it an image classification AI, but what I had really created was an object detection and location program, following a typical convolutional method that has been used for decades - as far back as the seventies.
By cutting up my input image into regions and passing each one into the network to get class predictions, I had created an algorithm that roughly locates classified objects. Other people have created programs that perform this operation frame by frame on real time video, allowing computer programs to draw boxes around recognised objects, understand what they are and track their motion through space.
In this article, I’ll give an interesting introduction to object detection in real-time video. I’ll explain why this kind of artificial intelligence is important, how it works, and how you can implement your own system with Yolo V3. From there, you can build a huge variety of real time object tracking programs, and I’ve included links to further material too.
Importance of real-time object detection
Object detection, location and classification has really become a massive field in machine learning in the past decade, with GPUs and faster computers appearing on the market, which has allowed more computationally expensive deep learning nets to run heavy operations. Real time object detection in video is one such AI, and it has been used for a wide variety of purposes over the past few years.
In surveillance, convolutional models have been trained on human facial data to recognise and identify faces. An AI can then analyse each frame of a video and locate recognised faces, classifying them with remarkable precision.
Real-time object detection has also been used to measure traffic levels on heavily frequented streets. AIs can identify cars and count the number of vehicles in a scene, and then track that number over time, providing crucial information about congested roads.
In wildlife, with enough training data a model can learn to spot and classify types of animals. For example, a great example was done with tracking racoons through a webcam, here. All you need is enough training images to build your own custom model, and such artificial intelligence programs are actively being used all around the world.
Background to Yolo V3
Until about ten years ago, the technology required to perform real-time object tracking was not available to the general public. Fortunately for us, in 2021 there are many machine learning libraries available and practically anyone can get started with these amazing programs.
Arguably the best object detection algorithms for amateurs - and often even professionals - is You Only Look Once, or YOLO. This collection of algorithms and datasets was created in the 2000s and became incredibly popular thanks to its impressive accuracy and speed, which lends it easily to live computer vision.
My method for object detection and recognition I mentioned at the start of this article happens to be a fairly established technique. Traditional object recognition would split up each frame of a video into “regions”, flatten them into strings of pixel values, and pass them through a deep learning neural network one by one. The algorithm would then output a 0 to 1 value indicating the chance that the specific region has a recognized object - or rather, a part of a recognized object - within its bounds.
Finally, the algorithm would output all the regions that were above a particular “certainty” threshold, and then it would compile adjacent regions into bounding boxes around recognized objects. Fairly straightforward, but when it comes down to the details, this algorithm isn’t exactly the best.
Yolo V3 uses a different method to identify objects in real time video, and it’s this algorithm that gives it its desirable balance between speed and accuracy - allowing it to fairly accurately detect objects and draw bounding boxes around them at about thirty frames per second.
Darknet-53 is Yolo’s latest Fully Convolutional Network, or FCN, and is packed with over a hundred convolutional layers. While traditional methods pass one region at a time through the algorithm, Darknet-53 takes the entire frame, flattening it before running the pixel values through 106 layers. They systematically split the image down into separate regions, predicting probability values for each one, before assembling connected regions to create “bounding boxes” around recognized objects.
Luckily for us there’s a really easy way we can implement YoloV3 in real time video simply with our webcams; effectively this program can be run on pretty much any computer with a webcam. You should note however that the library does prefer a fast computer to run at a good framerate. If you have a GPU it’s definitely worth using it!
The way we’ll use YoloV3 is through a library called ImageAI. This library provides a ton of machine learning resources for image and video recognition, including YoloV3, meaning all we have to do is download the pre-trained weights for the standard YoloV3 model and set it to work with ImageAI. You can download the YoloV3 model here. Place this in your working directory.
We’ll start with our imports as follows:
import numpy as np
from imageai import Detection
Of course, if you don’t have ImageAI, you can get it using “pip install imageai” on your command line or Python console, like normal. CV2 will be used to access your webcam and grab frames from it, so make sure any webcam settings on your device are set to default so access is allowed.
Next, we need to load the deep learning model. This is a pre-trained, pre-weighted Keras model that can classify objects into about a hundred different categories and draw accurate bounding boxes around them. As mentioned before, it uses the Darknet model. Let’s load it in:
modelpath = "path/yolo.h5"
yolo = Detection.ObjectDetection()
All we’re doing here is creating a model and loading in the Keras h5 file to get it started with the pre-built network - fairly self-explanatory.
Then, we’ll use CV2 to access the webcam as a camera object and define its parameters so we can get those frames that are needed for object detection:
cam = cv2.VideoCapture(0)
You’ll need to set the 0 in cv2.VideCapture(0) to 1 if you’re using a front webcam, or if your webcam isn’t showing up with 0 as the setting. Great, so we have imported everything, loaded in our model and set up a camera object with CV2. We now need to create a run loop:
ret, img = cam.read()
This will allow us to get the next immediate frame from the webcam as an image. Our program doesn’t run at a set framerate; it’ll go as fast as your processor/camera will allow.
Next, we need to get an output image with bounding boxes drawn around the detected and classified objects, and it’ll also be handy to get some print-out lines of what the model is seeing:
img, preds = yolo.detectCustomObjectsFromImage(input_image=img,
As you can see, we’re just using the model to predict the objects and output an annotated image. You can play around with the minimum_percentage_probability to see what margin of confidence you want the model to classify objects with, and if you want to see the confidence percentages on the screen, set display_percentage_probability to True.
To wrap the loop up, we’ll just show the annotated images, and close the program if the user wants to exit:
if (cv2.waitKey(1) & 0xFF == ord("q")) or (cv2.waitKey(1)==27):
Last thing we need to do outside the loop is to shut the camera object;
And that’s it! It’s really that simple to use real time object detection in video. If you run the program, you’ll see a window open that displays annotated frames from your webcam, with bounding boxes displayed around classified objects.
Obviously we’re using a pre-built model, but many applications make use of YoloV3’s standard classification network, and there are plenty of options with ImageAI to train the model on custom datasets so it can recognize objects outside of the standard categories. Thus, you’re not sacrificing much by using ImageAI.
Good luck with your projects if you choose to use this code!
Yolo V3 is a great algorithm for object detection that can detect a multitude of objects with impressive speed and accuracy, making it ideal for video feeds as we showed on the examples aboves.
Yolo v3 is important but it’s true power comes when combined with other algorithms that can help it process information faster, or even increasing the number of detected objects. Similar algorithms to these are used today in the industry and have been perfected over the years.
Today self-driving cars for example will use techniques similar to those described in this article, together with lane recognition algorithms and bird view to map the surroundings of a car and pass that information to the pilot system, which then will decide the best course of action.
Article | July 21, 2021
In today’s world, everyone and everything needs an expert’s work. Every sector and organization thrives to achieve perfection for themselves and their customers. But with the evolving scenario and new technologies emerging, perfection needs outsourcing. On that account, every organization is building its services to provide other organizations with managed services.
In simple words, managed services are the need of the hour. They have been around for a pretty long time; however, the benefits of managed services have proved their efficiency in the past few years.
Managed services are not limited to IT but provide services from supply management to call centers because of its optimal efficiency and organizational performance. This goes for the IT and non-IT sectors as well.
Every organization comprises of an IT department. But what happens when the IT department is involved in solving the technical issues of the organization, rather than focusing on their core work? The business goes haywire resulting in more investment than ROI.
In the past few years, every business has realized the importance of managed services. As a result, the managed services market’s global business value, which was valued at US$185.98 billion in 2019 is estimated to reach US$356.24 billion by 2025. And this is the result of the benefits of managed services.
What are Managed Services?
In the post-Covid era, almost all businesses are relying on their IT infrastructure to keep them going. Technology is the need of the hour to assure the best efficiency and gain maximum profits. But an in-house team to manage all the IT work and the infrastructure from servers to networks costs a lot. This is a huge blow to the resources especially for start-ups and small to medium-sized businesses.
This is where managed services come to the rescue. Managed services providers have the expertise and infrastructure to ensure that your network administration runs perfectly well. From data backup to security, they take care of everything required for IT support.
The benefits of managed services can highly be availed by start-ups and small to medium scale businesses. Implementing managed services provides them with the latest infrastructure and updated technology at nominal costs.
As said earlier, managed services can be outsourcing to any part of the business, but IT managed services play a significant role these days. Thus, we will focus on the benefits of managed services related to IT.
Benefits of Managed Services
Managed services simplify your IT management. They have abolished the break-fix method and paved the way for regular and consistent service. We would not wait for something to break and then repair it while wasting resources. Managed services assure that there is no break or downtime in your IT system. Whether you have a start-up or a multinational company, the benefits of managed services make sure that you focus on the things that matter the most.
Here are the top 5 benefits of managed services for your business.
Managed services lower the IT costs incredibly. Lots of dollars are spent hiring and training the IT staff, plus the in-house infrastructure costs a fortune. In addition, the maintenance of the equipment and the retention of the staff can create financial issues in the organization. Thus, availing IT managed services will widen your resource base.
You can put your resources to use in the right place and avail the best IT support services at nominal costs.
Your IT services are streamlined and managed by a single provider. It helps to increase and decrease the services according to your demand and supply in the market. In addition, the monthly or yearly subscription plans will help keep your budget as planned.
Minimum or No Downtime
It is estimated that network downtime can cost a business almost US$5600 a minute. So, now you can take into account how the benefits of the low cost of managed services help your business.
Server failures, machine malfunctioning, electrical disruptions, or unintentional human errors can cause downtime. However, managed services can cut down downtime or even make sure that it does not occur.
Their proactive approach to the maintenance of the system through remote monitoring and management ensures business continuity.
An Expert’s Approach
Technologies to a managed service are like solutions to every problem. Their in-depth knowledge, state-of-art infrastructure, and updated technologies guarantee top-notch services and support.
An in-house IT service may or may not be able to find solutions to all the technical hurdles. Plus, their training can be expensive and time-consuming. So instead of wasting resources and trying to hit the target in the dark, it is better to avail specialized services. These services can be used according to your requirements.
Thus, the benefits of managed services include expert IT services according to your cost, time, and project requirements.
Security & Compliance
These reasons to use managed services stand out more prominently than others. For instance, even if your company data is accessed by a third party, then an authenticated service provider will regulate to keep all the information secure. Plus, they update the system on a timely basis to keep it safe from security threats and breaches.
A managed service provider ensures that your organization is up to date with the required compliances and audits. This saves you from violating data regulations that you may be unaware of. The trusted service provider conducts regular audits and provides system reports while assuring your system is updated with the current technology.
Along with cost savings, the benefits of managed services include scalability. Scalability saves your resources, time and assures that your employees perform the tasks that they are hired for.
When you hire a managed service provider, you can scale the acquired services according to your demands. For example, during holiday seasons, when there is increased demand, you can upscale your services, and at the end of the season, you can revert to the original requirements.
Scalable solutions allow you to adapt to rapidly changing market conditions while assuring productivity, system availability, and minimal or no downtime.
How to Choose the Right Managed Service Provider?
The benefits of managed services are totally worth every penny you spend. But it would help if you were extra careful about choosing the provider. Look systematically at the managed services model of the provider and decide. You need an extremely trustable and recognized managed service partner to manage your services.
Consider the below factors while deciding.
24X7 customer service
Total commitment & flexibility
Single point of contact
Continuous remote monitoring
If the managed service provider fulfills the above considerations and more, you know you have made the right choice.
Have an Open Approach to Managed Services
You may have a list of the pros and cons of managed services. But we are confident that the pros outgrow the cons.
The demand for managed services has surged in the pandemic as businesses are running efficiently even in remote conditions. All thanks to these services, you can now easily utilize managed services for seamless, secure connections and maximum ROI.
Frequently Asked Questions
What is the value of managed services?
Managed services are economical for an organization in terms of time and cost if you compare recruitment or involvement of in-house staff and infrastructure. They provide maintenance, regular reports, minimal or no downtime, and expert security for your systems.
Do I need IT managed services?
Whether you are a start-up, small to medium-sized business, or a multinational company, you need IT managed services. We all know IT services demand expensive training and infrastructure, and if there is downtime, it costs huge losses to the businesses.
As a result, availing these services ensures productivity, maximum ROI, and reliable IT operations with minimum investment.
How do you explain managed services?
Managed services are processes or tasks that are outsourced to a service provider who handles them exclusively. They improve operations, cut expenses and increase the productivity of the organizations.
Managed services let you focus on your core business while your other processes are outsourced efficiently and securely.
"name": "What is the value of managed services?",
"text": "Managed services are economical for an organization in terms of time and cost if you compare recruitment or involvement of in-house staff and infrastructure. They provide maintenance, regular reports, minimal or no downtime, and expert security for your systems."
"name": "Do I need IT managed services?",
"text": "Whether you are a start-up, small to medium-sized business, or a multinational company, you need IT managed services. We all know IT services demand expensive training and infrastructure, and if there is downtime, it costs huge losses to the businesses.
As a result, availing these services ensures productivity, maximum ROI, and reliable IT operations with minimum investment."
"name": "How do you explain managed services?",
"text": "Managed services are processes or tasks that are outsourced to a service provider who handles them exclusively. They improve operations, cut expenses and increase the productivity of the organizations.
Managed services let you focus on your core business while your other processes are outsourced efficiently and securely."