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What is AI?
AI includes machine learning as well as deep learning. There has been significant progress in both fields. On one hand, machine learning algorithms are helping businesses evolve, and on the other, speech recognition, image processing techniques and fingerprint patterns are taking the world by storm.
We use gadgets that are intelligent and makes our everyday tasks easy. For example, Alexa can remind you about your daily appointments, keep a check on your grocery list, play your favorite music when you need, read news and even play some brain games! It is like a human companion – that is not human – but has human-like capabilities.
There are restaurants where robots serve food to humans – how do they take orders? How do they walk and turn and serve food to the right customer? There are self-driving cars. How does the car know about red signals, traffic, when to move slow or fast and so on?
More serious business scenarios include spam filtering, product suggestions and personalization of feeds, dynamic pricing (for example during online ticket booking), optimization (for example, getting the best route for a destination), emotion analysis and much more. To do all these needs a lot of processing behind the scenes – a lot of data is analyzed, reports are produced, new business scenarios are created and ideas just have to keep evolving.

The future of AI involves advanced cognitive systems capable of doing what machine learning systems can’t. They will intelligently and fluently interact with human experts, providing them with articulate explanations and answers, even at the edge of the network or in robotic devices. Across the board, people will see and work with systems endowed with rare and valuable intelligence.
Cognitive artificial intelligence – truly intelligent symbolic AI software with bio-inspired, human-like reasoning – will take automation technologies to the next level and enable enterprises to fully utilize their investments in advanced technology. Using cognitive AI, robots can work together to not only analyze time-sensitive data at the point of origin, but also diagnose and solve problems in real-time.






The internet of things (IoT) is a catch-all term for the growing number of electronics that aren't traditional computing devices, but are connected to the internet to send data, receive instructions or both.
There's an incredibly broad range of things that fall under that umbrella: Internet-connected "smart" versions of traditional appliances like refrigerators and light bulbs; gadgets that could only exist in an internet-enabled world like Alexa-style digital assistants; internet-enabled sensors that are transforming factories, healthcare, transportation, distribution centers and farms.

Types of IOT Networks

1. Cellular
Cellular networks use the same mobile networks as smartphones to allow IoT devices to communicate. Because these networks were originally designed for power-hungry devices like smartphones, they weren’t always considered the best fit for IoT devices. Eventually, the cellular industry developed new technologies that were more appropriate for IoT use cases. Today, this type of wireless network is very popular, and is considered a reliable and secure method of IoT connectivity. Cell service is available in most locations in the U.S., and this type of network covers a very large area. However, cell connectivity often isn’t available in the places that most need monitoring sensors—for example, inside utility closets, elevator shafts, basements, etc. (Another IoT wireless technology class, LPWAN, might be a better fit for these locations.) And even though cellular connectivity is now less expensive and more power efficient than traditional telecom standards, cellular-connected IoT devices still require a great deal more power and energy than some other types of wireless networks.
2. Local and Personal Area Networks (LAN/PAN)
Networks that cover fairly short distances are called personal area networks (PAN) and local area networks (LAN). PAN and LAN networks are considered to be fairly cost-effective, but the transfer of data can sometimes be unreliable.
Wireless personal and local area network technologies that are commonly incorporated into IoT connectivity solutions are WiFi and Bluetooth. WiFi can be used for applications that run in a local environment, or in a distributed setting if there are multiple access points integrated into a larger network. One downside to WiFi is that it works only if the signal is strong and you’re close to the access point. Also, WiFi is generally more power-hungry than people think, but it is possible to operate it in a way that’s a little more power-efficient (for example, your device only connects periodically to send data, then goes back to sleep).
Bluetooth Low Energy (BLE) is a more energy-efficient wireless network protocol—if you’re not receiving data constantly, a single battery running BLE could last up to five years. However, compared to WiFi it is slower to transmit and is more limited in the amount of data it is capable of sending.
3. Low Power Wide Area Networks (LPWAN)
IoT devices that run on LPWANs send small packets of information infrequently and over long distances. This type of wireless network was developed in response to the early challenges of cellular connectivity. Proponents of LPWAN position it as longer-range than WiFi and Bluetooth, but using less power than cellular. Sigfox built the first LPWAN network in France and is considered the driving force behind its growth.
4. Mesh Networks
Mesh networks are best described by their connectivity configuration—how the components communicate with each other. In mesh networks, all the sensor nodes cooperate to distribute data amongst each other to reach the gateway.






The web world continues to add on to its list of thousands of websites and millions of active web users at such a rapid pace, that If you want to make your business website noticeable among all the active websites, you need to be immensely creative and think different, by following the web development trends. Predictions may not give you a confirmed idea but they definitely guide you on your way to some soul searching while considering web development.
The question might seem a bit overwrought, but there are good reasons for people to ask the question. One reason is that getting a website has never been easier or cheaper. Think about it: if you want to create a content site, it doesn’t take much to set one up with WordPress. You barely need to be technically literate, let alone a developer. Similarly, if you want an eCommerce store there are plenty of off-the-shelf solutions that allow people to start running an online business with very little work at all.
Even if you do want a custom solution, you can now do that pretty cheaply. On the Treehouse forums, one user comments that thanks to sites like SquareSpace, businesses can now purchase a website for less than £100 (about $135). The commenter remarks that whereas he’d typically charge around £3000 for a complete website build, potential clients are coming back puzzled as to why he would think they’d spend so much when they could get the same result for a fraction of the price.
From a professional perspective, this sort of anecdotal evidence indicates that it’s becoming more and more difficult to be successful in web development. For all the talk around ‘learning to code’ and the digital economy, maybe building websites isn’t the best area to get into.






For many of us, the very sudden changes that have come about as a result of the global Covid-19 viral pandemic, have sent seismic shock waves through our homes, lives and neighborhoods. Almost nothing is the same.
Our daily routines, our children’s lives, our jobs, our relationships, have been flipped upside down. Have we ever looked at so many graphs, charts, models and metrics? Have we ever had to consume so much information, or to process so much government-imposed health and societal advice? Have we ever been so fearful for our safety and health, or that of others?
There is no doubt that this is a major re-set, and that we are faced with the pretty big challenge of working out how to live and how to survive this ‘new normal.’
Whilst there will be some very hard-hitting questions to answer and lessons for the world to learn, on a personal level, we may have time to pause and think. Perhaps we have been given an opportunity to seek clarity on the direction of our lives. Were we really happy before Covid-19? For me, my ‘thinking time’ had already taken place about a year prior to Covid and so I know that periods away from the rat-race can be a blessing.
Having trained and qualified as a lawyer after university studies, when our first child was born, I applied for an extended period of maternity leave. My husband had a demanding job, with a long commute, and it was decided early on that one of us should be based at home.As a stay-at-home mother, I found creative avenues through cooking and writing and later, I took an online course in food journalism. I soon picked up writing work, which was flexible and slotted in and around raising the children. The more time I gave it, the more opportunities came. Sometimes I stepped back, sometimes I stepped up. Three children came along and I with a bit of grit and determination, I landed a cook book deal. My legal career now seemed like another world away.






Few doubt that cybersecurity will increasingly become an important part of most industries. The doors are open to you in the private or public sector or even as a freelancer. You wouldn’t necessarily have to stick to one role – or one industry, for that matter – since everything is connected nowadays. Everybody needs protection: be it a small and up-and-coming startup, or an enterprise with billions of dollars in revenue.
Cybersecurity keeps on evolving, just as the rest of the tech world does, which means that new roles will emerge while old roles will gradually evolve to encompass new skills. Even now there is an abundance of roles to choose from.
For example, you can become a big data scientist, and work with emerging technologies such as machine learning. If you’re more into solving riddles and looking for flaws, you might become a penetration tester working to crack the security of clients’ IT systems or become an ethical hacker enrolled in official bug bounty programs. While both test the security of different IT systems, their working methods are different. Often, penetration testers are more specialized in specific areas, while ethical hackers are jacks of all trades.