AI-powered camera...

Artificial intelligence (AI) is everywhere, and if you haven't yet got an AI-powered smartphone, you probably soon will do. Is it all just marketing hubris, or is AI in a smartphone – and particularly, in its camera – something we should all aspire to have? With the term AI increasingly being used not only in smartphones, but in all kinds of cameras, it pays to know what AI is actually doing for your photos.

What is AI?

AI is a genre of computer science that examines if we can teach a computer to think or, at least, learn. It's generally split into subsets of technology that try to emulate what humans do, such as speech recognition, voice-to-text dictation, image recognition and face scanning, computer vision, and machine learning. What’s it got to do with cameras? Computational photography and time-saving photo editing, that’s what. And voice-activation.

Voice-activated cameras

The ability for a computer to understand human speech is a form of AI, and it's been creeping onto cameras for the last few years. 

Smartphones have been offering Google Now and Siri for a few years, while Alexa is entering homes via the Amazon Echo speakers. Action cameras have jumped on that bandwagon in recent years, with the GoPro action cameras and even dash cams able to take actions when you utter simple phrases such as 'start video', 'take photo' and so on. 

AI software

AI is about new kinds of software, initially to make up for smartphones’ lack of zoom lenses. “Software is becoming more and more important for smartphones because they have a physical lack of optics, so we’ve seen the rise of computational photography that tries to replicate an optical zoom,” says imaging analyst Arun Gill, Senior Market Analyst at Futuresource Consulting. “Top-end smartphones are increasingly featuring dual-lens cameras, but the Google Pixel 2 uses a single camera lens with computational photography to replicate an optical zoom and add various effects.” 

Hybrid App....

Hybrid mobile apps are like any other apps you’ll find on your phone. They install on your device. You can find them in app stores. With them, you can play games, engage your friends through social media, take photos, track your health, and much more.

Like the websites on the internet, hybrid mobile apps are built with a combination of web technologies like HTML, CSS, and JavaScript. The key difference is that hybrid apps are hosted inside a native application that utilizes a mobile platform’s WebView. (You can think of the WebView as a chromeless browser window that’s typically configured to run fullscreen.) This enables them to access device capabilities such as the accelerometer, camera, contacts, and more. These are capabilities that are often restricted to access from inside mobile browsers. Furthermore, hybrid mobile apps can include native UI elements in situations where necessary, as evidenced by Basecamp’s approach towards hybrid mobile app development.

It can be very difficult to tell how a mobile application is built. Hybrid mobile applications are no different. A well-written hybrid app shouldn’t look or behave any differently than its native equivalent. More importantly, users don’t care either way. They simply want an application that works well. Trying to figure out if a mobile application is hybrid or native is like trying to differentiate rare grape varieties of wine. Unless you’re a sommelier or someone who really cares about it, it’s not terribly important. What matters is that the wine tastes good. The same can be said for hybrid mobile applications; so long as the application does what it’s supposed to do, who really cares how it was built? This point is underscored through an experiment we conducted where we wanted to see if people could tell the difference between a native application and a hybrid application:

Exponential growth in cloud services solutions....

Software as a Service (SaaS) opened a flexible and financially attractive door for businesses and consumers to try early cloud services. The growth of infrastructure and platform as a service (Iaas and PaaS, respectively) has expanded the number of cloud solutions available in the public and private sectors. In 2018, we expect to see many more organizations take advantage of the simplicity and high-performance the cloud guarantees.

According to a forward-looking 2016 survey on cloud services from Cisco, these solutions will continue to be deployed and used worldwide to accomplish diverse goals on an unprecedented level. 2018 will see SaaS solutions take the cake as the most highly deployed cloud service across the globe. The Cisco survey also forecasts that SaaS will account for 60% of all cloud-based workloads—a 12% increase over 2017 predictions. PaaS solutions will experience a modest five percent growth rate, while IaaS solutions are also set to increase. Given that these projections were made in 2016 and given positive performance in 2017, we can reasonably expect even greater growth in cloud services solutions than these predictions. Businesses that want to simplify operations and make it easier for their customers to access services will move more aggressively toward integrating SaaS, IaaS, and/or PaaS into their business processes.

The CDO role will grow extensively....

With the establishing of CDOs (Chief Data Officers) and other senior data professionals in top management, large organizations are changing their approach to data management. CDOs are now the driving force behind innovation and differentiation. They are in charge of revolutionizing existing business models, improving the communication of the company with the target audience, and revealing new opportunities to improve business performance. Their position in the company is relatively new, but it is quickly becoming mainstream. According to Gartner, by 2019 CDO position will be present in 90% of large organizations, but only half of them will manage to succeed. In addition to personal qualities, understanding the responsibilities, and awareness of the obstacles they might encounter, there is one more important thing that the company should do to unlock CDOs potential. Firms should consider branching the IT department into “I” and “T” separately, and CDOs should take the lead in the new group that is responsible for information management.

Cyber Security....

Cybersecurity is the protection of internet-connected systems, including hardware, software and data, from cyberattacks.

In a computing context, security comprises cybersecurity and physical security -- both are used by enterprises to protect against unauthorized access to data centers and other computerized systems. Information security, which is designed to maintain the confidentiality, integrity and availability of data, is a subset of cybersecurity.

Types of cybersecurity threats

The process of keeping up with new technologies, security trends and threat intelligence is a challenging task. However, it's necessary in order to protect information and other assets from cyberthreats, which take many forms.

• Ransomware is a type of malware that involves an attacker locking the victim's computer system files -- typically through encryption -- and demanding a payment to decrypt and unlock them.
• Malware is any file or program used to harm a computer user, such as worms, computer viruses, Trojan horses and spyware.
• Social engineering is an attack that relies on human interaction to trick users into breaking security procedures in order to gain sensitive information that is typically protected.
• Phishing is a form of fraud where fraudulent emails are sent that resemble emails from reputable sources; however, the intention of these emails is to steal sensitive data, such as credit card or login information.

Growing of NLP...

The usage of chatbots in customer service became one of the leading trends of the outgoing year. In 2018 applications will need the ability to recognize the little nuances of our speech. The users want to get a response from their software by asking questions and giving commands in natural language, and not thinking about the “right” way to ask. The development of NLP and its integration into computer programs will be one of the most exciting challenges of the 2018 year, and we have high expectations about it.

What is a simple task for a human — to understand the tone of speech, it’s emotional coloring, and double meaning — is also a difficult task for a computer that is accustomed to understanding the language of specific commands. These complex algorithms require many steps of predictions and computations, all of them must occur in the cloud and a split-second. With the help of NLP, people will be able to ask more shaded questions and receive apposite answers and, as a result, make better insights on their problems.

Google Map VPS...

With AR on, a future version of the Maps app will merge its traditional interface with a live camera view. When doing navigation, superimposed arrows will appear at each turn, making it harder to misinterpret directions. The company is even experimenting with inserting animated characters such as a fox, which would remove any doubt and make the app more entertaining. 

AR technology may also make its way into the rest of the app, for example popping up an information card when looking at a storefront.

VPS is a related feature, combining the live camera view with Google's data trove to get a better sense of position than possible with just GPS. The technology could be especially useful in dense urban areas where GPS is often blocked by skyscrapers.

A less radical additional in the works is a "For You" tab that will show nearby points of interest, with a "Your Match" feature attempting to custom-tailor recommendations. One intended use of this is sharing lists with friends instead of having to rattle off names from memory.

Deep learning will be faster and data collection better...

Nowadays, deep learning faces the challenges of data collection and the complexity of the computations. Due to the last problem, a big part of the innovation in hardware is aimed at speeding up the deep learning experiments, like new GPUs with a greater number of cores and different from today’s architecture that are now under development. According to Marc Edgar, a senior information scientist at GE Research, in the next 3–5 years, deep training will shorten the development time of software solutions from several months to several days. This will lead to better functional characteristics, increased productivity and reduced product costs.

Speaking of data collection, now almost all large firms have realized its importance and influence on the effectiveness of the work. In the coming year, companies will start using even more data, and the success will depend on the ability to combine disparate data. In 2018, companies will collect customer data via CRM, ticket systems, BMP and DMP, omnichannel platforms. Also, there is a rise in popularity in collecting data on specialized sensors like LIDAR. The integration of existing systems and the integration of all types of client data into a single information pool will definitely be a trend. Moreover, startups will continue to create new methods for gathering and using data, and therefore the costs for it will be reducing.

Self-Driving Cars

The stir about electric and autonomous cars has been around for a couple of years now. Big names like Volkswagen, Mercedes, Tesla, General Motors, and Google (of all companies) are pushing for driverless cars.

The goal everyone is aiming for is to solve the long-standing issue of people on the road. Yes, we are a danger to ourselves. Google’s self-driving cars have been involved in 11 minor accidents in the last 6 years, and none of them were reportedly caused by the car’s own fault.

By introducing autonomous cars on roads, cars which can compute faster than a hundred sober minds combined, road-related accidents may see a significant drop. Driverless cars will also significantly help those who do not have the capacity to drive, either because of health reasons, disabilities or old age.

New approaches to privacy and security...

 
The technological development boosts the importance of data, so hacking techniques become ever more progressive. The increase in numbers of devices connected to the internet creates more data but also makes it more vulnerable and less protected. IoT gadgets are getting more popular and widely used, yet they remain extremely insecure in terms of the data privacy. Any large enterprises are constantly under threat of hack attacks, as it happened with Uber and Verizon in 2017.

Luckily, the solutions are achievable, and this year we will see great improvements in the data protection services. Machine learning will be the most significant security trend establishing a probabilistic, predictive approach to ensuring data security. Implementing techniques like behavioral analysis enables detecting and stopping an attack capable of bypassing the static protective systems. Blockchain brought our attention to a new technology called Zero Knowledge Proof which will further develop in 2018 enabling transactions that secure users’ privacy using mathematics. Another new approach to safety is known as CARTA (Continuous adaptive risk and trust assessment). It is based on a continuous evaluation of the potential risks and the degree of trust, adapting to every situation. This applies to all business participants: from the company's developers to partners. Although our security is still vulnerable, there are promising solutions that can bring better privacy into our lives.

Augmented reality goes mainstream....

Before smartphones existed 10 years ago, most people would consider spending five hours daily staring at your phone as crazy. In 2018, the bent-neck trend will start to reverse itself.

The mobile game Pokémon Go has unleashed a billion-dollar demand for augmented reality entertainment, and major brands are taking notice. Thanks to the introduction of affordable augmented reality glasses, our phones will remain in our pockets and Heads Up Displays (HUD) will improve how we work, shop, and play.

HUDs, best known today as the instrument gauges that fighter pilots monitor on their visors or windshields, will become a standard in consumer eyeglasses. Imagine walking down the street in a foreign country, for example, and having all of the store signs instantly translated into English thanks to your trendy sunglasses.

AR will customize in-store experiences with mannequins that match your body type and display enough virtual inventory to rival any online site. Merchants will create AR experiences with their packaging so that demonstration videos can appear when you look at the product on the shelf or celebrity spokespeople can magically stand in the aisle to pitch the product. Virtual pop-up stores can be built to appear anywhere that crowds are gathered (in a stadium, a busy street corner, or even inside a subway). These non-brick and mortar retail locations will bring new opportunities for merchants to create engaging shopping experiences anywhere with accessible bandwidth.

Li-Fi, a new light-base wireless connection with data speeds 100 times that of Wi-Fi, will bring high-definition virtual objects into stores. With Li-Fi and AR, consumers can see limitless virtual inventory in store, at scale.

With just a wave of your hand, a car salesperson can change the model, color, and customized features of the car “sitting” on the dealership’s showroom floor. Combining real and virtual objects can enhance experiences for all out-of-home activities. Sports stadiums will be brought into the 21st century with personalized HUDs of players on the field. Imagine watching a live football game in the stadium and seeing personalized stats floating above the fantasy sports players you follow. When watching sports from home, AR has the potential to bring the excitement of life-size boxing matches into your living room. The real promise of AR is to bring people the information they need without having to ask for it.

The unstoppable freight train that is automation...

The more intelligent machines become, the more they can do for us. That means even more processes, decisions, functions and systems can be automated and carried out by algorithms or robots.

Eventually, a wide range of industries and jobs will be impacted by automation. However, for now, the first wave of jobs that machines are taking can be categorized using the four Ds: dull, dirty, dangerous and dear. This means humans will no longer be needed to do the jobs that machines can do faster, safer, cheaper and more accurately.

Beyond the four Ds, machines, robots and algorithms will replace – oraugment – many human jobs, including professional jobs in fields like law or accounting. From truck drivers to bricklayers to doctors, the list of jobs that are likely to be affected by automation is surprising. One estimate reckons that 47 percent of US jobs are at risk of automation.

Artificial Neural Network

In information technology (IT), a neural network is a system of hardware and/or software patterned after the operation of neurons in the human brain. Neural networks -- also called artificial neural networks -- are a variety of deep learning technology, which also falls under the umbrella of artificial intelligence, or AI.
Commercial applications of these technologies generally focus on solving complex signal processing or pattern recognition problems. Examples of significant commercial applications since 2000 include handwriting recognition for check processing, speech-to-text transcription, oil-exploration data analysis, weather prediction and facial recognition.

How artificial neural networks work

A neural network usually involves a large number of processors operating in parallel and arranged in tiers. The first tier receives the raw input information -- analogous to optic nerves in human visual processing. Each successive tier receives the output from the tier preceding it, rather than from the raw input -- in the same way neurons further from the optic nerve receive signals from those closer to it. The last tier produces the output of the system.

Each processing node has its own small sphere of knowledge, including what it has seen and any rules it was originally programmed with or developed for itself. The tiers are highly interconnected, which means each node in tier n will be connected to many nodes in tier n-1-- its inputs -- and in tier n+1, which provides input for those nodes. There may be one or multiple nodes in the output layer, from which the answer it produces can be read.

Neural networks are notable for being adaptive, which means they modify themselves as they learn from initial training and subsequent runs provide more information about the world. The most basic learning model is centered on weighting the input streams, which is how each node weights the importance of input from each of its predecessors. Inputs that contribute to getting right answers are weighted higher.

Applications of artificial neural networks

Image recognition was one of the first areas to which neural networks were successfully applied, but the technology uses have expanded to many more areas, including:

• Chatbots
• Natural language processing, translation and language generation
• Stock market prediction
• Delivery driver route planning and optimization
• Drug discovery and development

BLOCKCHAIN

Blockchain is one of the biggest buzzwords in technology right now. But what is it? And why are all your friends and family talking about it?

Let’s start from the beginning. The first major application of blockchain technology was bitcoin which was released in 2009. Bitcoin is a cryptocurrency and the blockchain is the technology that underpins it. A cryptocurrency refers to a digital coin that runs on a blockchain.

Understanding how the blockchain works with bitcoin will allow us to see how the technology can be transferred to many other real-world use cases.

Bitcoin is the brainchild of a mysterious person or group of people known as Satoshi Nakamoto. Nobody knows the identity of Nakamoto, but their vision was laid out in a 2009 whitepaper called “Bitcoin: A Peer-to-Peer Electronic Cash System.”

The bitcoin blockchain

The blockchain behind bitcoin is a public ledger of every transaction that has taken place. It cannot be tampered with or changed retrospectively. Advocates of the technology say this makes bitcoin transactions secure and safer than current systems.

So here are a few facts about bitcoin:

• It is not issued by a central authority.
• There is a limit of 21 million.
• Currently just over 17 million are in circulation.
• The first transaction using bitcoin is widely believed to be carried out by a programmer named Laszlo Hanyecz, who spent 10,000 bitcoin on two Papa John's pizzas in 2010.
• The identity of bitcoin creator Satoshi Nakamoto remains a mystery.
• Bitcoin has often been used to buy illicit products such as drugs.

The Internet of Things (IoT) and how everyday devices are becoming more ‘smart’

The IoT – which encompasses smart, connected products like smart phones and smart watches –is a major contributing factor in this exponential increase in data. That’s because all these smart devices are constantly gathering data, connecting to other devices and sharing that data – all without human intervention (your Fitbit synching data to your phone, for instance).

Pretty much anything can be made smart these days. Our cars are becoming increasingly connected; by 2020, a quarter of a billion cars will be hooked up to the Internet. For our homes, there are obvious smart products like TVs,and less obvious ones, like yoga mats that trackyour Downward Dog. And, of course, many of us have voice-enabled personal assistants like Alexa – another example of an IoT device.

That’s already a lot of devices, but the IoT is just getting started. IHS has predicted there’ll be 75 billion connected devices by 2020.

Google Duplex....

Google Duplex is a pretty big leap the evolution of artificial intelligence. Now, this is not to say that we’ll have human-like robots that can do the laundry or go shopping like in that movie I, Robot (at least not anytime soon). But, Google Duplex is a huge step in terms of A.I.’s ability to more naturally converse with humans. But what is it?

WHAT EXACTLY IS GOOGLE DUPLEX?

For years, businesses have been trying to create a way for people to have conversations with computers. Almost every time we call a business, we encounter an automated phone system. We have virtual assistants on our phones and virtual assistant-powered speakers in our homes. But although these computer systems can be helpful, they have their shortcomings.
In a blog post, Google notes that one of the biggest problems with these systems is that the user has to adjust to the system, instead of the system adjusting to the user. Think about all of the times you have to repeat yourself when you’re on the phone with an automated system, or all of the times that a virtual assistant hears something different than what you actually said.
Google Duplex helps with these problems by allowing the computer to have a natural conversation with a human. The A.I. system adjusts to the person, instead of the person adjusting to the system. Therefore, the person can speak normally, just as they would if they were speaking to another person. Google Duplex also makes it so the computer system sounds like a human. It uses a natural tone and uses words and phrases like “um” and “uh” just like a human person would. During a conversation, the A.I. system can also handle interruptions and elaborate.

Digital Centralization

Over the past decade, we’ve seen the debut of many different types of devices, including smartphones, tablets, smart TVs, and dozens of other “smart” appliances. We’ve also come to rely on lots of individual apps in our daily lives, including those for navigation to even changing the temperature of our house. Consumers are craving centralization; a convenient way to manage everything from as few devices and central locations as possible. Smart speakers are a good step in the right direction, but 2018 may influence the rise of something even better.

5G AND THE WIRELESS FUTURE

As the next evolution of wireless architecture, 5G will extend connectivity into all aspects of our lives. Providing high-speed access, however, will also “create massive infrastructure demand on cities,” as traditional cell towers are expected to be supplemented with a system of smaller nodes, says Jason Tofsky of Goldman Sachs Investment Banking. Tofsky also expects 5G’s growth to blur lines between technology companies and communications companies as business models naturally converge.

AI Permeation

                                 

Artificial intelligence (AI), largely manifesting through machine learning algorithms, isn’t just getting better. It isn’t just getting more funding. It’s being incorporated into a more diverse range of applications. Rather than focusing on one goal, like mastering a game or communicating with humans, AI is starting to make an appearance in almost every new platform, app, or device, and that trend is only going to accelerate in 2018. We’re not at techno-pocalypse levels (and AI may never be sophisticated enough for us to reach that point), but by the end of 2018, AI will become even more of a mainstay in all forms of technology.