Will Data Science Be Ever Automated

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July 11, 2020

Data science has seen enormous growth in recent years due to the amount of data that is being collected by organizations. Ever since the word was coined in 2011, the data science domain has exploded in nine years. However, the increase in data collection is not the only reason why data science democratized over the years. The availability of computational resources was as vital as the data itself. But, as data became ubiquitous, companies struggle to process different types of information they gather. Therefore, this led to siloed data — information being stored on databases while waiting to be analyzed — within organizations. Consequently, companies are looking for automation tools that can streamline the data science initiative in organizations. This brings us to the question: will data science be ever automated? Or can AI take over data science?

Need For Automation In Data Science

Undoubtedly, the amount of data that organizations are gathering will take years for humans to analyze. And by the time they mold the data, will it be worth to find insights into the information that was generated a few years ago? In the ever-changing world, users’ behavior is continuously changing, and thereby historical data might not be useful in every use case. For instance, people used to watch longer videos; however, today, the rise of TikTok popularity tells a different story; users are consuming short videos more often. While historical data will still be relevant, but there is a need for quickly processing information to make business decisions and gain a competitive edge.

Also Read: Amazon Makes Its Machine Learning Course Free For All

Rise Of Automation Solutions

As IoT is expected to increase in the coming years, data will only get more ubiquitous. Consequently, firms are moving towards streaming analytics — real-time insights — for gaining insights into data immediately after it gets generated. However, this requires a robust data pipeline for simplifying data analysis, which is near impossible as information comes from different sources. Nevertheless, companies are trying to streamline the process on a case-by-case basis.

Another solution that is showing the promise is AutoML — automatic machine learning. AutoML solutions are focused on automating the machine learning model selection for data scientists. Usually, professionals waste time determining which ML model brings more value to businesses. Numerous companies, such as DataRobot, H2O.ai, among others, offer superior AutoML solutions for doing all the heavy lifting for organizations. Besides, these AutlML tools can be leveraged by non-experts to build ML models and make informed decisions.

Why Data Science Cannot Be Completely Automated

Data scientists require many skills like data intuition that cannot be integrated into AutoML tools. Besides, professionals spend 80 percent of their time finding, cleaning, and organizing data. Although a tedious task, data wrangling eats up most of the time. To carry out such tasks, data scientists need skills like identifying the data source, understanding the structure of the website to crawl the data, and more. Unfortunately, automation tools can never perform those cumbersome activities. However, this doesn’t mean that machines cannot automate other tasks. AutoML and streaming analytics tools are helping companies to simplify the data science workflows, but a plethora of data science techniques are still untouchable by these solutions.

Outlook

If you are not on Mars, you must be aware of the fact that artificial intelligence doesn’t have common sense. This makes AI models ineffectual in replicating humans in a wide range of tasks. Since the data science landscape must further evolve and accomplish common sense, we are poised to witness several changes in the way we process data. For one, the self-driving car could not deliver on the hype it created and need to be revamped the way it operates. Therefore, development in the data science space is going to increase further, which would be difficult for automation solutions to catch up with the market. However, if the landscape gets matured enough to enable AI agents to replicate human-like behaviors, one can then argue that data science might be automated.

Apple Exposed! It Will Now Pay $27 Million As Fine

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Analytics Drift

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February 8, 2020

Apple for years has indulged in unfair practices for expediting its new iPhone sales. In 2017, it was reported that the firm deliberately slackens the device a few months before it releases new phones. This drew the interest of experts and users from all across the world, which led Apple to accept the claim.

However, Apple said that it adopted such practice to prolong the life of old devices. The firm stressed on the fact that due to the continuous charging and discharging of lithium-ion batteries, the phones fail to deliver peak performance. Consequently, Apple released a software update for iPhone 6, iPhone 6s, among others, to reduce the performance with the introduction of a dynamic power management system. But why didn’t the company notified the users to replace the battery?

Besides, Apple didn’t notify users about the changes it was going to make in their phones with the update, which bought the firm in the soup. Now, since Apple has been exposed, it will have to pay $27 million to France’s competition and fraud watchdog DGCCRF. The company has accepted the fine and will also publish a press release in the French language for a moth to inform stakeholders.

Irrespective of the public outrage since 2017 for its clever tricks, Apple continues to implement such practices. The organisation enables the feature as and when the battery starts degrading in newer iPhones. However, now it informs users of the decreased performance when it automatically switches the mode for avoiding unexpected shut down of devices.

“The effects of performance management on these newer models may be less noticeable due to their more advanced hardware and software design,” Apple said. Despite Apple’s rhetorics, users still question the timing of the release and believe that the company’s prime motive was to encourage them to buy new iPhones.

Will AWS Lose Its Monopoly To Azure And Google Cloud?

By

Ratan Kumar

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February 8, 2020

Cloud computing technologies have become the backbone for any organization to deliver robust products and scale their business effortlessly. As more and more companies are migrating towards the cloud, various blue-chip companies are offering their cloud services and catering to the needs of rising demands. In 2019 Q3, the global cloud infrastructure services market grew by 37% to reach $27.5 billion. And as AWS tapped into the market in 2006, it has created a monopoly in the current landscape. The report also stated that in Q3 2019, AWS has retained its dominant position with a growth of $2.3 billion, which is equal to the year-on-year increase of the next three competitors combined.

Varied Options In The Market

However, with the rise of various competitors such as Azure, IBM, Google, among others, AWS is starting to feel the heat. Such a wide range of options in the cloud market has slackened the growth of AWS; as per the report, AWS had 34% of the market share in Q2 2017 and has reduced by one percentage point to 33% in Q3 2019. Nevertheless, Azure has risen to 17% from 11% in Q2 2017.

Rise In Competition

Of all the competitors, Azure is giving AWS a run for its money. Although Microsoft is a distant second, it has matched AWS in providing superior services, and in some, it has overpowered AWS services. “We have seen a pretty big uptick in Azure, thus we can expect a big battle between the AWS and Azure. Microsoft has a robust partner program that has been assisting in accelerating its growth,” said Patrick Harr, CEO at Panzura.

Reportedly, Google top management has set 2023 as a deadline for beating Microsoft and Amazon in cloud computing. Google’s mission can be witnessed with the ramp-up of hiring senior executives for its cloud offerings. Thomas Kurian, Oracle executive, was hired earlier this year to run Google cloud.

Although Google cloud was built for internal development, now it has enhanced services for businesses. “We have transformed Google Cloud into more of an enterprise-ready company; we have all the services and enterprise companies should have,” said Kurian.

Another report evaluated the cloud computing performance and concluded that in comparison to AWS and Alibaba Cloud, Google and Azure delivered desired performance, especially outside the US. Therefore, in Asia specific, Azure retained its top spot in the region.

Azure Vs Google Vs AWS

Despite the surge in the competition, AWS has performed well by retaining its market share due to its superior security and customer service. Besides, AWS enhances the cloud platform by continually adding new features. Therefore, over the years, feature-rich services have allowed it to grow an average of 48% in the last three years.

However, with the Azure winning big deals like the $10 billion deal with Pentagon, although controversial, there could be a sign of AWS losing its shine. The resent is quite evident as Amazon challenges the Pentagon cloud deal.

Due to the fierce competition in the cloud market, Mike Maciag, CMO of Dynatrace, believes there might not be a single winner. “What I do know is the world very rarely settles on one thing. I’ve seen Microsoft come up and Google come up. In customers, we see a real desire to have the flexibility of deployment. I think people want choice,” said Maciag to a media firm.

Outlook

Currently, AWS has almost twice the market share than what Azure has; thus, Amazon might still lead the race. But Azure footprints are growing in the Asia Pacific. It may further gain momentum to close the gap quickly. And as Google is starting to show promise with Kurian, one can expect their spike as well. It won’t be straightforward for AWS to maintain its momentum throughout the world since Google and Azure are gaining prominence as well.

These 5 Technology Trends Will Shape Our Lives In 2020

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Analytics Drift

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February 5, 2020

Technology is continuously evolving and changing the way we carry out our day-to-day activities. And this year is going to be no different. Unlike in the past, in 2020, we will witness a considerable shift in the landscape as technologies like artificial intelligence (AI), Internet of Things (IoT), among others, are penetrating in several use cases. Consequently, Analytics Drift brings to you the top six technology trends that will shape your lives in 2020.

Facial Recognition

In 2019, facial recognition technology was in the news mostly due to its deployment in China and India’s announcement of building the world’s most extensive facial recognition system in the coming years. Although countries like France and the U.S. have moved to ban the technology, considering the population of countries that are embracing the technology, facial recognition has gained steam.

Besides, Europian Union is now considering to drop its plan to ban facial recognition. Sundar Pichai, CEO of Alphabet, a few weeks ago at the World Economic Forum in Davos, had supported the EU and asked governments to devise frameworks. Pichai believes regulatory robustness will be vital for businesses around the world to develop technologies while ensuring privacy.

However, irrespective of the participation of blue-chip companies like Google, Facebook, and more, the facial recognition technology will move ahead and become an integral part of our lives. This is mainly because India and China will become the driving force and bring technology to the mainstream.

Deepfakes

Deemed as a threat, Deepfakes is poised to have its play in 2020. Deepfakes will be one of the biggest technology trends after facial recognition as it has the potential to revolutionize content creators. In 2020, people fascinated with designing and filmmaking will leverage this technology for delivering superior storytelling without the need for influencers.

Consumption of short videos has seen an unprecedented rise due to the success of Tik-Tok. And now, with the introduction with more similar applications like Byte, which topped one million downloads in no time after its launch, creators will adopt deepfake for producing engaging videos.

Undoubtedly, deepfakes are more famous for their potential misuse, but the technology has numerous advantages pertaining to showcasing creativity. Yes, it is feared that deepfakes can be used to spread fake news to gain political gain during elections, but on the flip side, it can be the next wave in filmmaking, marketing, and more.

5G Technology

Competition in 5G is heating up as different telecom companies are trying to take the lead by collaborating with several governments. While in the U.S., T-Mobile and AT&T are actively working towards offering advanced networks in India, China, and the U.K, Huawei and Erricson are the prominent firms.

Despite Trump’s pressure on its allies like India and the U.K for fortifying Huawei’s participation for their 5G spectrum, these countries have allowed the Chinese firm, which is considered to be the leader in the 5G technology.

5G will offer enhanced security, decrease the latency in the networks, thereby empowering business and users to provide and avail exceptional IT products and services. Consequently, 5G will become one of the most important technology trends in 2020.

Edge Computing

Mere adopting IoT devices will not help us in streamlining our tasks. Rather, we need to process information that are being generated by these IoT devices in real time. Today, a colossal amount of data is being collected but are mostly residing in silos. Consequently, firms are failing to harness the power of data. Owing to this, organizations are willing to enable computing on edge to make quick decisions for business growth. As a result, among other technology trends, edge computing has an essential role in 2020.

Self-Driving Cars

Over the years, you must have heard about the breakthroughs in new autonomous cars, but they are yet to hit the roads. However, 2020 might be the year when self-driving cars will be functional in many cities. Autonomous vehicles have been catering to the needs of users in specific or closed environments, but companies like Apple, Aurora, Tesla, Uber, Google, and more, are gradually improving abilities of self-driving cars.

Artificial intelligence in vehicles works more like a pattern-matching instead of generalizing the learning and making the right decisions in different environments. Thus, people are critical about self-driving cars’ success. But, recent breakthroughs in reinforcement learning by OpenAI and other researches have opened up the doors for achieving true AI.

Top Cybersecurity Trends To Look Forward To In 2020

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Analytics Drift

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February 3, 2020

We witness a plethora of data privacy breaches this year, and after arduous tries to thwart malicious acts, organizations, and governments have failed to safeguard information. Cyberattacks have cost over $1 trillion to companies and have mostly afflicted small and medium scale industries. However, cyberattacks are not limited to these small firms, and negatively impacts big tech firms. Consequently, companies will have to make cybersecurity their prime initiative for ensuring streamlined workflows in their businesses.

Going forward, it is expected that the annual cost will increase to $6 trillion by 2021. To weather such storms, businesses and governments are continually attempting to protect customers’ data.

In 2020, we will witness these five key trends in cybersecurity:

Spending For Cybersecurity

Over the years, corporates have increased their investments to fortify cyberattacks by implementing new security tools as protecting users’ data is of paramount importance. In response to increased attacks, spending will further increase to limit breaches in the systems.

Many blue-chip companies have in 2019 announced the increase in their budget size for cybersecurity. This will allow them to expedite their R&D initiative for ensuring various ways of securing data.

With the rise in security threats, organizations are burning their cash to hire in developing or embracing the latest tools to defend attacks. Besides, a huge amount of the budget goes into hiring top talents from the market for helping them achieve their business goals.

Even small and medium scale companies will have to ensure they embrace cutting-edge technologies for protecting their businesses.

Regulations

Today, breaches in data are not only carried out by hackers but by organizations as well. Data is being shared among businesses without user consent for monetizing their services indirectly.

Such instance was witnessed numerous times this year as Facebook, Google, among other companies were guilty of sharing customers’ data that they shouldn’t have. Thus, regulators along with devising rules for hackers will bring new regulations on the table for organizations to restrict the sharing of sensitive users’ information.

5G Technology

With the advancement of 5G technology, accessibility of data will increase for delivering superior applications through IoT technology. Billions of IoT devices will be connected to the internet for providing automation, control, and in turn, comfort to people. Such free-flowing data will also open up opportunities for hackers to penetrate networks and misuse data.

A broader bandwidth of 5G technology can enable hackers to collect a colossal amount of information within seconds. Therefore, companies need to ensure that hackers do not get access to networks even for seconds. Besides, they will have to deploy security tools for protecting networks or act instantaneously in case of attacks.

The use of automation will be the key to shield networks among connected devices, as the classical approach of determining and then acting will be a no brainer.

Artificial Intelligence

Artificial intelligence will play a major role in both fending and penetrating databases. This cutting-edge technology is being used by hackers and organizations alike for accomplishing their goals. More than ever, firms are extensively working towards obtaining supremacy in AI to forestall attacks.

Besides, machine learning will be used for determining vulnerabilities in the systems and patch them automatically. This will enable firms to shield the networks before hackers get can penetrate and install malware.

Cloud

While the cloud is empowering businesses to innovate and effortlessly deliver products and services, it has been a hot spot for hackers to perforate and fetch information. Cloud has been orchestrating business’ operations and are more secure than premise cloud, but are prone to cyberattacks.

Consequently, cloud providers are adding many layers of security to avert threats. Public cloud vendors have a crucial role to play as firms are now mostly dependent on their services. So, we can expect major changes in cloud infrastructure in 2020 to keep it safe for various organizations.

Artificial Intelligence In Vehicles Explained

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Analytics Drift

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February 3, 2020

Artificial Intelligence is powering the next generation of self-driving cars and bikes all around the world by manoeuvring automatically without human intervention. To stay ahead of this trend, companies are extensively burning cash in research and development for improving the efficiency of the vehicles.

More recently, Hyundai Motor Group said that it has devised a plan to invest $35 billion in auto technologies by 2025. With this, the company plans to take lead in connected and electrical autonomous vehicles. Hyundai also envisions that by 2030, self-driving cars will account for half of the new cars and the firm will have a sizeable share in it.

Ushering in the age of driverless cars, different companies are associating with one another to place AI at the wheels and gain a competitive advantage. Over the years, the success in deploying AI in autonomous cars has laid the foundation to implement the same in e-bikes. Consequently, the use of AI in vehicles is widening its ambit.

Utilising AI, organisations are not only able to autopilot on roads but also navigate vehicles to parking lots and more. So how exactly does it work?

Artificial Intelligence Behind The Wheel

In order to drive the vehicle autonomously, developers train reinforcement learning (RI) models with historical data by simulating various environments. Based on the environment, the vehicle takes action, which is then rewarded through scalar values. The reward is determined by the definition of the reward function.

The goal of RI is to maximise the sum of rewards that are provided based on the action taken and the subsequent state of the vehicle. Learning the actions that deliver the most points enables it to learn the best path for a particular environment.

Over the course of training, it continues to learn actions that maximise the reward, thereby, making desired actions automatically.

The RI model’s hyperparameters are amended and trained to find the right balance for learning ideal action in a given environment.

The action of the vehicle is determined by the neural network, which is then evaluated by a value function. So, when an image through the camera is fed to the model, the policy network also known as actor-network decides the action to be taken by the vehicle. Further, the value network also called as critic network estimates the result given the image as an input.

The value function can be optimized through different algorithms such as proximal policy optimization, trust region policy optimization, and more.

What Happens In Real-Time?

The vehicles are equipped with cameras and sensors to capture the scenario of the environment and parameters such as temperature, pressure, and others. While the vehicle is on the road, it captures video of the environment, which is used by the model to decide the action based on its training.

Besides, a specific range is defined in the action space for speed, steering, and more, to drive the vehicle based on the command.

Other Advantages Of Artificial Intelligence In Vehicles Explained

While AI is deployed for auto-piloting vehicles, more notably, AI in bikes are able to assist people in increasing security. Of late, in bikes, AI is learning to understand the usual route of the user and alerts them if the bike is moving in a suspicious direction, or in case of unexpected motion. Besides, in e-bike, AI can analyse the distance to the destination of cyclist and enhance the power delivery for minimizing the time to reach the endpoint.

Outlook

The self-driving vehicles have great potential to revolutionize the way people use vehicles by rescuing them from doing repetitive and tedious driving activities. Some organisations are already pioneering by running shuttle services through autonomous vehicles. However, governments of various countries do not permit firms to run these vehicles on a public road by enacting legislations. Governments are critical about the full-fledged deployment of these vehicles.

We are still far away from democratizing self-driving cars and improve our lives. But, with the advancement in artificial intelligence, we can expect that it will clear the clouds and steer their way on roads.