How Machine Learning Can Help You Make Better Decisions?


Recent technologies have aided business organizations in retrieving massive data amounts. If interpreted correctly, it could provide valuable insight into consumer behavior, driving up sales considerably. Moreover, it gives the basis to form actionable plans. However, without leveraging the information present in this data, you can’t hope to propel your brand on the path to success. Here, Machine learning plays a significant role. With Machine Learning, businesses can now gain more scalability while improving their operation across the globe.

Benefits of machine learning in making better business decisions

There are numerous advantages that brands can gain from implementing ML into their business decision-making process. It is true that ML aids in the extraction of useful information from a massive amount of raw data. Take a look at why integrating ML into your business is a beneficial idea –

  • Predict consumer behavior

One of the most advantageous aspects of using machine learning is to predict customer behavior. By having valuable insights on purchasing patterns and behavior of the client, brands can recommend products accordingly.  Moreover, now companies can use a massive amount of stored data to get vital information on consumers.

  • Prevent manual errors

Inaccurate data entry can lead to a plethora of issues. Moreover, it is a much bigger issue than you realize. However, with machine learning’s predictive model algorithms, there is a considerable reduction in the chance of manual errors. This way, the employees can use the time saved to carry out other tasks.

  • Aids in predictive maintenance

Predictive maintenance is essentially the discovery of meaningful patterns and analyses that often remain hidden within the factory data. Most often, mining this data becomes exceedingly expensive. However, with the integration of Machine Learning, predictive maintenance is not that expensive or hard anymore. Moreover, you can also reduce the risks of unnecessary costs and sudden failures.

  • Detects spam

Did you know that businesses have often used machine learning to detect spam? With the aid of Machine Learning, it is now used to recognize spam and get rid of them. Gone are the days of using the rule-based technique to detect spam.

  • Assist in financial analysis

Integration of machine learning to assist in algorithmic trading or fraud detection is a massive milestone. Machine Learning can assess the massive quantitative data and offer valuable insights. The inclusion of Machine Learning in Chatbots in the near future is a very real possibility.

  • Helps to create product recommendations

Usage of Machine Learning to create personalized product recommendations can become particularly beneficial for eCommerce websites. Machine Learning uses algorithms to track the purchase history of consumers. Then, it is matched with the product inventory, and the discovery of patterns takes place. After that, these products are listed and suggested to consumers. It will propel them to at least browse your products.

  • Analyzes images

Did you know that you can derive symbolic knowledge by assessing images? With machine learning, it is now easy to get data from image recognition. Numerous industries can benefit from the information extracted from images. Some of these include automobiles, healthcare, etc.


These are some of the reasons why using machine learning is an excellent business approach. It not only analyzes customer behaviour and predicts valuable data but also eliminates manual labour. Moreover, keeping up with the latest technology will only aid you to keep your brand ahead of the competition. For the best experience, you must seek assistance from the best Machine Learning Company. You can consult GoodWorkLabs for any queries related to machine learning. Contact the team here.


Why Should Your Business Embrace AI? Read Details

Artificial intelligence (AI) is the most revolutionary technology in today’s world and has the ability of machines to interpret data and act intelligently. AI can carry out tasks, based on data, similar to how a human does it.  We use AI in our daily lives, such as asking Alexa for the weather report and even social media platforms rely highly on AI. buying something that Amazon recommends, and unknowingly we have made it a part of our lives.


Large corporations have already leveraged AI but the major challenges come for the small and medium-sized enterprises. In the coming days, AI is bound to play a dominant role in our lives. Many artificial intelligence companies have understood AI’s potential, and have incorporated it.  GoodWorkLabs, an artificial intelligence company in Bangalore has a team of experts who are skilled to incorporate AI into your business systems.


You must be thinking, why should your business embrace AI, and how it will help you?


Here are the top five benefits of AI that makes it beneficial for businesses around the world – 


1. Automates Customer Interactions

AI enables companies to automate any repetitive tasks many customer interactions that require human intervention. Artificial intelligence companies leverage AI to program the computer so that it responds to customers by using previous details accurately. This includes communicating via email, social media conversations, telephone calls, and online chat. Furthermore, by combining AI with machine learning, the platforms interact even better. Thus the regular tasks that can take up a lot of time and workforce are simplified by leveraging AI in the business process. 


2. Gives personalized solutions

AI helps in personalized marketing and gives preference to each customer.  A personalized approach to consumers increases engagement, customer loyalty and results in brand promotion and improving sales. AI also helps to identify patterns in customers’ buying habits and behavior. This further allows companies to craft specific offers for individual customers. Cloud-based AI apps can even find out relevant pieces of information while processing big data. 


3. Stay ahead of the competition

With AI becoming a part of our daily lives, every business in the coming days will implement it and AI will become a more affordable and common technology. So now is the right time for your business to implement AI It will not only give you immense benefits but also will attract customers to your business and build your brand.


4.AI will help in conducting market research

As AI has the ability to predict outcomes based on data, it will help in both the present day and for future needs. By implementing an AI strategy in your market research, businesses can benefit from the data procured of the market trends. If you want your business to stay ahead of the competition, you must implement them and use AI to grow.


5.AI fuels other technology trends

AI is the base on which various other technology trends are built, such as virtual reality, chatbots, facial recognition, autonomous vehicles, etc. Without AI, all these advances were not possible. AI, along with machine learning, has brought about a significant change in the technology industry. 


Now Use AI In Your Business Process. Contact GoodWorkLabs

Whether you are in the eCommerce business or any other product or service-related work, you must know how AI can help you succeed further.  Talk to our experts and understand how artificial intelligence can help you grow. GoodWorkLabs, a renowned artificial intelligence company in Bangalore, will help you figure out where to apply AI. Shoot us an email at – [email protected] to discuss further.



GoodWorkLabs Fighting COVID-19 

Hit by a pandemic, we all have changed the way we have been working and prioritising work. Almost all the businesses in the world have changed their work approach and business model to fit in the new normal in the past few months. Understanding the gravity of the situation, many corporates are now providing a helping hand to the government, health-care institutes, and the public at large by helping them fight COVID-19 in one way or the other.

GoodWorkLabs, a world-leading technology organisation based in Bangalore, India and San Francisco Bay Area, USA has always been committed to helping businesses solve complex problems using technology. During these unprecedented times, we have pledged to help create sustainable and affordable tech solutions to fight the COVID-19 crisis. Being a futuristic tech company, we are looking forward to partnering with businesses/ startups to create effectively-designed tech solutions to combat the COVID-19 problems that the world is facing today.

We believe that even if the technology cannot prevent the onset of the pandemics, it can, however, help prevent the spread of infection, educate, empower, and warn people around. We can help businesses and start-ups optimise the trending technologies to fight COVID-19 – application development, cloud, IoT, big-data, AI/ML, etc.

fighting coronavirus with tech.png

Mobile Application Development: 

GoodWorkLabs is one of the leading app development company in India. We are known for developing cutting-edge mobile applications and games on all major platforms – iPhone, Android, and Windows. With the hands-on experience in the app development industry, we have helped businesses and start-ups leverage their presence in the app store markets.

During the pandemic, the developers at GoodWorkLabs are highly motivated to use their talents and ideas in building an innovate mobile application that can help end-users be aware and safe during this pandemic.

Artificial Intelligence and Machine Learning

GoodWorkLabs comes with a vast experience of setting up an advanced centre of big data, AI, and ML technologies. We have worked with clients ranging from Start-ups to Fortune 500 companies to develop unique and helpful solutions using these technologies. We believe that big data, AI, and ML can transform business and its operations in the near future. Understanding the nuances of AI, ML, deep learning, language processing, and big data, we ensure to create solutions that are powerful and reliable backed by minutely detailed data.

Cloud and Internet of Things

At GoodWorkLabs, we have a dedicated and most skilled IoT app development team which is committed to delivering products and applications that bring change in the current times. Over the years, we have supported clients from India, the USA, and Europe in the optimization and automation of the IoT products. Seamlessly delivering the effective and ahead of time IoT products and applications is our key focus area at this moment.

Observing the current world crisis closely, we believe that the world has now truly understood the importance of digital readiness. The acceptance and usage of these digital technologies will help us be aware, ready, and fight the current and future pandemics. It is essential for the companies, corporates, and start-ups to focus on building necessary digital infrastructure and help the community and people stay safe and aware. We are in the times when we should take an approach where technology is used for people-centred problems.

In this regard, we are looking forward to partnering with businesses/start-ups to create effectively-designed tech solutions that combat the COVID-19 problems the world is facing today. Let us together make a difference and enable a COVID free world! Connect with us at [email protected] or call +91- 9863077000 and read about our service offerings in detail here.


How Can AI And ML Help You Build Trending Mobile Applications

Enough has been spoken and heard about artificial intelligence and machine learning. Most of us are aware of these technological jargons. We are in a world where we must have come across these technologies on a daily basis, but little do we know deeper about it. From tech to voice to face enabled devices, we all have witnessed a dramatic evolution of technology in the last decade. It did not only contribute towards the transformation of the internet and software industry, but also the lives of individuals – you, me, and us!

Technologies related to AI and ML is expected to grow in the years to come. Even many social media platforms are today investing ample amount of money in the development of AI techniques to keep their audiences hooked to the platform. Over-viewing the mobile app industry, it is not a hidden fact that today most of the mobile applications are built on AI and ML technologies. Today, we have mobile applications for all our activities – shopping to dating, food to fashion, travelling to surfing, etc.

How Can AI And ML Help You Build Trending Mobile Applications

According to a report by Statista, the global artificial intelligence market is expected to grow greatly by generating 118.6 billion revenue in 2025. Viewing that, the future of AI and ML technology looks very promising. Therefore, it is a great time to incorporate some AL and ML techniques in your mobile application. Let us look at how two of the leading the AI and ML techniques can help build a trending mobile application:

Predict User Behaviour 

You must have used Amazon or Myntra. Did you get what we are hinting at?

Yes, those suggestions, recommendations, and notifications. They provide you with the most similar products you are looking for. How do you think this happens? Is there is a fairy in the app? Yes, there is and she exactly knows – what you are looking for, what you like and what you don’t, what excites you and what makes you add the items in the cart. Well, no points for guessing, she is AI and ML.

AI and ML mobile applications developed by top AI and ML app developers help the businesses and their marketing teams to understand customer behaviour and psychology. The insights drawn provides information on customer choices, preferences, buying patterns, and budgets by capturing data such as age, location, gender, buying frequency, spending capacity, etc. It is the perfect integration of in-depth data learning and observing the user behaviour across all devices that help create a 360o view on customers. The data so collected enables the brands to approach each customer group and deliver products that perfectly fit their individual needs.

Virtual Assistants 

Hey Siri! “Go on, I am listening” – Siri (Well, there’s someone ‘listening’)

That is how we connect with our smartphones these days, don’t we? Siri, Alexa, and Google, all are changing the digital way of communication with our phones and mobile applications. The technology helps you use your phone or a mobile application while you are performing some other task. It has made the user experience much seamless and fruitful.

This technology has further strengthened the trend of online shopping. Today, 95% of online shopping in the world is made through voice commands and that shouldn’t be a surprise. Industry to industry, virtual assistants are greatly impacting and disrupting the way consumers purchase and retailers sell/market.

Are you still wondering how can you invest in AI and ML? Lets us connect to understand your requirements and help you with an AI and ML based mobile application. Connect with us at +91- 9863077000 or [email protected].



Three Technologies That Will Foster After The COVID-19 Pandemic 

The last decade introduced the world to the digitization of many sectors. This helped the global trade to increase worldwide as many developing and emerging countries became important trading partners and potential sales and development markets. Digitization has helped us to be more connected and perform our daily tasks more effectively. It has made the world a global village and people global citizens.

However, the economies built in the previous decade came crashing to the ground in the last few weeks as COVID-19 pandemic hit the world. While the pandemic has had a great impact on the global economy, it taught us how to fight and improve the current condition using technology. It has laid a new pathway by disrupting our lifestyles by enabling contact-less and virtual experiences. Even though the technology cannot prevent the onset of the pandemics, it can, however, help prevent the spread, educate, empower, and warn people around. Today, these technologies are emerging more than ever – mobile, cloud, analytics, robotics, AI/ML, 4G/5G, and high-speed internet.

Three Technologies That Will Foster After The COVID-19 Pandemic 

Let us look at three technologies that are disrupting our lifestyle each day during this pandemic:

Artificial Intelligence and Machine Learning

From tracking the travel history of COVID-19 patents to analysing the symptoms of people exposed to the infection, the applications used by many governments do it all. These applications use chatbots to gather information from people, and the technology used in these applications is that of AI and ML. This enables the government to collect reliable information much easier and faster without any human intervention.

The advent of more such mobile applications and software will help ease the lifestyle of customers.

Extended Reality

Augmented and virtual reality is surely a boon in the world of lockdown and quarantine. This technology can be used in providing more meaningful and real experiences for people. The technology can help you see the world while you are locked in your home. This experience will change the way we travel, work, and relax. For instance: Realty brands can focus on using AR/VR videos to target their audiences by helping them take a walk-through the project while they are seated in the comfort of their home. This is an example of how a sector can use the contact-less experience to their advantage.

Cloud and Internet

The last few weeks have seen a great transition in the way the workforce can function. Companies got to believe that remote working and work from home concepts can be of their advantage. The transition to work from home and remote working has increased the dependency on cloud and internet infrastructure. The usage of this technology is set to remain the same even post lockdown and pandemic as many companies are moving towards welcoming a ‘hybrid’ way of working. This will increase the demand for teleworking applications and software for the team to be connected and interactive.

Talking about the internet, technology has changed the sector of education. It has enabled kids to learn and study from home using applications that require an active internet connection to connect with their peers and teachers. For times to come, e-learning will be an accepted norm for the parents and teachers alike.

The COVID-19 pandemic has demonstrated to the world that importance of digital readiness. The acceptance and usage of digital technology will allow the business and individuals to continue their work and chores as usual during the pandemic. The companies at large will focus on building necessary digital infrastructure by using the latest technology to stay connected with their employees and customers. The pandemic has increased their market competition by many folds, therefore businesses will have to take an approach that is human-centred and inclusive using technology governance.


15 Mind-Blowing Stats about Artificial Intelligence

Are you looking to incorporate AI tech in your existing business model or are you generally curious about this technology? Get an insight into how Artificial Intelligence technology increases the productivity of the business and accelerates performance.

In either case, there are some mind-boggling essential facts that you must know about AI. 

Starting with the basics, we are quickly briefing you about this technology.

In the current industry scenario, some industry sectors are at the start of their AI journey, while others are veterans. 

Artificial Intelligence and Machine Learning are now considered one of the significant innovations since the microchip. 

We have come a long way since they set foot in the market. Machine Learning used to be a fanciful concept from science fiction, but has now become a reality.

Neural networks paved the way for “deep learning” breakthroughs in Machine Learning. While the previous Industrial Revolution has harnessed physical and mechanical power, this new revolution will harness mental and cognitive capacity. Many experts in the field believe that Artificial Intelligence Technology is ushering the next “Industrial Revolution”. 

Someday, not only manual labor will be replaced by computers, but also intellectual labor. But, the question is how exactly is this going to happen? Or has it already started?

By 2025, it is projected that 463 exabytes (EB) of data will be produced globally each day — equivalent data in 22 crore DVDs per day. That’s huge!

How Artificial Intelligence and Machine Learning will impact our day-to-day lives in times to come?


1) AI into Automated Transportation

Have you been flying on an airplane recently? If so, you’ve already experienced the automation of transportation at work. Such modern commercial aircraft use FMS (Flight Management System) to control their location during flight, motion sensors, a combination of GPS, and computer systems.


2) Self Driving Cars and AI

It is more difficult to leap into self-driving car business. Since there are more cars on the road, many obstacles to avoid, and the traffic patterns and rules restrictions which we need to adhere to. 

According to a report of 55 Google vehicles that have traveled over 1.3 million miles overall, these AI-powered cars have even exceeded the safety of human-driven cars.

With Google Maps’ assistance on your smartphone about location data, we have already conquered the GPS forefront. A similar GPS is used in these cars, which can calculate how quickly the device is traveling by comparing the position of a device from one point in time to another.

It can decide how slow real-time traffic is. It can combine information with user-reported incidents to create a traffic image at any given time. Maps will determine the fastest route between you and your destination based on traffic jams, construction works, or accidents.

What about the ability to drive a car? Well, machine learning enables self-driving vehicles to adapt instantly to changing road conditions while learning from new road situations at the same time. Onboard computers can make split-second decisions much faster than well-trained drivers by continuously filtering through a flow of visual and sensor information.

All this is based on the very same machine learning principles used in other industries. You have input characteristics (i.e., real-time visual and sensor data) and output (i.e., a decision on the next actions for a car). Amazing, right?


3) Cyborg Technology

Our minds and bodies are less than perfect. Technology will improve to the extent that we can increase some of our computer weaknesses and limitations, enhancing many of our fundamental skills.

But, wait before you start to imagine dystopian worlds of steel and blood, consider for a moment that most people walking around are in a certain way “cyborgs.”

How many people do you know that without your trusty smartphone would survive the day? For contact, navigation, information learning, receiving important news, and a host of other things, we still rely on these handheld computers.


4) Taking Over the Dangerous Jobs

Bomb disposal is one of the most dangerous jobs. Today, among other things, robots (or more technically drones) take over these risky jobs.

Currently, most of these drones need to be operated by a human.

But as machine learning software is evolving in the future, robots with artificial intelligence would do these tasks entirely. This technology has already saved thousands of lives on its own.

Welding is another work outsourced to robots. This type of work produces noise, intense heat, and fumes toxic substances.

Such robot welders would need to be pre-programmed to weld at a specific position without machine learning. Improvement in computer vision and deep learning, however, has allowed greater flexibility and accuracy.


5) How AI helps in nursing elders?

Everyday tasks can be a struggle for many senior citizens. Many have to hire help from outside or rely on members of the family. 

For many families, elder care is a growing concern. In-home robots can support elderly relatives who don’t want to leave their homes.

This approach provides more flexibility to family members to handle the care of a loved one. The in-home robots can help seniors with daily tasks and allow them to stay as long as possible independent and live in their homes, improving their overall well-being.

Health and Artificial Intelligence scientists even have infrared-based systems that can identify when an older adult falls. Scientists and medical specialists can also track sleeping, feeding, decreasing mobility, fluid intake, chair and bed comfort, urinary frequency, restlessness, fatigue, food and alcohol consumption, and many more.


6) AI into enhanced Health Care

Hospitals might soon put your well-being in the hands of AI.  Hospitals that use machine learning to help treat patients have fewer accidents and fewer cases of hospital-related illnesses, such as sepsis.

Artificial Intelligence also tackles some of the most intractable problems in medicine, such as helping scientists to understand the genetic diseases with the help of predictive models better.

Initially, health professionals must manually check the information reams before they diagnose or treat a patient. High-performance computing GPUs have become primary resources for deep learning and AI applications.

Deep learning models can offer real-time insights and, in conjunction with an abundance of computing power, help healthcare professionals diagnose patients more quickly and accurately, create innovative new drugs and treatments, minimize clinical and diagnostic errors, predict adverse reactions, and reduce healthcare costs for clinicians and patients.


7) Artificial intelligence is capable of changing the business forever

It is a promise to take care of all the tedious things that employees are already doing, freeing their time to be more imaginative, and doing the job that machines are unable to do.

Today, emerging technology is mainly used by large companies through machine learning and predictive analytics.


Here’s a look at AI’s current county and what lies ahead:-

  1. Nowadays, only 15% of companies use AI whereas 31 percent said it was on the agenda for the next 12 months.
  2. For those companies already in the Artificial Intelligence range, high-performing companies have said that they are more than twice as likely to use technology for marketing as their peers (28% vs. 12%). Unsurprisingly, data analysis is a key Artificial Intelligence focus for businesses, with on-site customization being the second most frequently cited use case for AI. 
  3. The survey respondents have described customer personalization (29%), AI (26%), and voice search (21.23%) as the next dominant marketing pattern. These top three responses, totaling 75% of all AI applications, indicate that AI is more widespread and accessible than the respondents are aware of. 
  4. 47% of digitally mature organizations or those with advanced digital practices have established a specified AI strategy. 
  5. Business leaders said they agree that AI will be fundamental in the future. In reality, 72% said it was a “business advantage.” 
  6. Of those who have an innovation plan, 61% said that they are using AI to find information gaps that would otherwise be overlooked. Just 22% said the same thing without a strategy. 
  7. Consumers use more AI than they know. While only 33 percent claim that they are using AI-enabled software, 77 percent currently using AI-enabled products or phones. 
  8. 38% of customers said they believed that AI would boost customer service. 
  9. Out of 6,000 people surveyed, 61% said they thought AI could make the world a better place. 
  10. In a survey of more than 1,600 marketing professionals, 61%, regardless of the size of the company, pointed to machine learning and AI as their company’s most significant data initiative for next year. 
  11. The effect of AI technology on business is projected to increase labor productivity by up to 40% and allow people to make more productive use of their time. 
  12. The largest companies, those with at least 100,000 employees are most likely to have an AI plan, but only half of them have one. 
  13. More than 80% of the executives see AI as a strategic tool. 
  14. Voice assistants are incorporated into a wide range of consumer products; almost half of US adults (46%) are now using these apps to communicate with smartphones and other devices. 
  15. When asked about requirements for marketing software providers to have native AI capabilities, more than 50% of the communicators said it was essential or appropriate to do so. 


Winding Up

As many people have rightly noted, the idea of Artificial Intelligence is not a new one. It’s been around since the very early days of computing. Pioneers always have invented ways to build smart learning machines.

At present, the most promising method for AI is the use of applied machine learning. Instead of trying to encrypt machines with everything they need to know beforehand (which is impossible), we want to allow them to learn, and then learn how to learn. 

The time for machine learning has arrived, and it is in the process of revolutionizing all of our lives.

Liked our content? Then visit us today at GoodWorkLabs and learn more about us. For any feedback or suggestions, you can comment in the drop-down section.




When we talk about the food industry, we also know that it is the biggest and most important sector in the industrial world. The food and Beverage industry is increasing in scale at a high pace in terms of technology. With the addition of Big Data, however, the industry has reached a whole new level.

This new technology has permitted the food industry to improve at a breakneck capacity. Technology, with the added benefit of Big Data, has developed the procurement of insights from data. Not only from data, but also from the marketing campaigns and more interactive development to create an innovative product.

It is not wrong to say that Big Data has helped the food and beverage industry scale new heights.


Food and Beverage Industry, and Big Data


The food industry, under Big Data, is witnessing growth at a high pace.

In fact, as per a report by McKinsey, food retailers witnessed an improvement in their profits by almost 60% with the use of Big Data.

The F n B industry is getting more organized with real-time insights and taking note of many important points.

All this is made possible through Big Data, allowing companies to get plausible leverage for their services.

Even with Big Data though, there is one critical challenge-

The F n B industry today has a shallow degree of customer loyalty, making it more competitive and fragmented. The industry did not depend on the available data. Instead, they relied on a traditional reporting format.

However, the preferences of a customer are bound to change pretty regularly, making it very difficult to keep pace with them. This has led to a revolution of sorts in the food and beverage industry.

Big Data helps to analyze all the structured and unstructured data. This data comes either through modern sources or even traditional methods. Once collected, this data provides many insights for shopping trends, market development identification, and customer behavior.

Big Data analysis provides a competitive edge to the entire food and beverage industry. Many big names are taking advantage of Big Data to stay ahead of their competitors.


It is evident with the impact of Big Data on the food and beverage industry that there are several benefits on offer. With such a dynamic sector under focus, Big Data proves its mettle through the following benefits-


Customer demands today change with every passing second. This makes it difficult for the food and beverage industry to meet their expectations consistently. Big Data, however, can provide the data analysis required and provide insights on changing the behavior of customers.

Through the collected ideas, efforts to improve market efficiency get easily implemented.

With the development of technology online and on smartphones, customers now have a wide array of options to address their needs. The advancement has led to the food industry to collect the maximum data for their choices.

From the particular food items and change in their preferences to order value, there is data for everything today.

It is simpler than ever to grab on the customer information to help get potential value to businesses. With significant growth in this industry over the last decade, the total cost from mobile and online technologies have proven to be immensely useful.

The utility has not only been in monetary terms but also spans through the ease of collecting information to improve the marketing campaigns for companies drastically.


When it comes to the most technologically innovative area in the food and beverage industry, it has to be data analytics. As the industries become more and more focused on the customers, there has been a constant flow of ideas to improve data quality.

This data is used widely to modify product offerings and customer demand, as well. In such a scenario, data analytics has proven to be the core promoter of the food and beverage sector. Presently though, the efficiency and effectiveness of data are not suited well enough to achieve desired results.

The lack of this point has made it all the more important to innovate and open up new doors related to the subject area. Innovations will permit companies to get better insights for the benefit of brands and get help to manage their products.


The bonds of restraint will help you as a business to explore many new options through the help of Big Data. It is the perfect way to boost your sales and business efficiency.

The data-driven nature lends you the flexibility to go with a new trend, thanks to better analysis of data sales.

A better understanding of restaurants with their customers is made possible with better analytics and will improve the brand value of your company.

The improved practices in the food and beverage industry can have a lot of influence on the Big Data sector. An individual restaurant can understand its competition in a better place. Initially, it is going to take some time. But then you will start getting proper data while also tracking your competition’s growth.

You will have every opportunity to get a competitive edge with this improved method of marketing.


It is effortless to track purchase decisions through Big Data for wholesaling. If a product gets picked at an increased rate, you will get a lot of help to increase the sale of your business.

For instance, if the sale of a particular type of food on a discount in a region gets monitored, the data collected can be analyzed in terms of profit and an increase in the purchase of this specific product.

You will get a set of data to help you in setting the quality of the food and beverage offerings. With the help of this data, the sale and marketing plans can be executed efficiently by the companies for their products.


Big Data plays a crucial role in the overall quality of food and beverage. Companies in the sector can effortlessly control the quality of food supply through aggregate data. Customers expect to have the same taste and quality every time they go for a particular product.

Any difference negatively impacts their preference and brands end up losing their customers. In such situations, data collection is your best option. The data collection will regularly update you on the quality of food.


Big Data has eased restaurants and companies to develop more advanced forms of marketing to engage global customers. Adding to that, companies can use the various social media platforms already in use by a huge number of people.

Their reviews and testimonies have the potential to take your business to a whole new level.

Need Big Data solutions for your Food & Beverage business? Get in touch for tailored Big Data solutions for your business at affordable prices.









Better Medicine through Machine Learning: What’s real, what’s artificial?

Artificial Intelligence is a part of our day to day lives.


Advancement in the field of AI might be the latest buzz in the tech world but AI in itself is not the new kid in the block. The first instances of AI can be found back as late as the 1960s. It was during this time that researchers and experts of cognitive sciences and engineering first started to work on a smarter and more responsive technology.

The idea was to create a computing language that like humans could learn, reason, sense and perform. With the advancement in AI, a subfield came to the forefront which we call the ML or Machine Learning.

It developed as researchers started to use numerical strategies coordinating standards from optimization computing and statistics thus teaching the programs to perform the jobs naturally by processing the data at hand.

Since then a lot has happened in the field of AI, especially in recent years. Artificial Intelligence is involved in our day to day lives. Some of the notable works remain to be gaming and transportation sector being driven by computer vision and planning and phone-based conversational apps that operate through speech processing. Besides that, we have also seen significant progress in works like language procession and knowledge representation as well.  

Better _medicine_machine_learning

In this write-up, we will focus on the advances made by AI and Machine Learning in the Medical field. We will discuss the various ways in which we can use ML in that respect.


There is a lot of scope for ML in medical practice especially when it comes to the diagnosis of the patient. Experts in the field believe that the medical imaging sector will have a significant impact. For example, ML algorithms that can naturally process 2 or 3-dimensional scans to confirm the condition and follow up with the diagnosis. Often these algorithms use deep learning to influence the image data to undertake the respective tasks. Deep learning is of great use in the field of ophthalmology. Recently a healthcare automation company named as the IDx developed a software that can scan images to detect signs of diabetic retinopathy. It is cloud-based software that has already received a green signal from the FDA (US Food and Drug Administration). This kind of software can be of great help in places which are low on resources and yet have a bulk load of complex imaging data to process.   Deep learning based software has also proved to be helpful in radiology as well.


The classification and description of diseases and their subtypes that are used today are solely based on the symptoms related observations that were recorded centuries ago. With the advancement in technology, the time has come to opt for a more data-driven approach for classification and diagnosis of diseases.

Some researchers have been working in this respect for diseases like allergy and asthma. They assessed the data from the Manchester Asthma and Allergy Study (MAAS). After analyzing they were able to recognize novel phenotypes of childhood atopy. They have further their research and identified clusters of component-specific IgE sensitization through hierarchical cluster analyses. This according to them will be able to detect the risk of childhood asthma more efficiently.

Experts believe that there is ample scope of using the same data-driven technology to aid in the diagnosis of other diseases as well. Using Machine Learning to detect new actionable disease subsets will be instrumental in the advancement of precision medicine.    


Fluctuating healthcare costs, morbidity, and mortality, all are the by-products of the wrong medication or rather medication errors. All these errors are identifiable through expert chart reviews, the rules-based approach of EMR screening, and use of triggers and audits of events. But all these are faced with a number of hurdles such as time consumption, suboptimal specificity, and sensitivity, high expenses, etc.

On the other hand, anomaly detection techniques that use ML start with developing a probabilistic model. This model will ascertain what is likely to happen in a given context by using historical data. By utilizing that model a new approach within a particular context will be shown as an anomaly if the probability of that happening is at a lower percentage. For example, the patient’s characteristics can be studied after the particular dose of a certain medication to understand the anomaly.   

This kind of technology is already in use. MedAware is a commercially used system that detects medication errors with the help of anomaly detection.


There is no denying that ML has great potential to alter the traditional rules and methods of clinical care. But one has to be absolutely sure about the technology used before implementing it. Using the wrong methods can be harmful and even be fatal to the patients.

Let’s take an example: Someone wants to foretell the risk of emergency admissions in hospitals by utilizing a model that is trained on past admissions information and data of patients with varied symptoms. Generally, admissions depend on the availability of beds in a medical center, medical insurance of the patient and the reimbursement. The trained model might be able to work out a population level planning of resource to use it for individual-level triage. But it can falsely identify a person and determine that he/she does not require admission. So the algorithm has to be fully tested and trained to avoid such mistakes.

Another downside of naive implementation of a deep learning algorithm in medical care is to acknowledge associations in the training datasets that are not completely related to clinical prediction. These are not even relevant externally. Methods that influence causal elements are less inclined to such overfitting. Faithful development of training datasets and various external approval efforts for each model can give some affirmation that ML-based models are legitimate. These developments need to be validated by medical data scientists so that there is absolutely no risk to the patients. ML can be used for medical care and can benefit many patients. So there is no need to avoid ML. The medical practitioners should learn to understand the idea and technology and use it for the improvement of patient care.


How Machine Learning Gave ‘Thanos’ a Soul in Avengers Endgame

The universe belongs to Marvel.


With the movie spectacle of the decade running in theatres all over the world, it is not wrong to say that Avengers Endgame, the last movie in a decade long journey of a shared cinematic universe has surpassed all expectations.

From some characters like Captain America, Iron Man and Black Widow making their final appearances in the movie, the scintillating reviews from both audiences and movie critics alike have increased the potential of making it Hollywood’s highest grossing film ever, an accolade which presently lies with James Cameron’s Avatar.

While there is no denying that Marvel Studios has been supremely successful in the execution of a cinematic universe, the absence of villains that could be a real threat to the Avengers was a point where the makers could not cut through successfully. Until Thanos.




Other than Loki, played by Tom Hiddleston and Killmonger, portrayed by Michael Jordon, no single antagonist could hit the hearts of fans with as much impact expected. Not a proper recognition through the span of 22 movies.

Thanos, the purple-faced alien nemesis, made up for all of them with a brilliant screen presence, thanks to the fantastic Josh Brolin who blew life into the character both in Avengers Infinity War and now in Endgame too.

But was it just Brolin that made Thanos the perfect nemesis to the Avengers? No. Marvel Studios have Machine Learning to thank.

Apart from a revolution in CGI, the fact that Thanos was able to display perfect emotions on screen was what made him a force to reckon. Through Thanos, the stakes were high not only in the storyline of both the movies, but they were also huge for the makers, as they had the gap of an excellent villain to fill.

It was important to put emotions on a CGI character’s face to make him resonate more with the audience. This involved portraying the recognizable expressions of Josh Brolin on the Mad Titan’s face.

To achieve this, Digital Domain, one of the digital effect firms for the movie, used a sophisticated machine learning software named Masquerade to make the performance of motion capture more realistic and natural.

The entire process started by correctly putting a hundred to hundred and fifty track dots on Josh Brolin’s face, to be captured by a couple of vertical orientation enabled high-definition cameras.

The scan wasn’t required to provide high-quality results, but a pretty generic render of low quality. This initial rendering then was fed as input to the machine learning algorithm that used from many high- resolution facial scans by a vast variety of expressions.

The Masquerade software opts for those low resolution renders and automatically figures out the high-resolution face shape to be the perfect solution for the screen. If the answer did not seem accurate enough, the team would then tweak things a bit to arrive at a better solution.

These tweaks involved instances like raising the brows higher or a little bit of lip compression, which went back into the system and were then learned by the machine learning algorithm.

Subsequently, further results through the low mesh came out better, but all of this was just a single step. The next step in the process is known as direct drive, which plucked the high- res face mask function to place it on the villain’s character model.

If there were no machine learning system like Masquerade in place, the Visual Effects team would require to change the expressions manually through animation, where the results were surely not to be as impressive like the ones coming with the help of Masquerade. It would have been a time- consuming process too.

However, there are also other advanced techniques like FACETS, used for facial tracking in Avatar and even the Planet of the Apes trilogy.

It is quite clear that if you are not using machine learning in your software to enable better CGI and VFX, you are never going to get the final outputs as you expect them to be. In the times ahead, technology will be used more for things more than faces.

To cut a long story short, expect machine learning to have an integral role just about anywhere when it comes to special effects and design.

To get the best machine learning systems/solutions for your own business or company, let us help you with the best in class recommendations & solutions.

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Interesting Facts About 2019 Elections And The New Age Technology

India’s most anticipated events of 2019 — General Elections of Lok Sabha is right here.


From political campaigning to social good, AI seems to have been actively used for data prediction & accuracy. On the other hand, New Zealand which will be hosting the election for Prime Minister in the year 2020. For this very election, Sam is the frontrunner. He has the right amount of knowledge on education, policy, and immigration and answers all related questions with ease. Sam also is pretty active on social media and responds to messages very quickly. When it comes to being compared with the other politicians; however, there is one huge difference- Sam is an AI-powered politician.




Sam is the world’s first Artificial Intelligence (AI) enabled politician developed by Nick Gerritsen, an entrepreneur driven by the motive to have a politician who is unbiased and does not create an opinion based on emotions, gender and culture.

This is just one of the many instances where AI is playing an increasingly crucial role in politics all over the globe. Political campaigns have been taking the help of AI for quite a long time now.


The most significant advantage of AI in politics can is its ability where it can accurately predict the future. Political campaigns make the use of machine learning, social media bots and even big data to influence the voters and make them vote for their political party.
Apart from just wins and losses on the political front, AI presents with more obvious implications in decisions and policy making. Reports claim that deep learning, an essential aspect of AI, can look after issues that relate to executing the schemes laid down by the government.

The technologies that use AI for social good are also on the rise since some time now. This is why the arrival of AI politicians is not very surprising. As to how big data and deep learning help it all out, we will be discussing it further below.


With such a flurry of content on all social media platforms, it is understandable to get confused in determining which political leader is going to have the best interests of the nation at heart. You will be surprised to know that the leaders know how you think and also what you expect from them. Elections have a lot to do with psychology other than just indulging in political games.
While going through the Internet or mobile apps, you must have noticed that there is a pattern to the kind of videos which pop on your window. Some of these pop-ups are also related to the elections and candidates located within your vicinity. This pattern is backed up by reason.

The Lok Sabha election of 2019 may or may not play a decisive role in creating a bright future of India, but it is a witness to the fact that the use of technology is driving the people to act in a certain kind of way. It essentially is India’s big data election which is underway through several algorithms, analytics, and obviously, Artificial Intelligence.

Though they are not exactly visible in the election, they are more of the channels which are always present when it comes to tracing the online actions of voters, political messaging, customizing the campaigns and create advertisements targeted at the voters.

The Congress political party has provided all its candidates with a data docket which can track on-ground activities by their Ghar Ghar Congress app. The data dockets have information regarding households, missing voters, new voters, and even the local issues which plague the concerned constituency.

At the other end, the BJP looks far ahead in its quest to appeal the citizens to keep their party in power for another tenure. In states of the North, the party is a host to more than 25,000 WhatsApp groups. Ironically though, by the time Congress thought to compete with it, WhatsApp changed their policies, leaving the Opposition out to dry.

The optimal use of neural-network techniques, more often referred to as deep learning allows the political parties to have an unbeatable ability and have a fact-based study as to how such kind of data.

We at GoodWorkLabs are enthusiastic about creating such offbeat solutions using our expertise in AI, ML, Big Data, RPA. If you’ve any requirement which is this interesting & complex in nature, drop us a line and let us help you with a robust solution.

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