The Power of AI in Biotechnology: Revolutionizing Innovation

Artificial intelligence in biotechnology can speed up drug discovery, deliver analytics, accurately diagnose medical conditions, edit gene structures, develop personalized medicine, and do much more to help mankind. Here, we’ll discuss the role and importance of AI in biotech industries.  The role of AI in biotechnology is gaining momentum in recent times. The biotech industry is redefining its processes using AL and ML technology to get better, faster, and more accurate results. Be it the pharma industry, healthcare, animal husbandry, or agriculture, AI and biotech are setting the stage for greater advancements and innovations.  Biotech or biotechnology is the use of technology in biology. Pharmaceutical companies are the major players in this industry, though others are catching up quickly. Statistics show that the pharma industry will spend around $3 billion on AI in drug discovery by 2025. 82% of industry experts opine that the industry will continue with the digitalization of its operations during post Covid-19 pandemic.  The power of big data and data analytics can revolutionize the biotech industry on various fronts. From using machine learning algorithms to natural language processing (NLP), neural networks, and advanced robotics, AI pushes the boundaries and creates more possibilities to improve the quality of life. New biotech companies are entering the global market, using artificial intelligence as an integral part of their business. Reports show that the biotech industry received $2.4 billion in venture funding by December 2022. Many rely on AI Biotech companies and solution providers to integrate the systems with advanced technology and use AI in all verticals.  In this blog, we’ll read about the role of AI in biotechnology and how applied AI is helping biotech companies to drive innovation and be ready for future developments.  Can AI and Biotech Save Lives? Technically, yes, artificial intelligence and biotech can save lives. This is done by helping researchers create better quality drugs (with fewer or no side effects), correctly diagnose complex ailments in the healthcare industry, identify and change gene patterns to prevent life-altering diseases, etc.  Most importantly, combining AI and biotech allows different players in the industry to share information and work together irrespective of geographical restrictions. They can create AI-based pharma (medical) tools and find solutions to save lives.  How is Artificial Intelligence Transforming the Biotechnology Industry? The advancement in the biotech industry now relies on big data, AI, and ML technologies. Many experts and top-level executives of leading biotech and pharma companies have said that 2023 is when AI in biotechnology will bring revolution and value and also fit for the purpose it is being used for.  AI’s role in biotechnology is not limited to automating repetitive tasks or structuring data flow. Artificial intelligence can help in research, day-to-day work, data analytics, drug manufacturing, and much more. It speeds up the entire process by assisting human researchers to process large datasets accurately in a short time. Diagnosing and Treating Mental Illness  The growing cases of mental illness have been a cause of concern in the last few years. Mental illness affects around 13% of the world’s population. The Covid-19 pandemic has led to an alarming increase in depression and anxiety. People with depressive symptoms went from 193 million to 246 million (28% increase), while anxiety disorders showed a 25% increase (298 million to 374 million).  Artificial intelligence can help doctors and scientists detect early signs of mental illness and use preventive medication or treatment to help patients feel better. Treating mental illness is hard because the symptoms exhibited by patients are varied and not universally applicable. However, advanced AI programs can observe the brain waves of patients to recommend the best antidepressant therapies for each patient.  AI algorithms are being used to study and identify the behavioral loops in addicts to determine the chances of relapse so that physicians can take the necessary action. Furthermore, AI can help create personalized medicine that will be more effective in treating the patient. However, there is a lot more research to be done in this field to help people deal with mental illness and lead better lives.  Creating 3D Protein Structures  Proteins are one of the four most important macromolecules essential to building life. The scientific community has been using X-ray crystallography and nuclear magnetic resonance to identify protein structures. They have added 187,000 identified structures to the database. However, the process is slow and laborious. Many more proteins are yet to be identified.  A UK-based team of AI researchers created AlphaFold, a machine-learning platform that uses the existing database to predict protein structures and build 3D models. The tool takes only a small fraction of the time takes originally to complete the job, that too with greater accuracy. This can help biotech companies identify more proteins quickly and use the vital ones in developing effective drugs. Diseases like cystic fibrosis and muscular dystrophy can be treated with the help of this technology.  Gene Coding Identification  Machine learning in Biotech can be researchers build powerful models to study and understand human genomics. The next-gen technology used by biotech companies helps sequence a gene in less time and creates an alternative method to homology-based sequence analysis.  CRISPR (clustered regularly interspaced short palindromic repeats) can electively modify and edit the DNA or genes of living organisms. This allows scientists to identify and destroy the DNS from bacteriophages that cause infections and diseases. The technology can also help create personalized medicine based on the genome of the patient. This can be a game-changer in treating hereditary diseases and identifying the probability of a patient inheriting a family disease or illness.  Lab Assistants  AI in biotech is also being used to simplify tedious tasks. Artificial intelligence programs are acting as lab assistants and managing backend work as well as complex tasks like data analytics. H2O.ai is a fast, accurate, and open-source big data analytics platform that allows people to use its statistical models to identify patterns in datasets. Even though the company caters to many industries, many other AI platforms cater exclusively to the biotech, health, and pharma industries.  Another role of AI as a lab assistant is the use of robotic devices in research centers, healthcare

Read More

Breaking Down Language Barriers: How AI is Revolutionizing Translation

In today’s world, the ability to communicate effectively across multiple languages has become more important than ever. As businesses continue to expand their global reach, the demand for high-quality translation services has increased significantly. Fortunately, advancements in artificial intelligence (AI) have led to the development of sophisticated translation technologies that are transforming how we communicate across different languages. Here, we will explore how AI is revolutionizing translation, the benefits of using the latest AI powered translation technologies, and the potential impact on the future of communication. The Evolution of Translation Technology Translation technology has come a long way. Initially, translation was done manually, with human translators spending hours poring over texts and dictionaries to translate them from one language to another. However, this method was slow and expensive and often resulted in inaccuracies due to the human element involved. With the advent of computers, machine translation was introduced in the 1950s. Machine translation uses software to translate text automatically without human intervention. However, the quality of the translations produced by machine translation was often poor due to the limitations of the software at the time. In recent years, advancements in Artificial Intelligence and machine learning have led to the development of sophisticated translation technologies that are capable of producing high-quality translations in real-time. These technologies are changing how we communicate across different languages, making it easier than ever to break down language barriers. How AI Translates Languages AI powered translation tools use machine learning algorithms to analyze vast amounts of language data and learn how to translate different languages accurately. These tools can process natural language and identify patterns and relationships between different words and phrases. By doing so, they can translate text from one language to another with impressive accuracy. Types of AI Powered Translation Tools There are several types of AI powered translation tools, each with strengths and weaknesses. Some of the most common types include: Rule-Based Machine Translation Rule-based machine translation involves translating text based on a set of predefined rules. These rules are created by human linguists and programmers, and the translation process involves matching words and phrases in the source language to their corresponding words and phrases in the target language. Statistical Machine Translation Statistical machine translation involves analyzing vast amounts of language data to identify patterns and relationships between different words and phrases. By doing so, statistical machine translation tools can translate text from one language to another with high levels of accuracy. Neural Machine Translation Neural machine translation involves using deep learning algorithms to process natural language and translate text from one language to another. These algorithms can learn from vast amounts of language data, making them highly accurate and efficient. The Benefits of AI-Powered Translation AI powered translation offers several benefits over traditional translation services, including: Cost-Effectiveness AI powered translation tools are often more cost-effective than human translators, making them an excellent option for individuals and businesses on a budget. Efficiency AI powered translation tools can translate vast amounts of text quickly, making them an excellent option for individuals and businesses that need to translate large volumes of text regularly. Accuracy AI powered translation tools can translate text with impressive accuracy, making them an excellent option for individuals and businesses that require high levels of accuracy in their translations. Implications for Businesses and Individuals The rise of AI powered translation has significant implications for businesses and individuals alike. For businesses, AI translation tools offer a cost-effective and efficient way to communicate with customers, employees, and partners in different countries and linguistic regions. This can help to expand the reach of businesses and increase their global competitiveness. For individuals, AI translation tools can make it easier to navigate daily life in a new country, communicate with locals, and access information in a different language. Challenges and Limitations of AI Translation While AI powered translation tools offer many benefits, there are also several challenges and limitations to consider. First and foremost, these tools may struggle with idiomatic expressions, cultural nuances, and other subtleties of language that human translators are more adept at handling. Additionally, AI translation tools may not be suitable for translating highly technical or specialized content, as they may not have the required expertise or knowledge. Finally, there is a risk that reliance on AI translation tools could lead to a loss of human language skills and cultural knowledge over time. The Future of Communication The potential impact of AI powered translation technologies on the future of communication is enormous. As these technologies continue to improve, they will make it easier than ever for people to communicate across different languages, breaking down language barriers and promoting cultural exchange. In the future, we may see AI powered translation technologies integrated into everyday devices like smartphones and laptops. This would make it possible for people to communicate with each other in real time, regardless of the language they speak. The impact of AI powered translation on businesses is also significant. As businesses continue to expand globally, the ability to communicate effectively with customers in different languages will become increasingly important. By using AI powered translation technologies, businesses can communicate with their customers in real-time, regardless of the language they speak. Conclusion In conclusion, advancements in artificial intelligence have revolutionized translation technology, making it easier to communicate effectively across multiple languages. AI powered translation tools use machine learning algorithms to analyze language data and identify patterns, resulting in accurate translations. There are several types of AI powered translation tools, each with strengths and weaknesses. They offer cost-effectiveness, efficiency, and accuracy over traditional translation services. As AI powered translation technology continues to improve, it has the potential to break down language barriers and promote cultural exchange, making it easier for people to communicate across different languages in real time. This technology also has significant implications for businesses looking to expand globally and communicate with customers in different languages. Originally Published on The Tech Trend

Read More

Unlocking the Future: 9 Mind-Blowing AI Trends to Look Out For

Hey Alexa, “What are the top Artificial Intelligence trends this year? If you ask Alexa or Siri, you will probably hear that the most trending topics are Language modeling, Conversational AI, Computer Vision in Business, and the list.  But have you noticed that your assistant is also an example of Language Modeling and Conversational AI? Yes! You are using this advanced technology in your daily life every day without even being aware of it.  With the speed at which AI is disrupting industries and even our daily lives, it’s no wonder that experts are calling AI the future of technology.  Let’s find out more about current AI trends and how they are affecting the world.  Where Is Artificial Intelligence Used Today? Artificial Intelligence is changing the shape of the technology field. It’s now available in various sectors like transportation, manufacturing, health, and finance to automate all the possible systems to increase efficiency and performance. For instance, you can use mobile phones to diagnose diseases. The architecture provides a high-performance system with accuracy and efficiency.  Another great example of AI is transportation. A system like Google Maps can analyze the traffic movement speed with accuracy. This program provides records at any time and on-the-spot road incidents. The analysis result includes construction work, heavy traffic, and even accidents.  In the manufacturing industry, system maintenance with predictive and preventive mechanisms helps the management teams to avoid downtime. Also, AI systems in quality control help increase work production. The finance sector also leverages ML capability for fraud detection. AI and ML also play a vital role in the smart payment process, insurance, and investment recommendation. PrepAI is another example where AI is getting used in the education sector. PrepAI was originally developed and maintained by the DataToBiz company, which also uses the AI model for different AI services. On this platform, people like teachers or instructors can use the AI model to create various types of exam test papers. How Will Artificial Intelligence Change The World? From smartphones to chatbots, we are already using AI in our daily life. AI is evolving day by day. It observes our routine including our likes or dislikes and our purchases. Then AI specialists, or we can say AI developers, research all that data to train machines on how to learn from it and predict what we want.  Following are some predictions done by the USC researchers based on their analysis.  Healthcare The research analysis suggests that AI programs with computer vision will allow doctors and well-equipped hospitals to analyze data. Based on that analysis, doctors can customize health care according to individual patient’s genes.  AI will be able to diagnose major diseases like brain tumors and will suggest which cancer treatment will be suitable before it worsens. Several types of research are underway to develop AI-powered applications. Those applications are aimed to help doctors diagnose and treat patients with better medical care.  You can expect a different future in healthcare as it will adopt robots to interact with the patient. They will check the patient’s health condition and assess the need for a doctor’s appointment. AI will make our life simple with our clinical and healthcare history. Retail According to research, the adoption of ai-powered business intelligence in the decision-making process will make a huge impact on business growth and performance. In the future, AI-powered drones will deliver packages up to 5 pounds in less than 30 minutes.  Amazon has already started working on this project with proper safety and reliability measurements for package delivery. There is no fixed date for this delivery to get on the road, but you can expect the autonomous delivery of goods with drones in the next decade. Apart from autonomous delivery, future retail with AI will get individualized with virtual racks. The racks will get customized according to previous history and purchases made by customer choice.  Entertainment In the future, users will be able to order a movie that will be completely customized according to their desire. Even working independently, AI will assist humans in their own creative patterns like helping writers to avoid writer’s block by providing suggestions. Furthermore, in the present era, Artificial intelligence is still in action in the form of Google Assistant, Siri, and Cortana. They are able to handle most home devices connected to the internet over voice commands. How Big Is The Artificial Intelligence Market? The growth of AI in every possible application and its easy development dragged government interest toward it. Now the government is also taking a step ahead to invest in AI and its all related technologies.  According to Verified Market Research, the global market size of artificial intelligence was worth US$51.08 Billion back in 2020. It is projected to reach up to US$641.30 billion by the year 2028 with growth at a CAGR (Compound Annual Growth Rate) of 36.1% from 2021 to 2028. Apart from that, many sectors like aerospace, healthcare, and manufacturing are adopting AI. Thanks to its in-depth learning and Artificial Neural Network (ANN) mechanism. Also, the capability of big data interpretation and analysis boosted the demand for AI industry solutions.  The advanced AI development companies in cloud computing infrastructure and improved dynamic AI solutions have made the potential growth of the AI market. AI is getting used mostly to automate dangerous tasks in the manufacturing industry. Modern AI companies need people with certain skills to adopt, manage, and train AI systems. Top Artificial Intelligence Trends 1. DALL-E Earlier this year, Silicon Valley-based research lab OpenAI unveiled DALL-E, which surprised the internet. In terms of artificial intelligence, this tool is getting considered one of the most advanced systems on the market for creating images. The system works as you can create hyperrealistic photographs or artwork by typing a description. DALL-E is currently unavailable to the public. Researchers, academics, journalists, and artist testers are the only ones who can access to use this system. The company has recently announced that it will invite more people to the event. As

Read More

AI Consulting Explained: A Comprehensive Guide for Businesses

AI adoption is increasing in the global market, but businesses still have a few doubts about it. Here, we’ll discuss the need to partner with AI consulting companies and how they can help an enterprise achieve its goals.  There have been many technological developments during the last few years in the international market. Businesses are shifting from traditional to modern data-driven models and using cloud services for IT infrastructure. Artificial intelligence has become a common keyword in digitally and technologically transforming business processes. The global AI market is likely to grow at a CAGR (Compound Annual Growth Rate) of 39.7% and touch $309.6 billion by 2026. ‘Many large enterprises are rapidly transforming their systems to adopt AI tools to increase productivity and profits. Small and medium enterprises are a little behind due to cost issues. Many large companies as well as startups are investing in AI and ML models and increasing their budgets to digitally transform their systems. However, startups are realizing the importance of investing in artificial intelligence applications. Several organizations are increasing their budgets to spend more money on AI and ML models. That said, there are a few barriers to AI adoption slowing that slows down the adoption rate.  The main barriers to AI adoption are the lack of access to expertise and the cost of developing an AI application from scratch and that’s where AI consulting companies come to play. These roadblocks can be easily overcome by partnering with AI consulting companies. These companies have the necessary talent and tools to provide AI-based services for cost-effective prices. According to MarketWatch’s latest study, the AI consulting services market will earn a multi-million dollar revenue and grow exponentially in the next seven years.  Today, many big as well as small. More and more organizations are relying on artificial intelligence consultants for digital transformation services.  In this guide to AI consulting, we’ll read more about the types of services offered, how to choose the best AI consultants for your business, and the five best AI consulting solution providers in the market.  What is AI Consulting?  Artificial intelligence consulting is where AI engineers and experts assist business organizations from various industries to adopt AI applications to achieve their goals. This is easier said than done as it involves a series of activities and is a long-term process.  AI consulting companies have several roles and responsibilities, such as: AI Consulting Process Let’s look at the steps that AI consulting companies follow to help businesses leverage artificial intelligence technology in the right manner. 1. Strategy Formation  The first step is to create a strategy or plan of action to adopt AI within an enterprise. Here, the AI consultants will have in-depth meetings with the clients to identify areas best suited for AI integration. These are then prioritized to list the required tools for the adoption process.  The focus is on strategizing the right path to create the necessary IT infrastructure and data pipelines to integrate AI tools with existing legacy systems. The availability of resources, cost of investment, duration of the project, etc., are considered when planning the strategy.   2. Evaluating Processes and Possible Outcomes  Many AI projects fail to take off or end up incomplete due to a lack of evaluation. Whether a business wants to build an AI application from scratch or customize an existing one, the AI consultants will first determine the feasibility of the process and evaluate the possible outcome. These AI experts will assist organizations in choosing projects with commercial viability and success. This reduces the risk of failure and loss of investment.  3. Implementation and Deployment  Now, the major responsibility lies with the AI consulting company to implement and deploy the project (building, integrating, customizing, etc.) as per the approved plan.  For example, if a business wants to deploy chatbots to assist customer care executives, the AI consulting team will create the necessary framework to set up AI chatbots and automate their roles at the helpdesk.  4. Training and Maintenance  Some AI consulting companies also offer training services. After all, the end user/ employees must know how to work with the application. Training sessions are conducted to educate employees about the various features of the new AI application and ways to deal with errors.  Alongside this, the consulting company can continue to provide maintenance services if the organization wants. This ensures that AI experts regularly check the systems for errors and upgrade the features to make sure it offers the latest and expected services.  5. Governance and Compliance  The AI consulting company is also responsible to ensure that the artificial intelligence systems developed/ customized for the organization are compliant and meet global guidelines. Ensuring data security and developing data governance systems or protocols are a part of the process. The AI consultants may have to add multiple security layers in enterprises that work with highly confidential data.  Types of Artificial Intelligence Consulting Firms AI consulting firms are broadly divided into the following types:  1. Tech Consulting  These consulting companies are focused on offering tech (IT) based services. They have expert teams to provide off-shore, nearshore, and IT staff augmentation services.  2. Executive Consulting  This is also known as top management consulting. These AI strategy consulting companies help businesses understand how and when to implement AI in the enterprise. Large consulting companies also acquire smaller firms and deal with cross-industry adoption of artificial intelligence.  3. Cloud Consulting  These AI consulting companies offer cloud-based services. Amazon, Microsoft, and Google are examples of this type of AI consulting. They deal with cloud storage, network management, and cloud computing applications or services.  4. The Top Four  Deloitte, EY, PwC, and KPMG are the big four AI consulting companies that have been in the industry for more than 50 years. They offer services to clients from around the world and have premium prices. This makes them cost-intensive for small and medium-sized businesses.  5. End-to-End Consulting  Companies like DataToBiz offer end-to-end AI consulting solutions, where they take care of all AI-based processes, from strategy formation to maintenance. The consulting companies may

Read More

6 Business Benefits of Outsourcing Your AI Projects

The biggest dilemma for a business is to choose between building an in-house team and outsourcing the AI project to an offshore expert. We’ll discuss the benefits of outsourcing in detail to understand why it is the preferred choice for most enterprises.  Artificial intelligence has been a game-changer for many small, medium, and large enterprises. It has made digital transformation possible by helping businesses use data to derive actionable insights and make better decisions. AI can be used in different verticals in the organization. For example, AI applications help the sales team with demand forecasting and market trend predictions. Artificial intelligence is used by the human resource department for recruitment and tracking employee performance. AI has a role in supply chain management, finance, transportation, and customer service.  According to Gartner, organizations using AI for customer service are expected to see a 25% growth in customer satisfaction by 2023. More than 90% of the leading business organizations are investing in AI. In fact, 86% of the CEOs considered AI the mainstream technology in their offices as of 2021.  This raises the question of whether you need to hire an in-house team for AI projects or outsource the responsibilities to offshore AI developers in India. Outsourcing has its benefits and is a preferred choice for many businesses.  Small and medium-sized businesses outsource to avoid infrastructure and maintenance costs. Large enterprises outsource to increase employee productivity. Around 70% of the projects are outsourced to reduce the budget. Flexibility is the second next reason for outsourcing. Read on to understand how artificial intelligence can help your business and why outsourcing AI projects is beneficial. Importance of Artificial Intelligence  Artificial intelligence is becoming an imperative part of several businesses because of the range of advantages it offers. How you use AI within the business determines the results. Here are a few important areas where AI is prominently used by leading organizations.  Automation  Automation is the process of using technology to complete repetitive tasks that are otherwise handled by employees. It reduced workload to save time and energy. It reduces the risk of human error and delivers more consistent results in less time. Machine learning algorithms are used for automation in various industries like healthcare, manufacturing, retail, entertainment, etc.  Market and Customer Research  The sales team has a lot of responsibility. It has to predict the market trends, understand customer behavior, identify the right time for the promotional campaigns, and align everything with the business goals. AI application will simplify their job while empowering them to use the insights to plan marketing strategies more effectively.  Logistics  Inventory management, warehouse management, and aligning the movement of stock from the warehouse to the stores or transporting it to the distributors require constant coordination with internal and external teams. A small miscommunication at any stage of the supply chain can lead to delays and losses. Artificial intelligence prevents this by predicting delays in advance and sending automated alerts to supervisors.  Unlock the Power of Data  Data is available in abundance in today’s world. Enterprises can gather data from several external sources. But how you use the data determines the success of your business. You need the right tools to clean, structure, process, and analyze data to get accurate insights. AI streamlines this process and also provides insights in real-time. You can use the latest data from the market to make decisions instead of relying on outdated information.  Competitive Advantage  Using AI tools will give you an edge over other businesses in the same industry. It helps small and medium-sized businesses establish themselves in the market despite the strong presence of global enterprises. Artificial intelligence is ‘the key’ you need to survive competition, capture markets, and expand your customer base.  Disadvantages of In-House AI Team for AI Projects  Having learned how AI can help your business, you should decide between building an in-house team and outsourcing the projects to AI consulting companies in the market. It might appear tempting to start from scratch and develop an in-house team so that you will always have someone working on the AI tools.   However, you should consider the following aspects before going ahead with a permanent team within the enterprise.  Shortage of Skilled Professionals  Despite the increasing demand for AI and ML engineers, data scientists, etc., there aren’t enough professionals to bridge the gap between demand and supply. In such instances, hiring talented and experienced professionals in a short time is almost impossible unless you are a leading global organization. Furthermore, there’s no guarantee that the professionals will stay with your business. They can move to another company if they get a better offer. This means you have to start the recruitment process once again. It will lead to more delays and cause a waste of valuable resources.  Cost Intensive  The cost of having an in-house team doesn’t end with recruitment. You have to pay salaries and provide the necessary infrastructure and resources for the team to work on the AI projects. You also have to deal with the cost inflations due to additional requirements/purchases, pay hikes, and losses if the project is not successful.  An in-house team is expensive for a business unless you have the budget to sustain an R&D department and invest millions into it regularly. Machine learning outsourcing will cost less and deliver faster results.  Involvement from Different Departments The in-house cannot work in isolation. It needs input from other departments and should have team members for the same. However, not every business has enough manpower to spare employees from one department to work in another. Asking the employee to handle everything will lead to stress and decreased productivity.  Access to Quality Data for Training Models  Quality data is the key to accurate AI models. The algorithm will deliver results based on the input data you provide. But where does quality data come from? Data available online cannot be directly used to train models. It needs to be cleaned, formatted, structured, and processed before being fed into the model. The in-house team will spend most of the

Read More

A Definitive Guide To Machine Learning Consulting

Planning to integrate artificial intelligence and machine learning into your daily business operations?  If yes, then what’s the best way to go about it?  If you are confused about how to leverage machine learning or artificial intelligence capabilities to scale your business, then you need an expert to guide you. This guide will walk you through the whole process of ML and AI consulting and whether it’s the right choice for you.  What is Machine Learning Consulting? The goal of AI/ML consulting is to help businesses improve their performance and productivity by using AI technologies. The main focus of artificial intelligence is to exploit machine learning to increase companies’ value in an environment of rapid change and intense competition.  AI consulting companies help their clients design and develop advanced AI-based products and solutions by developing AI-driven algorithms and machine learning tools.  In order to ensure maximum results, it is essential to design, implement, and integrate Artificial Intelligence into the business environment of various organizations.  The demand for artificial intelligence-driven products and systems is high at present. But, there are still limited options available. The services offered by AI consultants include: What Does A Machine Learning Consulting Firm Do? There are many reasons why companies need consultants, such as a lack of expertise, existing commitments, government regulations, or the need for an unbiased perspective.  While consulting firms perform varying roles and responsibilities depending on the industry and the company’s needs, their primary goal is to improve business efficiency and profitability. Consulting firms begin their work with the following tasks. The Process Starts With Knowing What Your Business Needs Every consulting project begins with some business need. Business requirements are still one of the biggest reasons for the failure of consulting and software projects. It can be choosing the right location to install your next branch or selecting the right audience.  There is a particular issue with ML consulting, as it is at the intersection of consulting and software development. Setting Up the Team and the Process Machine learning is not necessary for all business problems. Problems that cannot get reduced to a set of rules make sense for machine learning and other approaches.  The performance and maintenance of rule-based systems are better than machine learning when the rules are well known. ML can be useful for solving particular problems, but the project team, stakeholders, and high-level targets needed get decided. The Process of Collecting and Exploring Data It is relatively simple to do this if the company already has the data. Else consultant has to collect all the data to understand the business problem.  Afterward, consultants must verify that data labels are accurate and do not conflict with each other. If data isn’t readily available, you can also have options like leveraging online data, paying for labeling, or using novel machine learning techniques such as one-shot learning. The Model Development Process. Developing a machine learning model that performs more accurately requires thousands of experiments.   It is a trial-and-error process involving the latest research, a thorough understanding of business dynamics, and data analysis skills. For accuracy testing, all models get tested against the same data set. Full-Stack Application Development The model development and integration for production require additional time and resources.  In most cases, ML models get embedded into APIs which makes it easy to integrate them into applications.  Application development, which implements the ML model and integrates it into decision-making processes, can be more challenging than modeling itself.  When developing applications, integrating them into existing enterprise systems is necessary, which requires an external developer’s involvement. To put the model into action, it is necessary to address the scalability and data security issues. Why Does Your Business Need Machine Learning Consulting Services? If you are just getting started with machine learning, it can be difficult to differentiate a top consulting firm from an upstart. You should consider these points before working with a consulting firm. They Are A Time Saver McKinsey estimates that artificial intelligence and machine learning will replace 30% of current jobs by 2030. Machine learning service providers can save you a lot of time. You can find running a machine learning campaign difficult if you don’t have any AI training.  The advantage of hiring a highly regarded machine learning company is that they have expertise in all aspects of machine learning and can launch your campaign quickly. Experienced consultants are familiar with best practices. For instance, A lean consultant can quickly pinpoint inefficiencies in a company’s manufacturing process.  Business owners do not need to create something from scratch or waste valuable time on tasks an expert contractor can complete. They Are Result Driven  A good machine learning firm will always take the time to understand your business, your goals, and your needs before creating a machine learning campaign for you.  In this way, they will design and implement a machine-learning strategy that corresponds to your business goals and provides you with the desired outcomes. It Is Financially Profitable It is important to have a lot of data to make good decisions when creating a machine learning campaign. In order to hire a machine learning consultant, you will need access to various programs and software, which can cost quite a bit over time. When you hire a machine learning consultant, you will have access to many different programs and software, which can be expensive over time. Additionally,  you pay only for the services that you need, when you need them.  An ML consultant with similar expertise can save hundreds of dollars compared to hiring salaried employees. Besides, consultants with expertise in many areas can identify pinpoints where you are currently overspending and suggest ways to cut it.  Providing Support For Data Preparation The data preparation and collection are essential for modeling and training ML, as well as the foundation for deep learning and AI.  Also, for combining data sets, renormalizing data, and preparing your database for successful implementation, a good ML consultancy can provide you with helpful advice.  Consultants

Read More

6 Reasons To Hire a Machine Learning Developer

Artificial intelligence and Machine Learning are undeniably transforming and integrating themselves into every aspect of our everyday lives, from entertainment and social interactions to the workplace. Artificial intelligence, according to experts, will advance a company into the next generation, revolutionize data management, and improve the whole consumer experience. There are many business applications for AI and machine learning, and as these applications become more widespread and sophisticated, we can only anticipate an expansion of this list.  6 Reasons to Hire a Machine Learning Developer Here are a few of the reasons you should hire a machine learning developer: 1. Supports Real-Time Decision Making Big data’s potential is expanding quickly, thus you must connect users and providers (buyers and sellers) instantly. Businesses must instead use data and analytics to quickly determine the best course of action based on the current situation. Your consumers will appreciate personalized services, which will increase profits. A machine learning developer helps businesses achieve real-time decision-making by drawing insightful conclusions from the data. 2. Enables Automation That Replaces Manual Efforts ML technology advances industrial automation by replacing manual jobs that incorporate unpredictable elements like changeable parameters, external causes, and internal system changes. Industrial automation in the 20th century focused on employing machines to reduce predictable and repetitive human tasks. An ML developer gives businesses the ability to make quick judgments and automate operations by creating predictive data models. One such is Adobe Target‘s Auto Target, a potent AI technology that employs machine learning to create automated tailored experiences. Personalization in Adobe Target is based on a set of experiences chosen by the marketer. 3. Effectively Address Security and Network Challenges Cyberattacks, network breaches, and other security flaws sometimes occur in real-time without warning, giving users little opportunity to take action. One of the biggest cyberattacks in history occurred in 2018 when a series of DDoS strikes targeted GitHub and Arbor Networks in the US. Any network intrusion must be promptly detected and stopped by enterprises in order to avoid service interruptions and data leakage. ML developers are capable of creating algorithms that are capable of tracking network activity to quickly identify anomalies so that preventative steps can be taken. Additionally, as ML algorithms take the place of manual investigation and analysis, they self-learn and adapt to change, which further enhances the condition of cyber-security. 4. Improves Marketing Results The branch of AI known as machine learning focuses on creating intelligent machines that can operate independently of human intervention. Additionally, a machine learning developer helps businesses save time and money in the marketing sector as well. In marketing initiatives, machine learning can be an amazing and potent multiplier. Constant messaging, trends and changes in consumer behavior, targeted marketing techniques, etc. are all made possible by machine learning engineers. Social media websites can be used to develop micro-marketing campaigns. 5. Manages Unstructured Data Large amounts of unstructured data can take a long time to clean up. Any organization that evolves over time gathers a lot of fresh information. For instance, if you are in the air freight forwarding business, you will need to process large amounts of data on services, rates, etc. within a short period of time in order to evaluate it and obtain insights about potential future patterns. Managing and removing massive information indexes is one of machine learning’s most important applications. The information is easier to process, obtain, and retrieve thanks to machine learning. 6. Increasing Customer Satisfaction Currently, machine learning is used to improve customer experience, which results in increased customer loyalty. It is done by looking at the customer’s buying habits. Many organizations all over the world already use this technology. According to research, 76 percent of business owners agreed that their profitability increased as a result of incorporating machine learning into their processes to understand client behavioral patterns. Google and many other large websites are using this technology. You may have observed that when using websites like YouTube, LinkedIn, etc., you frequently receive recommendations for various goods to buy or individuals to connect with. With the aid of machine learning, the ads and friend suggestions are handled. How To Hire A Machine Learning Engineer When hiring a machine learning engineer, who can be a valuable asset for your business, it is advised to exercise extreme caution if the company is investing in the development of artificial intelligence and machine learning. As a result, there are some essential factors to consider when hiring a machine learning engineer or specialist. What to take into consideration when you want to hire a machine learning developer is covered in full below. 1. Technical Skills For these professionals, full-fledged technical skill in coding and programming is essential in order to tackle such assignments. Here, you must check the applicant’s technical specialization and administer the coding test to confirm that she/he is capable of overseeing the creation of AI and ML models. Make sure you have qualified professionals to hire the best applicant so you can evaluate their technical talents. A machine learning developer should have knowledge of languages like python, frameworks like Pytorch or TensorFlow, algorithms like Scikit, and many others. Make sure you test all the necessary technical skills before hiring. 2. Interactive Communication Skills The ability to communicate with others, which is necessary for collaboration with colleagues, should be taken into account when trying to hire a machine learning engineer. Before beginning the project, AI and machine learning professionals should agree on a framework for communication with the company. Therefore, if you are concerned about a candidate’s communication skills, you should assess their capabilities to ensure effective communication. Wrapping Up Finding a suitable AI or machine learning professional would be difficult and time-consuming. To prevent confusion between data analysts, data scientists, and machine learning engineers, it provides basic stages of vacancy description with a precise set of responsibilities. In order to recruit a machine learning engineer that is an expert in his field, one must have a complete understanding of technology and competence. So, to

Read More

Why Hire an AI Software Development Company?

Whether or not a business project is a success largely depends on how solid the technical team is. Today, AI development is faster than ever, pushing businesses to gain a competitive advantage.  Every project is unique and so are its requirements. A company must choose the most convenient and efficient model for AI software development, depending on the project’s scale, features, goals, and budgetary constraints. However, there is also a slew of factors that determine the success of a project.  Factors Responsible for Outsourcing AI Development Needs of a Company  Requirements Before you decide whether to outsource a project or handle it in-house, clearly assess the project goals. What are the features you are looking for in your project? What are the services you will require for the successful execution of the project? When are you planning to launch the project?  Next, you need to assess if an in-house team has all the necessary skills to fulfill your expectations from the project or if an external agency can provide you with the level of customization you require for the project. Budget  Maintaining a budget is one of the most crucial aspects of a business. So you need to figure out how much capital you can invest into developing your project. Next, calculate the expenditure required for in-house handling and outsourcing and choose the option that best fits your budget. The Results  It is one of the most crucial factors you need to consider to decide which of the two options is more viable for you. Compare the services that your in-house team will offer with an external agency. Understand the complete scope of work and the exact services you will be paying for. Now, the next question that might come into your mind is, “How do you ensure that your project idea is executed in the best possible manner? Do you hire an in-house software development team? Do you partner with an AI outsourcing agency?” Let us deep dive into the pros and cons of both these options so you can decide what suits your company the best. Advantages and Disadvantages of In-House AI Development In-house AI development means hiring team members within your organization and training them with the crucial IT skills and abilities needed to handle the project. Although this method is more cost-effective in the long run, it can seriously load the company’s budget in a shorter span.  Disadvantages of In-House AI Project Development Lack of Expertise  In-house AI developers demonstrate lesser expertise and the skill to develop AI-based ideas as compared to ones in an agency. They do not have an interdisciplinary perspective which is a prerequisite for creating meaningful models for making business decisions and getting faster results. Need for Resources Hiring an entire team is even more difficult than it sounds. As an organization, you must equip yourself with all the resources such as infrastructure, overhead, additional employee benefits, training fees, etc. making an in-house team an expensive affair. Time Crunch  Hiring an in-house AI development team is an extensive process. From evaluating potential team members to recognizing the skill gap of every member, training every member is a long process. If you run out of time to execute a project, it is natural to not go with this option. Advantages of In-House AI Project Development High level of Personalization By developing your own AI solution, you can remove all the unnecessary features and complicated settings and bring down costs just by sticking to the product requirement.  Ownership of Intellectual Property (IP) If your company invests in developing advanced technology like AI by building an in-house team, you can gain patent rights for the value you add in this field. It can give you an edge over your competitors in the industry. Advantages and Disadvantages of Outsourcing AI Project Development Outsourcing means your company partners with an external AI development agency and delegates the project execution job. Though outsourcing technical projects can be expensive, it is worth the investment. You get access to domain experts with a lot of experience working on similar projects. It is especially beneficial if you do not want to wait too long to launch your product in the market. Advantages of Outsourcing AI Project Development Instant Access to High-Quality Data Tons of high-quality data are needed for developing machine learning and building deep learning models. Even if your business has access to big data, working with such massive data requires a lot of experience and is time-consuming. Only an external AI development agency can bring such expertise to the table. Before starting any AI project development, proper data cleansing and preparation are prerequisites. An outsourcing agency can feed a Machine learning platform with high-quality data sets to leverage it to your advantage. Outsourcing Is a Remedy for Invisible Costs Outsourcing might be expensive, but you pay for the skills and expertise. But while building an in-house team, you pay in terms of both time and money for additional things apart from the skills and expertise. Everything is an additional cost to the company, from recruitment and software licenses to training and employee benefits to providing refreshments. Also, hiring people in technical fields such as AI is tough. A lot of time is needed to search, interview, recruit, and onboard new employees. Your company can save all of this time and capital just by partnering with an outsourcing AI agency. Scalability and Flexibility  If you are a fast-growing startup in a highly competitive industry, you need to scale dynamically to meet market needs. In such a situation, the in-house team” approach might not be helpful, especially in challenging, specialized projects. Also, if you are a small company, you probably do not have the resources needed to implement all the in-house services and systems. So to ensure that the quality of the final product is not compromised and to compete with the big players in the market, outsourcing is a better option.  You can achieve high levels of scalability and

Read More

4 Best Computer Vision Use Cases for Solving Business Challenges

Computer vision is a field of artificial intelligence (AI) that can be found in an increasing number of business use cases. It enables machines to “see” objects and interpret them as humans do. Computer vision services specialize in many types of vision, including detection, identification, and supervision. Here’s a quick rundown of both how the technology works and how businesses are using it to overcome challenges and optimize workflows. How Computer Vision Works All computer vision devices and applications utilize AI, which is a simulated form of human intelligence and the basis of all machine learning. Just as a human sees an image and processes an appropriate response, the AI in computer vision detects digital images, analyzes the data, and processes a response in the blink of an eye. For a computer vision system to work effectively, developers must expose it to thousands of images with definitive traits, such as names, physical features, and labels. Pattern recognition is the name of the game. Once the system acquires a knowledge base of its particular environment, it can automatically take over detection, identification, and supervision responsibilities without human assistance. Computer vision is gaining a foothold in various industries, and business leaders have many opportunities to use the technology and get ahead of their competitors. Here are four of the most influential applications and real-world examples of how computer vision can solve companies’ challenges. Computer Vision Use Cases for Solving Business Challenges 1. Object Detection Object detection is the most well-known and widely used computer vision function. A system utilizes its AI network to identify specific objects in various settings. It eliminates much of the programming and guesswork that previous detection devices relied on, allowing for quick and accurate detections without human supervision or intervention. Self-driving cars are perhaps the most well-known examples of AI-powered object detection, but that technology has seen mixed results in practice. These other real-world applications have been more successful: Object detection is just the first step in a computer vision service’s analysis. It also classifies, monitors and verifies objects based on what the AI has learned. This technology will only get more accurate as it continues to gather information. 2. Optical Character Recognition On a smaller scale, computer vision services use optical character recognition (OCR) to identify letters, numbers, and other symbols from images. The most mainstream example of OCR that you might have already used is Google Lens. This tool enables users to pull fragments of text from digital images and printed documents and even translate foreign languages from photographs. OCR has also been a valuable tool for several key societal institutions, including education, finance, and government. Universities can scan and extract text from obscure historical documents and make more accurate translations, preserving precious knowledge from the past that otherwise might have been lost. Banks and credit unions offer OCR services so customers can scan their checks and credit cards without coming into the office. Other machine-readable personal documents — passports, driver’s licenses, green cards — also utilize OCR to help governments with border security and identification. Virtually every scannable item you can imagine can benefit from OCR, so your business is sure to find a relevant use for it. 3. Risk Management Employee safety should be the top priority for all businesses and industries, but equipment and regulations can only do so much. A computer vision system can help create a safer work environment by tracking worker activity, including how they use heavy machinery and navigate the work site. Safety-oriented computer vision applications are most common in dangerous settings, such as construction sites and warehouses. Workers use wearable AI devices to monitor their physical conditions, while supervisors use drones and cameras to identify hazards and ensure everyone follows required safety procedures. The health care industry has found a similar use for computer vision services, providing patients with wearables that automatically monitor specific conditions and send feedback in real-time to their doctors. This trend arose by necessity during COVID-19, as many people were either unable or unwilling to schedule in-person appointments. Computer vision is also a key part of some in-house hospital equipment. Medical professionals can train AI to identify the early stages of illnesses through X-rays, MRIs, and CT scans. 4. Image and Video Restoration Modern cellphones, cameras, and editing tools allow people to make drastic changes to images and videos, but none of those devices come close to computer vision’s editing capabilities. Computer vision services restore pictures and videos with extensive damage and decades of deterioration. AI in computer vision services evaluates the missing or damaged parts in the original image or video, reads a generative model of the same media, and fills in the gaps to recreate the scene. Some take the restoration a step further and build 3D sets of real settings, such as archaeological and environmental professionals.  Computer vision’s restoration abilities have also proven valuable in the court of law, as forensic specialists can perform more immersive crime scene reconstructions and thus solve many cases. Computer Vision Has Massive Potential These applications of computer vision services are just a handful of successful examples. This technology has massive potential to transform many crucial industries, from health care to finance to construction. Developers are still working out some of the kinks, but business leaders should embrace this technology and add it to their operations in any way they can.

Read More

Depression Analysis Using Machine Learning and AI

Depression has become one of the major global health concerns. Technology like AI and ML can be used to analyze depression data to provide better treatments to people suffering from different types of depressive disorders. We’ll discuss depression and the ML Python code used to analyze data. The changing lifestyle and social scenarios have brought many changes to our lives. We have access to too much information. We are way too connected with the virtual world, and the lines between real and virtual are blurring rapidly. While it sounds like a good thing to stay up to date and informed about anything under the sun, it also has severe side effects.  The fast-paced world has resulted in a lot of anxiety and stress, leading to different psychological issues in people. Depression and poor emotional health are now among the major concerns across the globe. Thankfully, technology is coming to the rescue yet again. Machine learning engineers and researchers are working on analyzing depression in people to detect the symptoms at earlier stages and provide better ways to cope with mental health issues.  Artificial intelligence and machine learning algorithms can be used to analyze datasets with depression-related data to deliver accurate and in-depth insights. Let’s understand what depression actually is and how ML can provide a feasible solution to help people with depression and make their lives happier.  What is Depression?  Depression is a serious mental illness that makes you feel sad, lonely, tired, or anxious. It makes you lose interest in things you previously enjoyed. Depression is a psychological disorder that increases negative thoughts and emotions, leading to other health conditions. It also reduces your productivity, alertness, and ability to think coherently. It affects how you think, feel, and act.  Depression is a common condition seen in many people. Many times, people themselves don’t realize that they are in depression. Statistics show that around 3.8% of the global population suffers from depression. This includes 5.7% of adults who are aged over sixty years and 5% of adults aged less than sixty.  To put it in figures, 280-310 million people have depression. What’s alarming is that more than 800,000 people commit suicide due to depression every year. Kids and teens are by no means safe from depression. The US is among the states with the highest depression rates around the world.  Depression (Major Depressive Disorder, MDD) is commonly known as clinical depression. MDE (Major Depressive Episode) is a measure of time a person exhibits or has the symptoms of depression. Note that mood swings and short bursts of anger/ irritation are not considered depression.  Different Types of Depression  Depression is an umbrella term that covers more than one type of mental illness/ disorder. It can be classified into the following types:  Anxiety/ Distress  Anxiety is when you feel stressed and tense throughout the day. It brings negative thoughts about how things can go wrong or that something really bad will happen to you or your loved ones. So much worry takes over your mind and your thoughts. It also leads to anxiety and panic attacks.   Agitation  You feel uneasy and uncomfortable no matter what. You cannot relax and calm down. An agitated person has jerky movements and is constantly fidgeting or in motion. You cannot sit in a position for more than a few seconds. Some people also tend to talk a lot when agitated. It doesn’t make sense, but you can’t control it either.  Melancholy  Melancholy is intense sadness or emotional pain. It fills your mind to an extent where even good things don’t cheer you up. Activities you usually enjoy also fail to make you happy. Melancholy results in loss of appetite, sad thoughts, feeling down/ low in the mornings, disturbed and irregular sleep patterns, and suicidal thoughts.  Persistent Depressive Disorder Persistent Depressive Disorder is when a person is suffering from depression for more than two years. It is a chronic condition where the person is highly vulnerable and susceptible to making harmful decisions. PDD is used to describe chronic major depression and dysthymia (low-grade persistent depression). The symptoms of this disorder are:  What is Bipolar Disorder?   Bipolar disorder is also called manic depression, as it causes extreme mood swings in a person. You might experience random bursts of energy where you feel fantastic and at the top of the world. You work and overdo things until you’re exhausted. Meanwhile, on the other end of the spectrum, you’ll feel miserable and horrible about anything and everything. You feel fatigued, tired, and worthless.  This is a vicious cycle where you alter between two contrasting moods but no middle ground. Doctors recommend mood stabilizers like lithium and calming activities like meditation to bring some sort of balance and stability to your mood.  Symptoms and Warning Signs of Depression Depression has many symptoms, some of which overlap with a general lack of mood or exhaustion after a long day of work. Naturally, all of us feel low at some point in our lives or another. But when the feelings persist and take over our lives, it is a sign of depression.  Depression isn’t general sadness or pain of loss. It is more intense and can wreak havoc in your life by gradually robbing your happiness and ability to assert yourself. You can no longer feel, think, work, enjoy, and act the way you used to do. Some people term it as ‘living in a black hole’, where the void sucks out even the last bit of energy and happiness from you.  Some feel apathetic to their surroundings. Nothing matters to them anymore. Others have a constant sense of impending doom and cannot consider a positive alternative. Men exhibit signs of anger and restlessness, while women have excessive feelings of guilt, sleepiness, hunger, etc. Obviously, this varies from person to person.  Apart from this, all the above-listed symptoms are warnings signs of depression. A person who exhibits such signs needs medical intervention as soon as possible.  Datasets Used to Analyze Depression  Using the following datasets,

Read More
Services
Data Engineering
Azure
AWS
GCP
Big Data
Data Warehousing
AI & Machine Learning
Artificial Intelligence
Natural Language Processing
Vision Analytics
Large Language Model (LLM)
Business Intelligence
PowerBI
Tableau

DataToBiz is a Data Science, AI, and BI Consulting Firm that helps Startups, SMBs and Enterprises achieve their future vision of sustainable growth.

Hire Developers
Get In Touch
Use Cases
Digital Transformation
AI Insurance Automation
Boutique Analytics
Ecommerce Analytics
Manufacturing Analytics
Digital Lending Automation
Sales Analytics
OEE Analytics
HR Analytics
Procurement Analytics
IT JIRA tracking
Products
PrepAI
Tally BI
Marketing Cockpit
Virtual Try On Platform
HirelakeAI
SensiblyAI
DataToBiz CV Platform
Quick Links
Careers
About
Partner Program
Knowledge Base
Case Studies
Industries

DataToBiz is a Data Science, AI, and BI Consulting Firm that helps Startups, SMBs and Enterprises achieve their future vision of sustainable growth.

Hire Developers
Get In Touch
DMCA.com Protection Status
Hire Developers
Request a Quote